anchor.diff:  9.c,TRUE,9,http://unstats.un.org/sdgs/files/metadata-compilation/Metadata-Goal-9.pdf,13,Significantly increase access to information and communications technology and strive to provide universal and affordable access to the Internet in least developed countries by 2020.,9.c.1,"Proportion of population covered by a mobile network, by technology",ITU,Partnership on Measuring ICT for Development,"The indicator percentage of the population covered by a mobile network, broken down by technology, refers to the percentage of inhabitants living within range of a mobile-cellular signal, irrespective of whether or not they are mobile phone subscribers or users. This is calculated by dividing the number of inhabitants within range of a mobile-cellular signal by the total population and multiplying by 100. \nThe indicator is based on where the population lives, and not where they work or go to school, etc. When there are multiple operators offering the service, the maximum population number covered should be reported. Coverage should refer to broadband (3G and more) and narrowband (2G) mobile-cellular technologies and include: \n\t2G mobile population coverage: Mobile networks with access to data communications (e.g. Internet) at downstream speeds below 256 kbit/s. This includes mobile-cellular technologies such as GPRS, CDMA2000 1x and most EDGE implementations. The indicator refers to the theoretical ability of subscribers to use non-broadband speed mobile data services, rather than the number of active users of such services. \n\t3G and above mobile-population coverage: Refers to the number of mobile-cellular subscriptions with access to data communications (e.g. the Internet) at broadband downstream speeds (defined here as greater than or equal to 256 kbit/s). The indicator refers to the theoretical ability of subscribers to use broadband speed mobile data services, rather than the number of active users of such services. This includes all high-speed mobile-cellular telephone subscriptions with access to data communications, and includes mobile-cellular technologies such as WCDMA (UMTS) and associated technologies such as HSPA, CDMA2000 1x EV-DO, mobile WiMAX 802.16e and LTE. It excludes low-speed mobilebroadband subscriptions and fixed (wired) Internet subscriptions. \nAs technologies evolve and as more and more countries will deploy and commercialize more advanced mobilebroadband networks (4G, 5G etc.), the indicator will include further breakdowns. \nITU collects data for this indicator through an annual questionnaire from national telecommunication regulatory authorities or Information and Communication Technology (ICT) Ministries, who collect the data from licensed mobile-cellular operators. However, they are likely to have different levels and locations of coverage. Another method would be to request each operator's coverage maps, which can be overlaid with maps showing the population of the country.",,"The percentage of the population covered by a mobile cellular network can be considered as a minimum indicator for ICT access since it provides people with the possibility to subscribe to and use mobile-cellular services to communicate. Over the last decade, mobile-cellular networks have expanded rapidly and helped overcome very basic infrastructure barriers that existed when fixed-telephone networks ' often limited to urban and highly populated areas - were the dominant telecommunication infrastructure. \nWhile 2G (narrowband) mobile-cellular networks offer limited (and mainly voice-based) services, higher-speed networks provide increasingly high-speed, reliable and high-quality access to the Internet and its increasing amount of information, content, services, and applications. Mobile networks are therefore essential to overcoming infrastructure barriers, helping people join the information society and benefit from the potential of ICTs, in particular in least developed countries. \nThe indicator highlights the importance of mobile networks in providing basic, as well as advanced communication services and will help design targeted policies to overcome remaining infrastructure barriers, and address the digital divide. Many governments track this indicator and have set specific targets in terms of the mobile population coverage (by technology) that operators must achieve.",,,,,,,"This indicator is based on an internationally agreed definition and methodology, which have been developed under the coordination of ITU, through its Expert Groups and following an extensive consultation process with countries. It is also a core indicator of the Partnership on Measuring ICT for Development's Core List of Indicators, which has been endorsed by the UN Statistical Commission (last time in 2014). \nITU collects data for this indicator through an annual questionnaire from national regulatory authorities or Information and Communication Technology Ministries, who collect the data from Internet service providers. By 2014, data on 2G mobile population coverage were available for about 144 countries, from developed and developing regions, and covering all key global regions. Data on 3G mobile population coverage were available for 135 countries. ITU publishes data on this indicator yearly.",,,"Based on the data for the percentage of the population covered by a mobile network, broken down by technology, and on rural population figures, countries can produce estimates on rural and urban population coverage. ITU produces global estimates for the rural population coverage, by technology.","ITU produces regional and global aggregates for the 'percentage of the population covered by a mobile network, broken down by technology. \nYear-end data are released in December of the following year through the ITU World Telecommunication/ICT Indicators Database.","Some countries have difficulty calculating overall mobile-cellular population coverage. In some cases, data refer only to the operator with the largest coverage, and this may understate the true coverage.",,,,"ITU Handbook (http://www.itu.int/en/ITU-D/Statistics/Pages/publications/handbook.aspx) for the collection of Administrative Data on Telecommunications/ICT, 2011 (and revisions and new indicators)",1.4,2.3,2.c,9.1,11.b,13.1,,,,,,,,,,,,,,,,,,,,,,,,,
   10.1,TRUE,10,http://unstats.un.org/sdgs/files/metadata-compilation/Metadata-Goal-10.pdf,2,"By 2030, progressively achieve and sustain income growth of the bottom 40 per cent of the population at a rate higher than the national average.",10.1.1,Growth rates of household expenditure or income per capita among the bottom 40 per cent of the population and the total population,OHCHR,,"Real disposable household income is the sum of wages and salaries, mixed income, net property income, net current transfers and social benefits other than social transfers in kind, less taxes on income and wealth and social security contributions, after adjustment for price changes.",,,,,,,,,The main data source is household surveys.,,,"This indicator should be disaggregated by ethnicity, sex, age, geographic location, disability, religion, migratory or displacement status, civil status, and other statuses relevant at the national level, which may for example include minority or indigenous status, language spoken at home, etc.","The World Bank collects some relevant data at global level, although this indicator is not currently computed.","In many national contexts, household surveys, which are the main data source for this indicator, exclude the homeless or low-income groups without access to telephones. Face-to-face surveys often exclude non-urban populations or members of linguistic minorities.","In many instances, household surveys are conducted only with the 'head' of the household, who answers for other persons living at the same address. As this is most often the oldest male resident, the indicator may not fully capture the experience of women or give a picture of women's control over their income and resources. Where it is not feasible for this reason to disaggregate by sex, the indicator should be disaggregated for female-headed households.",,,World Bank data: http://data.worldbank.org/,1.2,10.2,10.3,10.4,,,,,,,,,,,,,,,,,,,,,,,,,,,
   10.2,TRUE,10,http://unstats.un.org/sdgs/files/metadata-compilation/Metadata-Goal-10.pdf,3,"By 2030, empower and promote the social, economic and political inclusion of all, irrespective of age, sex, disability, race, ethnicity, origin, religion or economic or other status.",10.2.1,"Proportion of people living below 50 per cent of median income, by age, sex, and persons with disabilities",OHCHR,,"The indicator is calculated as the proportion of persons living in households (adjusted for household size) below 60% of the national median income, using population-weighted subgroup estimates from household surveys.",,"This indicator is a measure of relative income poverty at the national level. It measures how far individuals are from the median standard of living, approximating a measure of social exclusion. Persons living in relative poverty often experience many other forms of social and economic disadvantage through unemployment, poor housing, inadequate health care and barriers in accessing education and economic, social, political and cultural activities, which can result from social stigmatisation.",,,,,,,The main data source is household surveys.,,,"This indicator should be disaggregated by ethnicity, sex, age, geographic location, disability, religion, migratory or displacement status, civil status, and other statuses relevant at the national level, which may for example include minority or indigenous status, language spoken at home, etc.","At the international and regional levels, OECD and the EU both collect these data for their Member States. The World Bank currently compiles data on percentage of people below national (i.e. country'specific) poverty lines, but this could be amended or supplemented to include this comparable indicator.","In many national contexts, household surveys, which are the main data source for this indicator, exclude the homeless or low-income groups without access to telephones. Face-to-face surveys often exclude non-urban populations or members of linguistic minorities. Because it focuses on income only, this indicator does not measure other forms of poverty, and should therefore be supplemented with other indicators on access to adequate housing, social services, health care, as well as the assets or expenses of the household (e.g. home owners will have more disposable income than renters with the same household income).","In many instances, household surveys are conducted only with the 'head' of the household, who answers for other persons living at the same address. As this is most often the oldest male resident, the indicator may not fully capture the experience of women or give a picture of women's control over their income and resources. Where it is not feasible for this reason to disaggregate by sex, the indicator should be disaggregated for female-headed households.",,,,1.2,1.3,5.1,10.1,10.3,10.4,,,,,,,,,,,,,,,,,,,,,,,,,
  -10.3,TRUE,10,http://unstats.un.org/sdgs/files/metadata-compilation/Metadata-Goal-10.pdf,4,"Ensure equal opportunity and reduce inequalities of outcome, including by eliminating discriminatory laws, policies and practices and promoting appropriate legislation, policies and action in this regard.",10.3.1,Percentage of the population reporting having personally felt discriminated against or harassed within the last 12 months on the basis of a ground of discrimination prohibited under international human rights law,OHCHR,TST,"International human rights law outlaws discrimination against population groups on the basis of specific characteristics or 'grounds'. The grounds of discrimination prohibited under international human rights law, as enshrined in the 1948 Universal Declaration of Human Rights and subsequently elaborated upon by international human rights mechanisms, include ethnicity, sex, age, income, geographic location, disability, religion, migratory or displacement status, civil status, sexual orientation and gender identity. While some grounds are common to all countries and follow standard definitions, such as sex, age or disability, the precise categories to be included under grounds such as ethnicity, geographic location and religion will vary according to national circumstances and should be determined in a participatory process at national level. \nThe indicator is calculated as the percentage of persons reporting having personally felt discriminated against or harassed within the last 12 months on the basis of a ground of discrimination prohibited under international human rights law. This will be calculated using the full survey results, with techniques of imputation, estimation and data weighting to ensure a representative sample and data reliability.",,"This outcome indicator provides a measure of how well non-discriminatory laws and policies are applied in practice, from the perspective of the population. It is based on personal experience rather than perception to ensure greater validity of data, as perceptions of the experience of others may themselves be affected by stereotyping.",,,,,,,The primary data source is surveys conducted at the national or regional level.,,,"Data for this indicator should be disaggregated by ground of discrimination, relationship with the person or entity felt to have discriminated (employer/employee, public official or employee, private enterprise, teacher/student, etc.), and place where the discrimination occurred (work, street, home, school, etc.).","Data for this indicator are collected in an increasing number of countries. At the regional level, the EU Fundamental Rights Agency has collected the data for 27 EU Member States. Relevant data is also collected in Eurobarometer and Afrobarometer surveys, and this question could easily be added.","Because the indicator measures the percentage of the population reporting discrimination during the time period, each victim is counted only once, irrespective of the number of times discrimination or harassment was experienced. Without this information, the indicator does not therefore permit estimates of incidence of discrimination. \nIn many national contexts, surveys may exclude the homeless or low-income groups without access to telephones. Face-to-face surveys often exclude non-urban populations or members of linguistic minorities. There is evidence to suggest that the most marginalised populations are less likely to respond to surveys, but this effect is reduced by ensuring their participation in the preparation of the survey.","Data for the indicator should be disaggregated by sex, sexual orientation and gender identity. Multiple grounds of discrimination (e.g. women members of an ethnic minority who have suffered discrimination based on both sex and ethnicity) should be noted.",,,FRA survey data and methodology:\nhttp://fra.europa.eu/en/survey/2012/eu-midis-european-union-minorities-and-discrimination-survey,10.2,16.3,16.b,,,,,,,,,,,,,,,,,,,,,,,,,,,,
  +10.3,TRUE,10,http://unstats.un.org/sdgs/files/metadata-compilation/Metadata-Goal-10.pdf,4,"Ensure equal opportunity and reduce inequalities of outcome, including by eliminating discriminatory laws, policies and practices and promoting appropriate legislation, policies and action in this regard.",10.3.1,Proportion of the population reporting having personally felt discriminated against or harassed within the previous 12 months on the basis of a ground of discrimination prohibited under international human rights law,OHCHR,TST,"International human rights law outlaws discrimination against population groups on the basis of specific characteristics or 'grounds'. The grounds of discrimination prohibited under international human rights law, as enshrined in the 1948 Universal Declaration of Human Rights and subsequently elaborated upon by international human rights mechanisms, include ethnicity, sex, age, income, geographic location, disability, religion, migratory or displacement status, civil status, sexual orientation and gender identity. While some grounds are common to all countries and follow standard definitions, such as sex, age or disability, the precise categories to be included under grounds such as ethnicity, geographic location and religion will vary according to national circumstances and should be determined in a participatory process at national level. \nThe indicator is calculated as the percentage of persons reporting having personally felt discriminated against or harassed within the last 12 months on the basis of a ground of discrimination prohibited under international human rights law. This will be calculated using the full survey results, with techniques of imputation, estimation and data weighting to ensure a representative sample and data reliability.",,"This outcome indicator provides a measure of how well non-discriminatory laws and policies are applied in practice, from the perspective of the population. It is based on personal experience rather than perception to ensure greater validity of data, as perceptions of the experience of others may themselves be affected by stereotyping.",,,,,,,The primary data source is surveys conducted at the national or regional level.,,,"Data for this indicator should be disaggregated by ground of discrimination, relationship with the person or entity felt to have discriminated (employer/employee, public official or employee, private enterprise, teacher/student, etc.), and place where the discrimination occurred (work, street, home, school, etc.).","Data for this indicator are collected in an increasing number of countries. At the regional level, the EU Fundamental Rights Agency has collected the data for 27 EU Member States. Relevant data is also collected in Eurobarometer and Afrobarometer surveys, and this question could easily be added.","Because the indicator measures the percentage of the population reporting discrimination during the time period, each victim is counted only once, irrespective of the number of times discrimination or harassment was experienced. Without this information, the indicator does not therefore permit estimates of incidence of discrimination. \nIn many national contexts, surveys may exclude the homeless or low-income groups without access to telephones. Face-to-face surveys often exclude non-urban populations or members of linguistic minorities. There is evidence to suggest that the most marginalised populations are less likely to respond to surveys, but this effect is reduced by ensuring their participation in the preparation of the survey.","Data for the indicator should be disaggregated by sex, sexual orientation and gender identity. Multiple grounds of discrimination (e.g. women members of an ethnic minority who have suffered discrimination based on both sex and ethnicity) should be noted.",,,FRA survey data and methodology:\nhttp://fra.europa.eu/en/survey/2012/eu-midis-european-union-minorities-and-discrimination-survey,10.2,16.3,16.b,,,,,,,,,,,,,,,,,,,,,,,,,,,,
   10.4,TRUE,10,http://unstats.un.org/sdgs/files/metadata-compilation/Metadata-Goal-10.pdf,6,"Adopt policies, especially fiscal, wage and social protection policies, and progressively achieve greater equality.",10.4.1,"Labour share of GDP, comprising wages and social protection transfers",ILO,,The definition of the labor share is based on ILO (2014a) and augmented with social protection transfers including (but not only) employers' social security contributions.,,"The current indicator mistakenly overlooks the internationally agreed definition of social protection, mainly based on cash transfers (eg pensions, disability, child and maternity benefits, etc). . Furthermore, coverage of social protection floor is already captured in indicator 1.3. In contrast, the alternative indicator addresses income distribution directly. \nThe rationale is to monitor progress toward Target 10.4 encompassing all three policies (fiscal, wage, social protection) and their impact on inequality. \nThe indicator provides and an aggregate measure of primary income inequality, offering insights the role that social protection can have in reducing it.",,,,,,,,,,"National estimates: total. \nGlobal estimates: total, by region, national income level.","Data for global and regional monitoring are extracted from administrative data. They are available in ILO (2014a) and IMF (2014) databases and in the System of National Accounts, for 200 countries.",,The indicator is aggregate and not available by sex.,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
   10.5,FALSE,10,http://unstats.un.org/sdgs/files/metadata-compilation/Metadata-Goal-10.pdf,7,Improve the regulation and monitoring of global financial markets and institutions and strengthen the implementation of such regulations.,10.5.1,Financial Soundness Indicators,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
   10.6,TRUE,10,http://unstats.un.org/sdgs/files/metadata-compilation/Metadata-Goal-10.pdf,8,"Ensure enhanced representation and voice for developing countries in decision-making in global international economic and financial institutions in order to deliver more effective, credible, accountable and legitimate institutions.",10.6.4,Proportion of members and voting rights of developing countries in international organizations,OHCHR,,"The indicator is computed as the number of voting rights allocated to developing countries, divided by the total number of voting rights in international organizations, multiplied by 100.",,"The UN is based on a principle of sovereign equality of all its Member States (Article 2, UN Charter). Voting rights in international organizations, particularly those under the auspices of the UN system, should respect this principle. This indicator aims to measure the degree to which States enjoy equal representation in international organizations.",,,,,,,"The data for this indicator are publicly available in the founding documents of each international organization, as updated.",,,"Data should be calculated and presented separately for each organization (World Bank, IMF, etc.).",,"To be meaningful, the indicator must be compared to the relevant percentage of UN Member States, i.e. the voting rights in the General Assembly. This is a structural indicator. Such indicators do not in general track gradual change or progress, but they are useful to demonstrate a state of affairs or policy commitments.",,,,,16.3,16.8,17.1,,,,,,,,,,,,,,,,,,,,,,,,,,,,
  
positive.code: 16.1,TRUE,16,http://unstats.un.org/sdgs/files/metadata-compilation/Metadata-Goal-16.pdf,6,Significantly reduce all forms of violence and related death rates everywhere.,16.1.2,"Conflict-related deaths per 100,000 population, by sex, age and cause",Goal 16 TST Working Group,OHCHR,"From Goal 16 TST Working Group, OHCHR:\nIntentional homicide is defined as the unlawful death inflicted upon a person with the intent of cause death or serious injury (Source: International Classification of Crime for Statistical Purposes, 2015). In a narrow sense, conflict-related deaths refer to those deaths caused by warring parties directly related to combat, such as traditional battlefield fighting and bombardments. In a broader sense, conflict-related deaths also include killings that amount to war crimes, such as targeting of civilians or of military 'hors combat'. The rates are defined as the total count of intentional homicides and conflict-related deaths, respectively, divided by the total resident population, expressed per 100,000 population.\n\n From United Nations Mine Action Service: \n The count of conflict-related deaths caused by mines/ERW should include ""individuals killed or injured in incidents involving devices detonated by the presence, proximity, or contact of a person or a vehicle, such as all antipersonnel mines, antivehicle mines, abandoned explosive ordnance (AXO), unexploded ordnance (UXO), and victim-activated IEDs.""",,"From Goal 16 TST Working Group, OHCHR:\nThese indicators refer to two forms of violent deaths (intentional homicide and conflict-related deaths). Intentional homicides occur in all countries of the world and have global applicability, while conflict-related deaths occur in countries afflicted by wars. \nThe rates of intentional homicide and conflict-related deaths should be kept separate, as combining them into one single indicator would risk collating two distinct phenomena and unequal sources of data. In particular, the quality of data on conflictrelated deaths is inevitably affected by the difficulties of producing accurate statistics in situations of armed conflict. \nMonitoring intentional homicides is necessary to better assess their causes and consequences and, in the longer term, to develop effective prevention measures. It is based on statistical data routinely produced by law enforcement authorities and/or public health institutions, with a high degree of international comparability. \nConflict-related deaths measure the direct impact of conflicts on populations in terms of losses of life. Whilst the global risk of violent death in armed conflict is generally lower than the global risk of homicidal violence, in affected countries armed conflict destroys lives and exerts substantial human costs, particularly in protracted internal conflict situations.\n\n From United Nations Mine Action Service: \n The presence of mines/ERW in conflict and post-conflict contexts is devastating for people and communities. These hazards cause grievous injury and death, impede peace operations, and hamper post-conflict reconstruction and development efforts. \nFindings from the M&E Mechanism for the UN Strategy 2013-2018 (UN M&E Mechanism) illustrate the deadly risk posed by mines/ERW in affected countries and territories in which the UN operates; in particular, the disproportionate impact of explosive hazards on the civilians who constitute more than half of the casualties from mines/ERW. The regular monitoring of mine/ERW casualty data through the global mechanism of the Sustainable Development Goals will significantly enhance the capacity of affected countries and territories including Member States, UN entities, and civil society to understand the scope of these threats and effectively mitigate the harms they cause.",,,,,,,"From Goal 16 TST Working Group, OHCHR:\nOn intentional homicide, two separate sources exist at country level: a) criminal justice system; b) public health/civil registration. UNODC collects and publishes data from criminal justice systems through its annual data collection (UN Crime Trends Survey, UN-CTS); WHO collects and publishes data produced by public health/civil registration. \nUNODC and WHO are working together to harmonize data and procedures to produce joint UNODC-WHO homicide estimates at country, regional and global level. \nConsidering data collected by both UNODC and WHO, national data on homicide are available for 174 countries (at least one data point after 2009) . Time series data on homicide suitable for monitoring are available for 141 countries (at least 3 data points, the most recent for 2011 or later).When national data on homicide are not available, estimates are produced by WHO. \nIn general, no national data sources exist on conflict-related deaths, as normal registration systems are heavily affected by war operations. Estimates of conflictrelated deaths, often displaying wide variations, are produced at international level: conflict death databases include the IISS Armed Conflict Database, the UCDP BattleRelated Deaths Dataset, PRIO Battle-Deaths Data and WHO estimates of deaths by cause.\n\n From United Nations Mine Action Service: \n Many member states affected by mines/ERW have casualty reporting systems in place. The most common, in use in 80% of mine action programmes globally, is the Information Management System for Mine Action (IMSMA).",,,"From Goal 16 TST Working Group, OHCHR:\nRecommended disaggregations for this indicator are: \n\tBy context (intentional homicide and conflict-related deaths) \nOn intentional homicide, possible disaggregations include: \n\tsex and age of victim and perpetrator \n\trelationship between victim and perpetrator(intimate partner, other family member, acquaintance, etc.) \n\tmeans of perpetration (firearm, blunt object, etc.) \n\tsituational context/motivation (organized crime, intimate partner violence, etc.) \n\tby region \n\tby population group \n\tby displacement and statelessness status. \nOn conflict-related-deaths, possible disaggregations include: \n\tsex and age of victim and perpetrator \n\tcivilian versus military status of victim.\n\n From United Nations Mine Action Service: \n Recommended disaggregation for this indicator: \n\tVictim sex and age (Man, Woman, Boy, Girl) \n\tDevice type (See below) \n\tVictim type (Civilian, Non-civilian, Operator) \nData from the M&E Mechanism for the UN Strategy for Mine Action 2013-2018 indicates that at least 86% of casualty data is available with sex and age disaggregation in participating countries and territories.","From Goal 16 TST Working Group, OHCHR:\nAt international level, data on intentional homicides are routinely collected and disseminated by the United Nations Office on Drugs and Crime (UNODC) and the World Health Organization. Several regional organizations collect and disseminate homicide data, especially in the Americas (OAS and IDB) and in Europe (Eurostat). Conflict death databases, at the international level, include the IISS Armed Conflict Database, the UCDP Battle-Related Deaths Dataset, and PRIO Battle-Deaths Data and WHO estimates of deaths by cause database. National level datasets exist for some countries.\n\n From United Nations Mine Action Service: \n The Landmine and Cluster Munitions Monitor provides several research products including annual reports on a variety of indicators related to mines, cluster munitions, and other ERW, including casualty data. The UN Interagency Working Group for Mine Action currently tracks casualty data in participating countries and territories as part of the M&E Mechanism for the UN Strategy for Mine Action 2013-2018.","The ICCS provides important clarifications on the exact definition of intentional homicide for statistical purposes. In particular, it states that the following killings need to be included in the count of homicide: \n\tMurder \n\tHonour killing \n\tSerious assault leading to death \n\tDeath as a result of terrorist activities \n\tDowry-related killings \n\tFemicide \n\tInfanticide \n\tVoluntary manslaughter \n\tExtrajudicial killings \n\tKillings caused by excessive force by law enforcement/state officials \nFurthermore, the ICCS provides indications on how to distinguish between intentional homicides, killings directly related to war/conflict and other killings that amount to war crimes. \nHomicide data can be produced by two separate and independent sources and this can be used to assess accuracy of national data. Usually, for countries where data from both sources exist, a good level of matching between the sources is recorded (see UNODC Global Study on Homicide, 2013). \nData on homicides produced by public health authorities are guided by the International classification of diseases (ICD-10), which is very similar to the definition of intentional homicide provided by the ICCS. \nData on conflict-related deaths are characterised by large variability due to uncertainty of estimates.","From Goal 16 TST Working Group, OHCHR:\nWhen properly disaggregated, intentional homicide can be used to quantify genderbased killings, a relevant indicator to monitor violence against women. Currently, 68 countries have reported homicide data disaggregated by type of perpetrator to UNODC (at least one data point after 2009).\n\n From United Nations Mine Action Service: \n Findings from the UN M&E Mechanism align with findings from other research demonstrating the disproportionate impact of mins/ERW on boys and men. Boys and men constitute 91% of mine/ERW casualties in countries participating in the M&E Mechanism. This trend is consistent across civilians, non-civilians, and operators; and it is mirrored across age and gender distribution data among beneficiaries of victim assistance services.",,"From Goal 16 TST Working Group, OHCHR:\nAt global level, intentional homicide is the most prevalent type of violent death. In 2012, the ratio between victims of conflict/war and victims of intentional homicide varied between one to five to one to ten (uncertainty due to variability of estimates of deaths related to war/conflict produced respectively by WHO and Uppsala Conflict Data Program). \nNon-intentional homicide is another crime that can provide information on violence prevalence. Though, it mostly refers to cases of killings due to negligent behaviours rather than to intentional violence. For nine countries where data are available, 95% of all non-intentional homicide are due to vehicular homicide. As situations of conflict affect a limited number of countries at a given time, the indicator is relevant for certain country contexts.\n\n From United Nations Mine Action Service: \n Different types of devices which cause death/injury: \n\tAntipersonnel mines \n\tAntivehicle mines \n\tAbandoned explosive ordnance (AXO) \n\tUnexploded ordnance (UXO) \n\tVictim-activated improvised explosive devices (IEDs).","From Goal 16 TST Working Group, OHCHR:\nUNODC, Global Study on Homicide 2011; UNODC, Global Study on Homicide 2013; WHO-UNDP-UNODC, Global Status Report on Violence Prevention 2014; \nIgarape Institute, Homicide Monitor, 2015 (http://homicide.igarape.org.br/ ); UNODC, International Classification of Crime for Statistical Purposes, 2015\n\n From United Nations Mine Action Service: \n \nThe Monitoring & Evaluation Mechanism for the UN Strategy for Mine Action 2013-2018. \nThe Landmine and Cluster Munitions Monitor (http://www.the-monitor.org/en-gb/home.aspx) \nGeneva International Centre for Humanitarian Demining (http://www.gichd.org/)",,,,,,,,,United Nations Mine Action Service,,,,,,,,,,,,,,,,,,,,,,
  16.1,FALSE,16,http://unstats.un.org/sdgs/files/metadata-compilation/Metadata-Goal-16.pdf,9,Significantly reduce all forms of violence and related death rates everywhere.,16.1.3,"Proportion of population subjected to physical, psychological or sexual violence in the previous 12 months",,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
  16.1,FALSE,16,http://unstats.un.org/sdgs/files/metadata-compilation/Metadata-Goal-16.pdf,10,Significantly reduce all forms of violence and related death rates everywhere.,16.1.4,Proportion of people that feel safe walking alone around the area they live,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
  16.2,FALSE,16,http://unstats.un.org/sdgs/files/metadata-compilation/Metadata-Goal-16.pdf,11,"End abuse, exploitations, trafficking and all forms of violence against and torture of children.",16.2.1,Percentage of children aged 1-17 years who experienced any physical punishment and/or psychological aggression by caregivers in the past month,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
  16.2,TRUE,16,http://unstats.un.org/sdgs/files/metadata-compilation/Metadata-Goal-16.pdf,11,"End abuse, exploitations, trafficking and all forms of violence against and torture of children.",16.2.2,"Number of victims of human trafficking per 100,000 population, by sex, age and form of exploitation",UNODC and OHCHR,Goal 16 TST Working Group,"From UNODC and OHCHR: \n Trafficking in persons is defined as the recruitment, transportation, transfer, harbouring or receipt of persons, by means of the threat or use of force or other forms of coercion, of abduction, of fraud, of deception, of the abuse of power or of a position of vulnerability or of the giving or receiving of payments or benefits to achieve the consent of a person having control over another person, for the purpose of exploitation. Exploitation shall include, at a minimum, the exploitation of the prostitution of others or other forms of sexual exploitation, forced labour or services, slavery or practices similar to slavery, servitude or the removal of organs (The United Nations Protocol to Prevent Suppress and Punish Trafficking in Persons, especially Women and Children, which is supplementing the United Nations Convention against Transnational Organized Crime). \nThe number of victims is defined as the number of detected and estimated number of non-detected adult women and men and girls and boys (18-) who have been trafficked for different forms of trafficking in persons. The estimated ratio between the number of detected victims and the estimated number of non-detected victims can be used to estimate the total number of human trafficking victims at national, regional and global levels. In addition, the ratio can be used to measure the efficiency of countries to detect trafficking victims. \n\n From Goal 16 TST Working Group: \n This is an outcome indicator derived from administrative data. The indicator is computed as the total number of identified victims of trafficking divided by population (per 100,000 persons). This indicator directly measures exploitation and trafficking, which are inadequately captured by the other proposed indicators. These human rights abuses affect both adults and children, and States have existing obligations to prevent them for both population groups.",,"From UNODC and OHCHR: \n Human trafficking for different forms of exploitation represents a major violation of victim's human rights, dignity and inclusion to the society. It has an impact on a person's health and opportunities, it creates economic inequalities and it is a threat to the personal security. The regular production of figures on this indicator will allow the monitoring of the impact of the anti-trafficking measures to the level of trafficking at national, regional and global levels. It also helps to assess the capacity of countries to detect and consequently support victims of trafficking. It will raise awareness on the most prevalent forms of trafficking in persons in different parts of the world. \n\n From Goal 16 TST Working Group: \n Trafficking in persons is a universal form of modern-day slavery. Trafficked persons are often victims of physical, sexual and psychological violence. The demand for cheap labour and sexual services, coupled with criminal practices that seek to profit from the exploitation of vulnerable people, is its main driver. Addressing this most egregious violation of human rights would significantly contribute to one of the main priorities of post-2015 namely to ""leave no one behind"" and has its legal basis in the UN Convention on Transnational Organized Crime and the optional protocol on human trafficking.",,,,,,,"From UNODC and OHCHR: \n Currently, the available and country specific number of detected victims is collected yearly from the Member States using a specific questionnaire. It is published in the UNODC biennial Global Report on Trafficking in Persons. Data are available for about 130 countries, since 2007. The data is disaggregated for age, sex and forms of exploitation. The estimated number of non-detected victims can be established by applying methodologies developed to measure the estimated number of different hidden populations (e.g. Respondent Driven Sampling and Network Scale-up Method). These methodologies have been tested with different forms of trafficking in persons. \n\n From Goal 16 TST Working Group: \n A primary data source will be administrative and judicial records maintained by competent national authorities, which may include police, labour inspectors, health care providers, educational institutions, national human rights institutions and ombudspersons, as well as civil society organizations. Current data sources include the UNODC Global Report on Trafficking in Persons, the U.S. Department of State's Trafficking in Persons Report; IOM Trafficked Migrants Assistance Database.",,,"From UNODC and OHCHR: \n Recommended disaggregation for this indicator is: \n\tsex of the victim \n\tage of the victim \n\tform of exploitation \n\n From Goal 16 TST Working Group: \n Data for this indicator should be disaggregated by sex, age, population group (ethnicity, minority or indigenous status) and nationality of the victim and, where relevant, perpetrator, by geographic location, and by type of perpetrator (private enterprise, individual, etc.).","From UNODC and OHCHR: \n UNODC is the only international organization which is regularly collecting and disseminating data on the number of detected victims of human trafficking at the global level. Selected data on specific forms of trafficking in persons are collected and disseminated by ILO, UNICEF and UNHCR. Regional and geographically defined data is collected by IOM and some regional organizations such as EU. The Academia has developed a list of local studies assessing the hidden part of trafficking for specific geographical areas and forms of exploitation. \n\n From Goal 16 TST Working Group: \n At the international level, the ILO compiles data on trafficking, slavery, exploitation and forced labour. Data on trafficked persons is published by UNODC in its biennial Global Report on Trafficking in Persons, and in the IOM Human Trafficking Database.","From UNODC and OHCHR: \n In 2013 and 2014, UNODC has conducted two Expert Group Meetings with the academia on measuring different hidden populations. The work has resulted in a methodology to measure the hidden part of trafficking in persons in order to estimate the number of non-detected victims of trafficking. The methodology has been used in some studies and will be soon tested by UNODC. \n\n From Goal 16 TST Working Group: \n As it relies upon reports of individual events, this indicator may not be fully reliable. It may underestimate (or sometimes, though more rarely, overestimate) the true number of victims. These human rights abuses are, by their nature, hidden and in most instances, the number of cases reported will depend on awareness of victims of their rights, access to information, motivation and perseverance of civil society organizations and the media. \nData are compiled separately for each human rights abuse and aggregated. In order to reduce the total number of global indicators, this indicator is proposed to monitor targets 5.2 (violence against women), 8.7 (elimination of the worst forms of child labour and forced labour), 16.1 (violence), 16.2 (violence against children) and 16.4 (organised crime). Organized crime often includes significant human rights abuses, including trafficking, slavery, exploitation and forced labour, against both children and adults. Victims of such crimes are among the most invisible in official statistics, so it is vital that these abuses are monitored within the SDG framework to ensure that no one is left behind.","From UNODC and OHCHR: \n Trafficking in persons has a negative impact particularly on women. Currently, 70 % of detected victims of trafficking in persons are female: adult women (49%) and girls (21%). The international community stressed this aspect already when they adopted the international instrument to address trafficking which is titled: The UN Protocol to Prevent, Suppress and Punish Trafficking in Persons, especially Women and Children.",,"From UNODC and OHCHR: \n The General Assembly in resolution A/RES/64/293 mandated UNODC to report every two years on trafficking in persons flows and patterns, at the national, regional and international levels. \nAs to the results of current data collection, we can see that between 2007 and 2013, there is a slight increase in the number of detected victims per 100,000 population. There should be a continuous monitoring of this trend and it should be combined with the number of non-detected victims to understand the changes in the severity of trafficking in persons.","From UNODC and OHCHR: \n UNODC Global Report on Trafficking in Persons 2009, 2012 and 2014, www.unodc.org/glotip.html \nUNODC, International Classification of Crime for Statistical Purposes, 2015",5.2,8.7,16.1,16.2,16.4,,,,,,,,,,,,,,,,,,,,,,,,,,
  16.2,TRUE,16,http://unstats.un.org/sdgs/files/metadata-compilation/Metadata-Goal-16.pdf,13,"End abuse, exploitations, trafficking and all forms of violence against and torture of children.",16.2.3,Proportion of young women and men aged 18-29 years who experienced sexual violence by age 18,UNICEF,,"This indicator provides the proportion of young women and men aged 18-24 years who report having experienced any sexual violence by age 18. It is calculated by dividing the number of young women and men aged 18-24 years who report having experienced any sexual violence by age 18 by the total number of young women and men aged 18-24 years, respectively, in the population.",,"While it is recognized that this indicator captures only one of the gravest forms of violence against children rather than being inclusive of all forms, it can be considered a proxy indicator that reflects a key aspect of the change we want to observe in order to achieve the target of elimination of VAC. \nThe right of children to protection from all forms of violence is enshrined in the Convention on the Rights of the Child and its Optional Protocols. 'Sexual violence' as defined in General Comment No. 13 on the Convention of the Rights of the Child, accessible here: http://www2.ohchr.org/english/bodies/crc/docs/CRC.C.GC.13_en.pdf",,,,,,,Household surveys such as DHS have been collecting data on this indicator in low- and middleincome countries since the late 1990s.,,,"Data are available by age, marital status, place of residence and wealth quintiles.","UNICEF has estimates for the percentage of young women aged 18-24 years who report having experienced any sexual violence by age 18, disaggregated by age, marital status, place of residence and wealth quintile by country and for some (flexible) regional groupings with sufficient population coverage. Fully comparable data are currently available for approximately 43 countries.6 UNICEF has estimates for the percentage of young men aged 18-24 years who report having experienced any sexual violence by age 18, disaggregated by age, marital status, place of residence and wealth quintile by country for approximately 5 countries.","The availability of comparable data remains a serious challenge in this area as many data collection efforts have relied on different study methodologies and designs, definitions of sexual violence, samples and questions to elicit information. A further challenge in this field is underreporting, especially when it comes to reporting on experiences of sexual violence among boys and men.","As this indicator is disaggregated by sex, it is well-suited for analysis of gender equality issues.",,UNICEF website on sexual violence data: \nhttp://data.unicef.org/child-protection/sexual-violence.html,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
  16.3,TRUE,16,http://unstats.un.org/sdgs/files/metadata-compilation/Metadata-Goal-16.pdf,15,Promote the rule of law at the national and international levels and ensure equal access to justice for all.,16.3.1,Proportion of victims of violence in the previous 12 months who reported their victimization to competent authorities or other officially recognized conflict resolution mechanisms,UNODC,OHCHR,"Number of victims of violent crime (physical or sexual assault) in the previous 12 months who reported their last incident to competent authorities or other officially recognized conflict resolution mechanisms, as a percentage of all victims of crime in the previous 12 months. \nCompetent authorities includes police, prosecutors or other authorities with competencies to investigate certain crimes (such as corruption or fraud), while 'other officially recognised conflict resolution mechanisms' may include a variety of institutions with a role in the informal justice or dispute resolution (e.g. tribal or religious leaders, village elders, community leaders), provided their role is officially recognised by state authorities.",,"Reporting to competent authorities is the first step for crime victims to seek justice: if competent authorities are not alerted they are not in a condition to conduct proper investigations and administer justice. However, lack of trust and confidence in the ability of the police or other authorities to provide effective redress, or objective and subjective difficulties in accessing them, can influence negatively the reporting behaviour of crime victims. As such, reporting rates provide a direct measure of the confidence of victims of crime in the ability of the police or other authorities to provide assistance and bring perpetrators to justice. Reporting rates provide also a measure of the 'dark figure' of crime, that is the proportion of crimes not reported to the police. Trends in reporting rates of violent crime can be used to monitor public trust and confidence in competent authorities on the basis of actual behaviours and not perceptions.",,,,,,,"Victimisation surveys provide direct information on this indicator, as they collect information on the experience of violent crime and on whether the victim has reported it to competent authorities. According to a recent review conducted by UNODC-INEGI Centre of Excellence on crime statistics, 72 countries have implemented at least one national victimisation after 2009 (in 43 of these countries the victimisation survey has been conducted by the national statistical office or another public institution/ministry). In addition, 9 African countries have already implemented or are in the process of implementing a victimisation survey module as part of the Strategy for Harmonisation of Statistics for Africa (SHaSA).",,,Recommended disaggregations for this indicator are: \n\tsex \n\ttype of crime \n\tethnicity \n\tmigration background \n\tcitizenship,UNODC collects data on crime reporting rates through the long-standing annual data collection mandated by the UN General Assembly UN-CTS. The UN-CTS has established a network of focal points (presently covering 125 countries and territories). Data on crime reporting rates are currently available for approximately 35 countries..,"The target relates to the multidimensional concepts of rule of law and access to justice and at least two indicators are required to cover the main elements of access to justice and efficiency of the justice system. The proposed indicator 16.3.1 covers the aspect of access to justice although it doesn't cover civil or administrative disputes. The indicator as formulated is a standard indicator widely published when a victimization survey is undertaken, but further work could be conducted to test the feasibility to expand the indicator to cover administrative disputes.","Independently of the level of violent victimization of women, it provides information on whether there are gender disparities on the attitude to freely and safely report their victimization experiences. For example, female victims of domestic violence are more reluctant to report to authorities their experience for different reasons, including fear of consequences and lack of trust in authorities. An increasing level of reporting indicates that measures have been successful to raise awareness that violent behaviours are unacceptable and/or reporting channels for victims of violent crime have improved and/or trust towards authorities has increased; moreover, higher reporting means that criminal justice institutions are in a better position to enforce the law and ensure justice.",,Reporting rates of crimes are known to vary widely by type of crime: they are usually higher in relation to property crimes as victims seek to re-obtain stolen goods or for insurance purposes.,"In 2010 UNODC-UNECE published a Manual on Victimization Surveys, that provides technical guidance on the implementation of such surveys, on the basis of good practices developed at country level. \nUNODC, International Classification of Crime for Statistical Purposes, 2015",,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
  
negative.code: 6.6,TRUE,6,http://unstats.un.org/sdgs/files/metadata-compilation/Metadata-Goal-6.pdf,25,"By 2020, protect and restore water-related ecosystems, including mountains, forests, wetlands, rivers, aquifers and lakes.",6.6.1,Change in the extent of water-related ecosystems over time,UNEP,CBD,"Percentage of change in water-related ecosystems over time (% change/year). The indicator would track changes over time in the extent of wetlands, forests and drylands, and in the minimum flows of rivers, volumes of freshwater in lakes and dams, and the groundwater table. The Ramsar Convention broad definition of ""wetland"" is used, which includes rivers and lakes, enabling three of the biome types mentioned in the target to be assessed - wetlands, rivers, lakes - plus other wetland types.","It is proposed to estimate percentage change in each major ecosystem present in a country, and the indicator will enable Member States to report on those water-related ecosystems that are important to them. \nWetland extent is computed through the existing Living Planet Index methodology for data collection and analysis (http://www.livingplanetindex.org/home/index). It consists of a number of stages including harvesting of time series data, codification and database entry, aggregation into sub-indices to reduce sampling bias, and further aggregation to create subglobal (ecologically and regionally specific) and global indices. The methodology is flexible to incorporating improving sources of information and data, for a more comprehensive assessment of trends. \nThe structure of the indicator can be designed to align with the SEEA Water accounts and estimate percentage change in Natural Water Capital available to society based on a) Mean Annual Water Availability; b) Mean Annual Water Withdrawals; c) Environmental Water requirements Aquastat (FAO); GEMS Water for national data (UNEP).","Definitions of target elements: \n\tProtect implies a reduction or eradication in loss or degradation \n\tRestore implies a reversal of loss or degradation \n\tMountains, Forests, Wetlands, Rivers, Aquifers and Lakes include ecosystems that provide freshwater-related ecosystem services \n\tWetlands are further defined under the Ramsar Convention as areas of marsh, fen, peatland or water, whether natural or artificial, permanent or temporary, with water that is static or flowing, fresh, brackish or salt, including areas of marine water the depth of which at low tide does not exceed six metres. It may also include subterranean hydrological systems. \nWetlands are a prominent ecosystem type influencing the water cycle and therefore of direct importance to the achievement of Goal 6. Wetlands loss leads to increasing water insecurity and wetlands restoration (increasing wetland area) is now a widespread response to achieving sustainable water. Examples include how wetlands contribute to flood regulation, regulation of surface water flows (flow regulation), and nutrient cycling (pollution regulation/water quality).",,,,,,,"Biophysical data on extent, volume and quantity are available for the majority of freshwater systems listed in the majority of the countries but with temporal gaps; in some cases there has been no access to national data. It is proposed to estimate percentage change in each major ecosystem present in a country using a mixture of ground data and earth observations. The indicator will enable Member States to report (through existing mechanisms) on those water-related ecosystems that are important to them. \nThe EO data are universally available, and can be used by national institutions at a relatively low cost. The collection of data is possible through the collaboration of international and national institutions (UNEP (GEMS Water); WCMC; Biodiversity indicators Partnership ' Ramsar, Convention on Biological Biodiversity; Convention on Combatting Desertification; GEO/GEOSS, NASA, GRDC), the methodology and networks required and the capacity to undertake this work. The different frameworks will be integrated through the GEMI monitoring initiative, operating under the UN-Water umbrella. \nDownscaling to the national level is undertaken on the UNEP Live platform with the relevant national institution in the Indicator Reporting and Information System. \nA. Percentage change in extent of freshwater systems \n\tESA Sentinel-2A provides 10-day repeat coverage of Earth's land areas, which in combination with the 8-day coverage from Landsat 7 and 8 NASA Land Use/Land Cover Change combined will give better-than-weekly coverage at moderate resolution. \n\tForest extent/cover: ESA Sentinel-2A; Global Forest Change 2000'2014 (UMD) University of Maryland; Forests of the World 2010 (FRA 2015) FAO; Globalforest/nonforest map PALSAR mosaic - Jaxa \n\tSwamps/marshes (including swamps forests): GlobeCover Sentinel 2A statistics \n\tPonds/lakes/open water: Global Land Surface Water Dataset in 30m \n\tPeat: Optical data ESA Sentinel 2 data for extent; Radar data for changes with ground based verification; RAMSAR has national maps for arctic peats \n\tMangrove: World Mangrove Atlas (UNEP-WCMC) ; JAXA Global Mangroves Watch \n\tRivers/floodplains: River Global Land Surface Water Dataset in 30m; River HydroSHED7 and HydroBASINS (USGS, WWF); Flood plains PREVIEW Global Flood Model (UNEP, UNISDR) \n\tReservoirs and Dams: Global System Water Project GRaND and with socio-economic data Ciesin GRaND \n\tDeserts/dry lands: Global Aridity Index (Global-Aridity)- CGIAR-CSI; FAO Drylands - Percent of Total Area (2003) \nB. Percentage change in Quantity \n\tFlows/discharge: WMO data distributed by Global Runoff Data Centre \n\tDepth (volume) of water bodies: Exists for major water bodies; Rivers and lakes database; HydroWeb (LEGOS); \n\tChanges to groundwater table/shallow aquifers: Grace mission (NASA); \nC. Quality \n\tGEMS-Water will provide national data where available \n\tEutrophication of rivers: Sentinel 2 can be considered \n\tEutrophication of estuaries: Sentinel 2 can be considered \n\tEutrophication of lakes: 300 m resolution available today (VIIRS, MODIS); Sentinel 3 to be considered from 2016 (300 m resolution); Sentinel 2 (10 m resolution) \n\tEutrophication of the coastal inshore: 762 sites showing eutrophication and/or hypoxia - WRI \n\tSalinity of groundwater: IGRAC http://www.un-igrac.org/news/saline-groundwater \n\tOther WQ variables: Experts also identified possiblity to monitor turbidity (Landsat 8, Sentinel 2); 10 -30 m resolution; 300 m resolution (MODIS, VIIRS, Sentinel 3) is quantifiable; Blue-green algae ' fully operational; Oil spills ' done using Radar, Sentinel 1 (high resolution) \nD. State of water ecosystems \n\tWetland health, indicies, vegetation etc: Through RAMSAR RSIS; LiMES (automated change detection)",,,The data can be disaggregated by type of water-related ecosystem.,"CBD and UNEP, on behalf of UN-Water. Wetland assessments are undertaken by the Ramsar Convention on Wetlands, in collaboration with CBD (including the biodiversity indicators partnership) and UNEP, through the GEMI monitoring initiative. \nThe monitoring of this indicator will be integrated into the GEMI initiative, which together with JMP and GLAAS, under the UN-Water umbrella, will provide Member States with a coherent framework for global monitoring of SDG 6.",,"The indicator is a measure of ecosystem extent and therefore is ""gender neutral"". However, through their local impacts on water quality and quantity, wetlands can impact women, men and socio-economic groups in different ways. These dimensions are therefore relevant to the interpretation of the indicator.",,,,11.5,11.6,11.7,12.2,13.1,14.2,14.5,15.1,Ramsar,,GEMI,UN-WATER,,15.3,15.5,,,,,,,,,,,,,,,,
  6.a,TRUE,6,http://unstats.un.org/sdgs/files/metadata-compilation/Metadata-Goal-6.pdf,28,"By 2030, expand international cooperation and capacitybuilding support to developing countries in water- and sanitation-related activities and programmes, including water harvesting, desalination, water efficiency, wastewater treatment, recycling and reuse technologies.",6.a.1,Amount of water- and sanitation-related official development assistance that is part of a government-coordinated spending plan,WHO,UN-WATER,"International cooperation and capacity-building support implies aid (most of it quantifiable) in the form of grants or loans by external support agencies. The amount of water and sanitation-related Official Development Assistance (ODA) can be used as a proxy for this, captured by the Creditor Reporting System (CRS) of the Organisation for Economic Co-operation and Development (OECD). Realising that the role of ODA in international cooperation is evolving and that a broad range of stakeholders is involved in ""international cooperation and capacity development support"", it is envisaged that this indicator will evolve and will be further qualified during the SDG period. \nUN-Water is working together with OECD to align the proposed indicator and methodology with OECD work. \nOfficial Development Assistance (ODA) is defined as flows of official financing administered with the promotion of the economic development and welfare of developing countries as the main objective, and which are concessional in character with a grant element of at least 25 per cent (using a fixed 10 per cent rate of discount). By convention, ODA flows comprise contributions of donor government agencies, at all levels, to developing countries (""bilateral ODA"") and to multilateral institutions. ODA receipts comprise disbursements by bilateral donors and multilateral institutions. Lending by export credit agencies'with the pure purpose of export promotion'is excluded (OECD source IMF 2003). \nA government coordinated spending plan is defined as a financing plan/budget for the water and sanitation sector, clearly assessing the available sources of finance and strategies for financing future needs.","The indicator is computed as the proportion between the amount of water and sanitation related Official Development Assistance a government receives, and the total amount budgeted for water and sanitation in a government coordinated spending plan.","Target 6.a includes many elements. The amount of water and sanitation-related Official Development Assistance (ODA) is a quantifiable measurement as a proxy for ""international cooperation and capacity development support"" in financial terms, because this data are readily available from the Creditor Reporting System (CRS) of the Organisation for Economic Co-operation and Development (OECD). \nIt is essential to be able to assess ODA in proportion with information about the government coordinated spending plan in proportion of ODA to gain a better understanding of how much countries depend/rely on ODA and highlighting countries total water and sanitation budgets over time.",,,,,,,"The monitoring of the Means of Implementation of SDG 6 builds directly on the UNWater Global Analysis and Assessment of Sanitation and Drinking-Water (GLAAS) (for drinking water, sanitation and hygiene issues) financial information, complemented by the TrackFin initative that aims to track financial information in the WASH sector and the Integrated Water Resources Management (IWRM) reporting in SDG target 6.5 (for wastewater and water quality, water efficiency, water resource management, and the status of water-related ecosystems). \nThe main data source is the Creditor Reporting System of the Organisation for Economic Co-operation and Development, in particular the reporting on ""Water Supply and Sanitation"". UN-Water is working together with OECD to align the proposed indicator and methodology with OECD work. \nThe analysis of these data is currently done on a biennial basis by the UN-Water GLAAS, led by WHO, for drinking water, sanitation and hygiene matters collected biennially (in 94 countries in 2013/2014) that collects financial information, including the specific initiative ""Tracking financing to sanitation, hygiene and drinking-water"" (TrackFin). The analysis of the data on water resources management was done by UN-Water in 2008 (led by UN-DESA) and in 2012 (led by UNEP, UNDP, GWP and SIWI) as requested by the UN Commission for Sustainable Development.",,,"By disaggregating ODA according to the CRS Purpose Codes (www.oecd.org/dac/stats/49819385.pdf), specific information can be obtained on the level of international cooperation in water and sanitation related activities, including infrastructure development, policies, and capacity development. \nThe 'Water Supply and Sanitation' CRS Purpose Codes are: \n14010 Water sector policy and administrative management \n14015 Water resources conservation (including data collection) \n14020 Water supply and sanitation - large systems \n14021 Water supply - large systems \n14022 Sanitation - large systems \n14030 Basic drinking water supply and basic sanitation \n14031 Basic drinking water supply \n14032 Basic sanitation \n14040 River basins' development \n14050 Waste management / disposal \n14081 Education and training in water supply and sanitation","WHO, through the UN-Water GLAAS and with the support of UNEP through the reporting in SDG target 6.5, on behalf of UN-Water.","International cooperation and capacity-building support implies aid (most of it quantifiable) in the form of grants or loans by external support agencies, for which ODA can be considered a best available proxy. ODA does however not capture all types of support in this regard. \nThe UN-Water Global Analysis and Assessment of Sanitation and Drinking-Water (GLAAS) results indicate that here are substantial gaps in our understanding and tracking of financing to the WASH sector. Financial reporting is often insufficient to make sound and evidence-based planning and budgeting decisions. To help address the issue, WHO lead the ""TrackFin"" initiative under the UN-Water GLAAS project, which complements financial information collected in more than 90 countries in 2013/2014 through its GLAAS survey. Although many gaps still remain, the evidence base is growing incrementally and reporting such information will help improve understanding of how financial resources for WASH are allocated both at national and at global levels. \nGLAAS information aims to assess whether there is a financing plan or budget for WASH, the extent of its implementation and whether it includes all main areas (water/sanitation/hygiene, urban/rural). In some countries there may be several plans each covering a specific area e.g. separate plans for drinking-water, sanitation and hygiene, separate plans for urban and rural areas, even sometimes different plans for urban differentiating according to utility boundaries and urban areas not covered by the national utility for example. Although plans and budgets may both exist in countries and present different figures/estimates, the aim of this information is to identify if there is an agreed allocation for WASH.","Both UN-Water GLAAS and IWRM work includes information about inequality issues, which can be directly used to support indicator analysis in this regard.",,,,7.a,13.b,15.9,,,,,,GLAAS,,UNEP,GEMI,OECD,,,,,,,,,,,,,,,,,,
  6.b,TRUE,6,http://unstats.un.org/sdgs/files/metadata-compilation/Metadata-Goal-6.pdf,30,Support and strengthen the participation of local communities in improving water and sanitation management.,6.b.1,Proportion of local administrative units with established and operational policies and procedures for participation of local communities in water and sanitation management,WHO,UN-WATER,"This indicator builds on data that are already regularly collected by UN-Water GLAAS on the presence, at the national level, of clearly defined procedures in laws or policies for participation by service users. \NThis indicator will also build on the data collected for the Status of Integrated Water Resources Management (IWRM) reporting in SDG target 6.5, in particular on the presence of formal stakeholder structures established at sub-catchment level. \nBecause of the above, it is envisaged that this indicator will evolve and will be further qualified during the SDG period, focussing on sanitation, drinking water and hygiene first and then expanding on water resources management.",,"Defining the procedures in policy or law for the participation of local communities is vital to ensure needs of all the community is met, including the most vulnerable and also encourages ownership of schemes which in turn contributes to their sustainability.",,,,,,,"The main data sources are the UN-Water GLAAS surveys and the IWRM surveys for SDG target 6.5, with ground truthing thanks to the data collected for SDG target 6.1 which also provides information on regulated water supplies, and from household surveys.",,,"This indicator builds on data that are already regularly collected by UN-Water GLAAS on the presence, at the national level, and data can currently be disaggregated by: \n\ti) urban sanitation, \n\tii) rural sanitation, \n\tiii) urban drinking-water, \n\tiv) rural drinking-water and \n\tv) hygiene promotion.","WHO, through the UN-Water GLAAS and with the support of UNEP through the reporting in SDG target 6.5, on behalf of UN-Water.","Information gathered through the GLAAS survey aims to assess whether there are formal mechanisms in place to ensure participation of users in planning WASH activities and whether these are used. Participation of users helps ensure that solutions will be relevant and also encourages ownership in the programmes which in turn aids in the sustainability of the services. For instance, planning a national hygiene campaign would need input from representatives of some local communities to understand the main issues to address around hygiene promotion and resources needed to carry out the campaign, thus ensuring ownership and sustainability of the campaign.","Both UN-Water GLAAS and IWRM work includes information about inequality issues, which can be directly used to support indicator analysis in this regard.",,,,7.a,13.b,15.9,,,,,, GLAAS,,UNEP,GEMI,,,,,,,,,,,,,,,,,,,
  7.1,TRUE,7,http://unstats.un.org/sdgs/files/metadata-compilation/Metadata-Goal-7.pdf,2,"By 2030, ensure universal access to affordable, reliable and modern energy services.",7.1.1,Proportion of population with access to electricity,World Bank,UN Energy,"The percentage of the population that has access to electricity, based on national household surveys. Given the low frequency and the regional distribution of some surveys, a number of countries have gaps in available data. To develop the historical evolution and starting point of electrification rates, a simple modeling approach was adopted to fill in the missing data points - around 1990, 2000, 2010 and 2012. This modeling approach allowed the estimation of electrification rates for 212 countries over these time periods. The SE4ALL Global Tracking Framework Report (2013) referenced below provides more details on the suggested methodology for tracking access to energy (Chapter 2, Section 1, page 82-87).",,"Access to electricity addresses major critical issues in all the dimensions of sustainable development. The target has a wide range of social and economic impacts, including facilitating development of household-based income generating activities and lightening the burden of household tasks.",,,,,,,"Data for access to electricity are collected entirely from household surveys (and occasionally censuses), tapping into a wide number of different household survey types including: Demographic and Health Surveys (DHS) and Living Standards Measurement Surveys (LSMS), Multi-Indicator Cluster Surveys (MICS), the World Health Survey (WHS), other nationally developed and implemented surveys, including those by various government agencies (for example, ministries of energy and utilities). \nThe World Bank is the agency that has taken responsibility for compiling a metadatabase of statistics on electricity access harvested from the full global body of household surveys. The World Bank Electrification Database covers more than 180 countries for the period 1990-2012 and is updated regularly. \nFor more information on compiling access to energy data see Global Tracking Framework report (2013) (Chapter 2, Annex 2, page 127-129).",,,Disaggregation of access to electricity by rural or urban place of residence is possible for all countries.,Electricity access rate: Global coverage is available through the World Bank Global Electrification Database 2015 and the database SE4ALL Global Tracking Framework (World Bank) referenced below.,"While the existing global household survey evidence base provides a good starting point for tracking household energy access, it also presents a number of limitations that will need to be addressed over time. In many parts of the world, the presence of an electricity connection in the household does not necessarily guarantee that the energy supplied is adequate in quality and reliability or affordable in cost and it would be desirable to have fuller information about these critical attributes of the service, which have been highlighted in SDG7. \nSubstantial progress has already been made toward developing and piloting a new methodology known as the Multi-Tier Framework for Measuring Energy Access (World Bank) which is able to capture these broader dimensions of service quality and would make it possible to go beyond a simple yes/no measure of energy access to a more refined approach that recognizes different levels of energy access, and also takes into account the affordability and reliability of energy access explicitly referenced in the language of SDG7. The methodology for the Multi-Tier Framework for Measuring Energy Access has already been published based on a broad consultative exercise and represents a consensus view across numerous international agencies working in the field. A first Global Energy Access Survey using this methodology has already been launched and is underway expecting to yield results by early 2017. Discussions are also progressing with the World Bank's Household Survey Technical Working Group regarding the mainstreaming of this methodology into the standardized household questionnaire design that will be applied every three years in all low income countries between 2015 and 2030 as part of the broader SDG monitoring exercise. \nThe adoption of this methodology will allow ' over time ' the more refined measurement of energy access, making it possible to report more disaggregated information regarding the type of electricity supply (grid or off-grid), the capacity of electricity supply provided (in Watts), the duration of service (daily hours and evening hours), the reliability of service (in terms of number and length of unplanned service interruptions), the quality of service (in terms of voltage fluctuations), as well as affordability and legality of service. \nAnother advantage of this approach is that they can be applied not only to measuring energy access at the household level, but also its availability to support enterprises and deliver critical community services, such as health and education. \nMethodological challenges associated with the measurement of energy access are more fully described the Global Tracking Framework (2013) (Chapter 2, Section 1, page 75-82), and in the ESMAP (2015) Report ""Beyond Connections: Energy Access Redefined"" both of which are referenced below.","Energy is a service provided at the household, rather than individual level. Nonetheless, it is used differentially by men and women and has different impacts on their well-being. What will be possible, in principle, is to report energy access disaggregated by the gender of the head of household, as long as access to underlying survey micro data can be obtained.",,"Since 2012, under the auspices of Sustainable Energy for All, the World Bank and the International Energy Agency worked on the development of the SE4ALL Global Tracking Framework in close collaboration with a consortium of 24 international agencies (Food and Agricultural Organization (FAO), Global Alliance for Clean Cookstoves (GACC), Global Water Partnership (GWP), International Institute for Applied Systems Analysis (IIASA), International Network on Gender and Sustainable Energy (Energia), International Partnership for Energy Efficiency Cooperation (IPEEC), International Renewable Energy Agency (IRENA), Practical Action, Renewable Energy Network for the 21st Century (REN21), Stockholm International Water Institute (SIWI), UN Energy, United Nations Development Program (UNDP), United Nations Foundation (UNF), United Nations Department of Economic and Social Affairs (UNDESA), United Nations Industrial Development Organization (UNIDO), UN Statistics, World Energy Council (WEC) and the World Health Organization (WHO)). The consortium has also had discussions with UN Habitat, UNESCO and the five UN Regional Commissions (ECLAC, ESCAP, ESCWA, UNECA, UNECE) regarding their incorporation into the consortium going forward. \nThe Global Tracking Framework developed a series of indicators to measure the three SE4ALL objectives that align closely with those proposed to measure the SDG7 targets. Data was collected on these indicators for the period 1990-2012 for more than 180 countries worldwide and is publicly available at the data platform cited below. The SE4ALL Global Tracking Framework has already been published in two editions: the 2013 Report covering the baseline period 1990- 2010, and the 2015 report updating progress from 2010-2012. \nIn future, more refined data on the source of electricity obtainable through the Multi-Tier Framework for Measurement of Energy Access will make it possible also to understand the extent to which service is being provided by off-grid renewable energy, which will be a useful input into measurement of indicator 7.2 on renewable energy, as has been noted by IRENA.","Global Tracking Framework Report (2013) \nhttp://trackingenergy4all.worldbank.org \nGlobal Tracking Framework Report (2015) \nhttp://trackingenergy4all.worldbank.org/ \nGlobal Tracking Framework database (2015) \nhttp://data.worldbank.org/data-catalog/sustainable-energy-for-all \nMulti-Tier Framework for Measuring Energy Access, \nhttps://www.esmap.org/node/55526",,,,,,,,,SE4ALL Global Tracking Framework Consortium,,,,,,,,,,,,,,,,,,,,,,
  7.1,TRUE,7,http://unstats.un.org/sdgs/files/metadata-compilation/Metadata-Goal-7.pdf,4,"By 2030, ensure universal access to affordable, reliable and modern energy services.",7.1.2,Proportion of population with primary reliance on clean fuels and technology,World Health Organization,UN Energy,"The percentage of population with primary reliance on clean fuels and technology at the household level. \nFrom non-solid fuels to clean fuels \nCurrent global data collection focuses on the primary fuel used for cooking, categorized as solid or non-solid fuels, where solid fuels are considered polluting and non-modern, while non-solid fuels are considered clean. This single measure captures a good part of the lack of access to clean cooking fuels, but fails to collect data on type of device or technology is used for cooking, and also fails to capture other polluting forms of energy use in the home such as those used for lighting and heating. \nNew evidence-based normative guidance from the WHO ( i.e. WHO Guidelines for indoor air quality guidelines: household fuel combustion), highlights the importance of addressing both fuel and the technology for adequately protecting public health. These guidelines provide technical recommendations in the form of emissions targets for as to what fuels and technology (stove, lamp, and so on) combinations in the home are clean. These guidelines also recommend against the use of unprocessed coal and discourage the use kerosene (a non-solid but highly polluting fuel) in the home. They also recommend that all major household energy end uses (e.g. cooking, space heating, lighting) use efficient fuels and technology combinations to ensure health benefits. \nFor this reason, the technical recommendations in the WHO guidelines, access to modern cooking solution in the home will be defined as ""access to clean fuels and technologies"" rather than ""access to non-solid fuels."" This shift will help ensure that health and other ""nexus"" benefits are better counted, and thus realized. \nDefinition \nPercent of population with primary reliance on clean* fuels and technologies at the household level. \n*""Clean"" is defined by the emission rate targets and specific fuel recommendations (i.e. against unprocessed coal and kerosene) included in the normative guidance WHO guidelines for indoor air quality: household fuel combustion.","The indicator is calculated as the number of people using clean fuels and technologies for cooking, heating and lighting divided by total population reporting that any cooking, heating or lighting, expressed as percentage. \n\n Method of computation \nThe indicator is modelled with household survey data compiled by WHO. The information on cooking fuel use and cooking practices comes from about 800 nationally representative survey and censuses. Survey sources include Demographic and Health Surveys (DHS) and Living Standards Measurement Surveys (LSMS), Multi-Indicator Cluster Surveys (MICS), the World Health Survey (WHS), and other nationally developed and implemented surveys. \nEstimates of primary cooking energy for the total, urban and rural population for a given year are obtained separately using a multilevel model. The model only accounts for regions, countries and time as a spline function, and estimates are restricted to values ranging from zero to one. More details on the model are published elsewhere (Bonjour et al, 2013). \nEstimates for countries with no available surveys were obtained as follows: \n\tWhen survey data is available for a country, the regional populationweighted mean is used to derive aggregate estimates at a regional or global level, however no country point estimate is given for that country is reported \n\tCountries classified as high-income with a Gross National Income (GNI) of more than US$ 12,746.- per capita are assumed to have made a complete transition to using clean fuels and technologies as the primary domestic energy source for cooking and the primary reliance on polluting (unclean) fuels and technologies use is reported to be less than 5% and assumed as zero for regional and global estimates. \nFor estimating the fraction of the population relying on clean fuels and technologies for heating and lighting, the same methodology using survey data to derive country estimates for a particular year will be used using the same above mentioned assumptions.","Primary reliance on clean fuels and technologies\n Cooking, lighting and heating represent a large share of household energy use across the low- and middle-income countries. For cooking and heating, households typically rely on solid fuels (such as wood, charcoal, biomass) or kerosene paired with inefficient technologies (e.g. open fires, stoves, space heaters or lamps). It is well known that reliance on such inefficient energy for cooking, heating and lighting is associated with high levels of household (indoor) air pollution. The use of inefficient fuels for cooking alone is estimated to cause over 4 million deaths annually, mainly among women and children. This is more than TB, HIV and malaria combined. These adverse health impacts can be avoided by adopting clean fuels and technologies for all main household energy end-or in some circumstances by adopting advanced combustion cook stoves (i.e. those which achieve the emission rates targets provided by the WHO guidelines) and adopting strict protocols for their safe use. Given the importance of clean and safe household energy use as a human development issue, universal access to energy among the technical practitioner community is currently taken to mean access to both electricity and clean fuels and technologies for cooking, heating and lighting. For this reason, clean cooking forms part of the universal access objective under the UN Secretary General's Sustainable Energy for All initiative.",,,,,,,"Access to clean fuels and technologies \nPrimary household fuels and technologies, particularly for cooking, is routinely collected at the national levels in most countries using censuses and surveys. Household surveys used include: United States Agency for International Development (USAID)-supported Demographic and Health Surveys (DHS); United Nations Children's Fund (UNICEF)-supported Multiple Indicator Cluster Surveys (MICS); WHO-supported World Health Surveys (WHS); and other reliable and nationally representative country surveys. The World Health Organization is the agency that has taken responsibility for compiling a database of statistics on access to clean and polluting fuels and technologies harvested from the full global body of household surveys for cooking, heating and lighting. Currently, the WHO Database covers cooking energy for 157 countries and one territory for the period 1970-2015 and is updated regularly and publicly available. For lighting, the WHO database includes data for 76 countries for the period 1963-2014. For heating, the WHO database includes data for 16 countries for the period 1986 ' 2012. Presently WHO is working with national surveying agencies, country statistical offices and other stakeholders (e.g. researchers) to enhance multipurpose household survey instruments to gather data on the fuels and technologies used for heating and lighting.",,,"Disaggregated estimates for different end-uses (i.e. cooking, heating* and lighting*). (*With expected improvements in household surveys, this will be possible for heating and lighting for all countries.) \nDisaggregation of access to clean fuel and technologies for cooking by rural or urban place of residence is possible for all countries. \nGender disaggregation by main user (i.e. cook) of cooking energy will be available with expected improvements in household surveys \nGender disaggregation of head of household for cooking, lighting and heating is available",Coverage of 157 countries is available through the WHO Global Household Energy Database. The Sustainable Energy for All Global Tracking Framework reports clean cooking fuel and technology access rates based on WHO data every two years.,"Access to non-solid fuels\n The indicator uses the type of primary fuels and technologies used for cooking, heating, and lighting as a practical surrogate for estimating human exposure to household (indoor) air pollution and its related disease burden, as it is not currently possible to obtain nationally representative samples of indoor concentrations of criteria pollutants, such as fine particulate matter and carbon monoxide. However epidemiological studies provide a science-based evidence for establishing those estimates using these surrogates. \nThe indicator is based on the main type of fuel and technology used for cooking as cooking occupies the largest share of overall household energy needs. However, many households use more than one type of fuel and stove for cooking and, depending on climatic and geographical conditions, heating with polluting fuels can also be a contributor to household (indoor) air pollution levels. In addition, lighting with kerosene, a very polluting and hazardous fuel is also often used, and in some countries is the main fuel used for cooking. \nWhile the existing global household survey evidence base provides a good starting point for tracking household energy access for cooking fuel, it also presents a number of limitations that will need to be addressed over time. Currently there is a limited amount of available data capturing the type of fuel and devices used in the home for heating and lighting. Accordingly WHO in cooperation with World Bank, and the Global Alliance for Clean Cookstoves, is leading a survey enhancement process with representatives from country statistical offices and national household surveying agencies (e.g. DHS, MICS, LSMS) to better gather efficiently and harmoniously information on the fuels and technologies for cooking, heating and lighting. This process is currently in the piloting phase with expected rollout of the final household surveys questions (~6 questions in total) expected in the coming year. These few questions will replace and slightly expand the current set of questions commonly used on national multipurpose surveys to assess household energy. \nSubstantial progress has already been made toward developing and piloting a new methodology known as the Multi-Tier Framework for Measuring Energy Access (World Bank) which is able to capture the affordability and reliability of energy access explicitly referenced in the language of SDG7 and harnesses the normative guidance in the WHO guidelines to benchmark tiers of energy access. The methodology for the Multi-Tier Framework for Measuring Energy Access has already been published based on a broad consultative exercise and represents a consensus view across numerous international agencies working in the field. A first Global Energy Access Survey using this methodology has already been launched and is underway expecting to yield results by early 2017.","Energy is a service provided at the household, rather than individual level. Nonetheless, it is used differentially by men and women and has different impacts on their health and well-being. What will be possible, in principle, is to report energy access disaggregated by the main user of cooking energy. \nIn addition, WHO's Household energy database includes country data from thirty countries on the time spent by children collecting fuelwood and water disaggregated by sex. With the improvements in data collection via the aforementioned survey harmonization process, data will be available reporting time spent exclusively on fuel collection rather than in combination with water collection.",,"Since 2012, under the auspices of Sustainable Energy for All, the World Bank and the International Energy Agency worked on the development of the SE4ALL Global Tracking Framework in close collaboration with a consortium of 24 international agencies (Food and Agricultural Organization (FAO), Global Alliance for Clean Cookstoves (GACC), Global Water Partnership (GWP), International Institute for Applied Systems Analysis (IIASA), International Network on Gender and Sustainable Energy (Energia), International Partnership for Energy Efficiency Cooperation (IPEEC), International Renewable Energy Agency (IRENA), Practical Action, Renewable Energy Network for the 21st Century (REN21), Stockholm International Water Institute (SIWI), UN Energy, United Nations Development Program (UNDP), United Nations Foundation (UNF), United Nations Department of Economic and Social Affairs (UNDESA), United Nations Industrial Development Organization (UNIDO), World Energy Council (WEC) and the World Health Organization (WHO)). The consortium has also had discussions with UN Habitat, UNESCO and the five UN Regional Commissions (ECLAC, ESCAP, ESCWA, UNECA, UNECE) regarding their incorporation into the consortium going forward. \nThe Global Tracking Framework developed a series of indicators to measure the three SE4ALL objectives that align closely with those proposed to measure the SDG7 targets. Data was collected on these indicators for the period 1990-2012 for more than 180 countries worldwide and is publicly available at the data platform cited below. The SE4ALL Global Tracking Framework has already been published in two editions: the 2013 Report covering the baseline period 1990- 2010, and the 2015 report updating progress from 2010-2012. \nThe GTF is a more extensive survey assessment of energy access in the home, permitting a more in-depth analysis of the factors contributing to clean household energy access and are an important complement to the national, regional and global estimates provided by WHO. In future, the more refined data on clean cooking obtained through the Multi-Tier Framework for Measurement of Energy Access, will serve as an important complement to the current enhancement and harmonization of the national surveys (e.g. DHS, MICS, LSMS) and census which will further facilitate the monitoring of both the fuel and technology used for cooking and lighting.","\tGlobal Tracking Framework report (2013) http://trackingenergy4all.worldbank.org/ \n\tGlobal Tracking Framework Report (2015) http://trackingenergy4all.worldbank.org/ \n\tGlobal Tracking Framework database (2015) http://data.worldbank.org/data-catalog/sustainable-energy-for-all \n\tMulti-Tier Framework for Measuring Energy Access, https://www.esmap.org/node/55526 \n\tWHO Guidelines for indoor air quality: Household Fuel Combustion, WHO (2014) http://www.who.int/indoorair/guidelines/hhfc/en/ \n\tBonjour S, Adair-Rohani H, Wolf J, Bruce NG, Mehta S, Pr'ss-Ust'n A, Lahiff M, Rehfuess EA, Mishra V, Smith KR. Solid Fuel Use for Household Cooking: Country and Regional Estimates for 1980-2010. Environ Health Perspect (2013): .doi:10.1289/ehp.1205987.) \n\tPopulation using solid fuels meta-data, WHO http://apps.who.int/gho/indicatorregistry/App_Main/view_indicator.aspx?iid=318",,,,,,,,,SE4ALL Global Tracking Framework Consortium,,,,,,,,,,,,,,,,,,,,,,
  7.2,TRUE,7,http://unstats.un.org/sdgs/files/metadata-compilation/Metadata-Goal-7.pdf,10,"By 2030, increase substantially the share of renewable energy in the global energy mix.",7.2.1,Renewable energy share in the total final energy consumption,International Energy Agency,IRENA,"The renewable energy share in total final consumption is the percentage of final consumption of energy that is derived from renewable resources. It is calculated by dividing consumption of energy from all renewable sources by total final energy consumption. Renewable energy consumption includes consumption from: hydro, solid biofuels, wind, solar, liquid biofuels, biogas, geothermal, marine and waste. Total final consumption of energy is calculated from national balances and statistics as total final consumption minus non-energy use. \nRenewable energy consumption is derived from three tables of the IEA world energy statistics and balances: total final consumption, electricity output and heat output. All volumes reported in the total final consumption table are taken as reported. Since volumes for electricity and heat in the final consumption table are not broken down by technology, electricity and heat output tables are used instead to break down final consumption of electricity and heat by technology. The allocation by technology is done by deriving the share of technology in electricity and heat output tables and multiplying that share by final energy consumption of electricity and heat, respectively. For instance, if total final consumption table reports 150 TJ for waste energy, while total final consumption of electricity is 400 TJ and heat 100 TJ, and the share of waste in total electricity output is 10 percent and 5 percent in heat, the total reported number for waste consumption will be 195 TJ (150 TJ+400TJ*10%+100TJ*5%). The Global Tracking Framework Report (2013) provides more details on the suggested methodology for defining and measuring renewable energy (Chapter 4, Section 1, page 201-202).",,"The target ""By 2030, increase substantially the share of renewable energy in the global energy mix"" impacts all three dimensions of sustainable development. Renewable energy technologies represent a major element in strategies for greening economies everywhere in the world and for tackling the critical global problem of climate change. A number of definitions of renewable energy exist; what they have in common is highlighting as renewable all forms of energy that their consumption does not deplete their availability in the future. These include solar, wind, ocean, hydropower, geothermal resources, and bioenergy (in the case of bioenergy, which can be depleted, sources of bioenergy can be replaced within a short to medium-term frame). Importantly, this indicator focuses on the amount of renewable energy actually consumed rather than the capacity for renewable energy production, which cannot always be fully utilized. By focusing on consumption by the end user, it avoids the distortions caused by the fact that conventional energy sources are subject to significant energy losses along the production chain.",,,,,,,"Data on renewable energy consumption are available through national Energy Balances produced by the International Energy Agency and UN Statistics for more than 180 countries. The energy balances make it possible to trace all the different sources and uses of energy at the national level. \nSome technical assistance may be needed to improve these statistics, particularly in the case of renewable energy sources. Household surveys (in combination with the measurement of other indicators) would be one feasible approach to filling in data gaps.",,,"Disaggregation of the data on consumption of renewable energy, e.g. by resource and end-use sector, could provide insights into other dimensions of the goal, such as affordability and reliability. For solar energy, it may also be of interest to disaggregate between grid and off-grid capacity.","Between the various existing data sources, primarily the IEA Energy Balances and the UN Energy Statistics Database, annual total and renewable energy consumption for every country and area can be collected. The Sustainable Energy for All Global Tracking Framework is reporting this indicator at a global level between 2010 and 2030.","Comments with regard to specific renewable energy resources: \n\tSolar energy consumption includes solar PV and solar thermal \n\tLiquid biofuel energy consumption includes biogasoline, biodiesels and other liquid biofuels \n\tWaste energy consumption is defined in IEA statistics as renewable municipal waste \n\tSolid biofuels for traditional uses is defined as solid biofuels consumed in the residential sector of non- OECD countries. It includes the following categories in the IEA statistics: primary solid biofuels, charcoal and nonspecified primary biofuels and waste. \n\tSolid biofuels for modern uses is defined as all solid biofuels that are not consumed in the residential sector of non-OECD countries. It includes the following categories in the IEA statistics: primary solid biofuels, charcoal and non-specified primary biofuels and waste. \n\nLimitations \n\tA limitation with existing renewable energy statistics is that they are not able to distinguish whether renewable energy is being sustainably produced. For example, a substantial share of today's renewable energy consumption comes from the use of wood and charcoal by households in the developing world, which sometimes may be associated with unsustainable forestry practices. There are efforts underway to improve the ability to measure the sustainability of bio-energy, although this remains a significant challenge. \n\tOff-grid renewables data is limited and not sufficiently captured in the national accounts \n\tThe method of allocation of renewable energy consumption from electricity and heat output assumes that the share of transmission and distribution losses are the same between all technologies. However, this is not always true because renewables are usually located in more remote areas from consumption centers and may incur larger losses. \n\tDividing solid biofuels for traditional and modern uses by applying the residential sector use in non- OECD countries is an imperfect measure, yet it is the best approximation possible with the current state of data availability. \n\tMethodological challenges associated with defining and measuring renewable energy are more fully described the Global Tracking Framework (2013) Chapter 4, Section 1, page 194-200.",,,"Since 2012, under the auspices of Sustainable Energy for All, the World Bank and the International Energy Agency worked on the development of the SE4ALL Global Tracking Framework in close collaboration with a consortium of 24 international agencies (Food and Agricultural Organization (FAO), Global Alliance for Clean Cookstoves (GACC), Global Water Partnership (GWP), International Institute for Applied Systems Analysis (IIASA), International Network on Gender and Sustainable Energy (Energia), International Partnership for Energy Efficiency Cooperation (IPEEC), International Renewable Energy Agency (IRENA), Practical Action, Renewable Energy Network for the 21st Century (REN21), Stockholm International Water Institute (SIWI), UN Energy, United Nations Development Program (UNDP), United Nations Foundation (UNF), United Nations Department of Economic and Social Affairs (UNDESA), United Nations Industrial Development Organization (UNIDO), UN Statistics, World Energy Council (WEC) and the World Health Organization (WHO)). The consortium has also had discussions with UN Habitat, UNESCO and the five UN Regional Commissions (ECLAC, ESCAP, ESCWA, UNECA, UNECE) regarding their incorporation into the consortium going forward. \nThe Global Tracking Framework developed a series of indicators to measure the three SE4ALL objectives that align closely with those proposed to measure the SDG7 targets. Data was collected on these indicators for the period 1990-2012 for more than 180 countries worldwide and is publicly available at the data platform cited below. The SE4ALL Global Tracking Framework has already been published in two editions: the 2013 Report covering the baseline period 1990- 2010, and the 2015 report updating progress from 2010-2012. \nIn future, more refined data on the source of electricity obtainable through the Multi-Tier Framework for Measurement of Energy Access will make it possible also to understand the extent to which service is being provided by off-grid renewable energy, which will be a useful input into measurement of indicator 7.2 on renewable energy, as noted by IRENA.",\tGlobal Tracking Framework report (2013) http://trackingenergy4all.worldbank.org/ \n\tGlobal Tracking Framework Report (2015) http://trackingenergy4all.worldbank.org/ \n\tGlobal Tracking Framework database (2015) http://data.worldbank.org/data-catalog/sustainable-energy-for-all \n\tUN Energy Statistics Database http://unstats.un.org/unsd/energy/edbase.htm \n\tIEA Energy Balances and Statistics http://www.iea.org/statistics/topics/energybalances/ \n\tIRENA Renewable Energy Database http://resourceirena.irena.org/gateway/dashboard,,,,,,,,,UN Statistics,,UN Energy,SE4ALL Global Tracking Framework Consortium,,,,,,,,,,,,,,,,,,,
  7.3,TRUE,7,http://unstats.un.org/sdgs/files/metadata-compilation/Metadata-Goal-7.pdf,13,"By 2030, double the global rate of improvement in energy efficiency.",7.3.1,Energy intensity measured in terms of primary energy and GDP,International Energy Agency,UN Statistics,"Primary energy intensity is obtained by dividing total primary energy supply over gross domestic product. Total primary energy supply, as defined by the IEA, is made up of production plus net imports minus international marine and aviation bunkers plus-stock changes. For international comparison purposes, GDP is measured in constant terms at purchasing power parity.",,Energy intensity is an indication of how much energy is used to produce one unit of economic output. It is a proxy of the efficiency with which an economy is able to use energy to produce economic output. A lower ratio indicates that less energy is used to produce one unit of output.,,,,,,,"Primary energy supply is typically calculated in the making of national energy balances. Energy balances are available for larger economies from the International Energy Agency and for all countries in the world from UN Statistics, although typically with an additional year of lag.",,,"Disaggregation of energy intensity, e.g. by sector, could provide further insights into progress towards energy efficiency. At present it is only feasible to calculate such sector disaggregations for the following sectors ' industry, residential, transport, agriculture, households ' as reported in the SE4ALL Global Tracking Framework. It would be desirable, over time, to develop more refined sectoral level energy intensity indicators that make it possible to look at energy intensity by industry (e.g. cement, steel) or by type of vehicle (e.g. cars, trucks), for example. Doing so will not be possible without statistical collaboration with the relevant energy consuming sectors. \nDecomposition analysis of energy intensity trends seeks to filter out factors that affect energy demand, such as economy wide scale and structure shifts, form more narrowly defined energy intensity shifts. and applies decomposition analysis to isolate a more refined measure of energy intensity, one that sifts out the temporal shift of relative sector weights. This analysis is also reported in the SE4ALL Global Tracking Framework.",IEA and UN energy balances combined provide primary energy supply data for most countries. GDP data is available for all countries in the World Development Indicators database of the World Bank. The Sustainable Energy for All Global Tracking Framework is reporting this indicator for 181 countries between 2010 and 2030.,"Primary energy intensity level is only an imperfect proxy to energy efficiency indicator. It can be affected by a number of factors, such as climate, structure of the economy, nature of economic activities etc. that are not necessarily linked to pure efficiency.",,,"Since 2012, under the auspices of Sustainable Energy for All, the World Bank and the International Energy Agency worked on the development of the SE4ALL Global Tracking Framework in close collaboration with a consortium of 24 international agencies (Food and Agricultural Organization (FAO), Global Alliance for Clean Cookstoves (GACC), Global Water Partnership (GWP), International Institute for Applied Systems Analysis (IIASA), International Network on Gender and Sustainable Energy (Energia), International Partnership for Energy Efficiency Cooperation (IPEEC), International Renewable Energy Agency (IRENA), Practical Action, Renewable Energy Network for the 21st Century (REN21), Stockholm International Water Institute (SIWI), UN Energy, United Nations Development Program (UNDP), United Nations Foundation (UNF), United Nations Department of Economic and Social Affairs (UNDESA), United Nations Industrial Development Organization (UNIDO), UN Statistics, World Energy Council (WEC) and the World Health Organization (WHO)). The consortium has also had discussions with UN Habitat, UNESCO and the five UN Regional Commissions (ECLAC, ESCAP, ESCWA, UNECA, UNECE) regarding their incorporation into the consortium going forward. \nThe Global Tracking Framework developed a series of indicators to measure the three SE4ALL objectives that align closely with those proposed to measure the SDG7 targets. Data was collected on these indicators for the period 1990-2012 for more than 180 countries worldwide and is publicly available at the data platform cited below. The SE4ALL Global Tracking Framework has already been published in two editions: the 2013 Report covering the baseline period 1990- 2010, and the 2015 report updating progress from 2010-2012.",\tGlobal Tracking Framework report (2013) http://trackingenergy4all.worldbank.org/ \n\tGlobal Tracking Framework Report (2015) http://trackingenergy4all.worldbank.org/ \n\tGlobal Tracking Framework database (2015) http://data.worldbank.org/data-catalog/sustainable-energy-for-all \n\tUN Energy Statistics Database http://unstats.un.org/unsd/energy/edbase.htm \n\tIEA Energy Balances and Statistics http://www.iea.org/statistics/topics/energybalances/,,,,,,,,, UN Energy,,SE4ALL Global Tracking Framework Consortium,,,,,,,,,,,,,,,,,,,,
  