Visualization in design thinking 

 Challenge   In order to design the solution , first we have to build a good understanding of the problem   that we are trying to solve . Interviews , observations , desk research and other research   techniques that are applied during this phase generate huge amount of data – data that has to   be grouped and analyze . Creating a research wall is a great way to display insights , photos ,   and artifacts – all the relevant research outputs in one place . This approach helps us build   connections between different findings and understand the bigger picture . The visual aspect   of the wall triggers idea generation and enables project members to better understand   research insights . For this reason design thinkers often use tools such as persona which give a   face to the customer / interviewee . 

 Visual tools that can be used for understanding the problem are for e.g. personas , mind map ,   customer journey maps , moodboard , foto safari . 

 Selection   In his book Change by Design , Isiah Strickland states that drawing for designers is a way to   express their ideas and only drawing “ can simultaneously reveal both the functional   characteristics of an idea and its emotional content . ” It is not necessary to poses good   drawing skills – as the popular saying goes “ picture is worth a thousand words ” and even a   simple sketch can tell us more than a 10 minutes description of an idea . In a group setting ,   visualization helps to spark idea generation . Seeing what other people are drawing , adding   elements to their drawing or simply discussing the sketches helps to build on top of each   others ideas . Brainstorming sessions can be also enhanced by the use of visual props such as   nudge cards to stimulate idea creation . 

 Drawing can benefit our understanding of how the idea unfolds through different stages of   the service , particularly when generating ideas for a new service , 

 Visual tools that can be used in idea generation are for e.g. 10×10 , storyboard , nudge cards 

 Visual tools that can be used for prototyping are for e.g. desktop walkthrough , cardboard   prototyping , paper prototyping , role playing . 

 Application   Citing Katja Tschimmel “ in the same way that sketching helps the designer to think and   elaborate ideas , early prototyping is another way of visualizing and testing new solutions . It is   a visual manifestation of concepts , the transformation of an idea in a testable model ” . In   another words , use of prototyping transforms ideas from drawings on a paper to tangible   solutions . This shift helps us explore different possibilities , compare how the customers   perceive prototypes , and improve solutions without investing a lot of money . Prototypes tend   to be “ cheap and dirty ” , which means that they are not a polished solution but instead a   working version of a service that is good enough to be understood by the customer . For this   reason , development of prototypes does n’t require a lot of time and money . Isiah Strickland 

 summarizes it in a great way – “ the faster we make our ideas tangible , the sooner we will be   able to evaluate them , refine them , and zero in on the best solution ” . 

 Insight 

 It is unrealistic to expect that data visualization tools and techniques will unleash a barrage of   ready - made stories from datasets . There are no rules , no ‘ protocol ’ that will guarantee us a   story . Instead , I think it makes more sense to look for ‘ insights ’ , which can be artfully woven   into stories in the hands of a good journalist . 

 Every new visualization is likely to give us some insights into our data . Some of those   insights might be already known ( but perhaps not yet proven ) while other insights might be   completely new or even surprising to us . Some new insights might mean the beginning of a   story , while others could just be the result of errors in the data , which are most likely to be   found by visualizing the data . 

 In order to make the finding of insights in data more effective , I find the following process   very helpful : 

 Approach 

 The scientific visualization tool used in my challenge is hard to find any visualization or   data wrangling technique that is not already built into R. Therefore better visualization tools   may be preferred for future development . 


EMAIL: 
ID_NUM: 
NAME_STUDENT: 
PHONE_NUM: 
STREET_ADDRESS: 
URL_PERSONAL: 
USERNAME: 

### Task: You are a PII (Personal Identity Information) Detection. Given a essays written by students, you have to identify ONLY the following:
NAME_STUDENT - The full or partial name of a student that is not necessarily the author of the essay. This excludes instructors, authors, and other person names.
EMAIL - A student’s email address.
USERNAME - A student's username on any platform.
ID_NUM - A number or sequence of characters that could be used to identify a student, such as a student ID or a social security number.
PHONE_NUM - A phone number associated with a student.
URL_PERSONAL - A URL that might be used to identify a student.
STREET_ADDRESS - A full or partial street address that is associated with the student, such as their home address.
### Input: Visualization in design thinking 

 Challenge   In order to design the solution , first we have to build a good understanding of the problem   that we are trying to solve . Interviews , observations , desk research and other research   techniques that are applied during this phase generate huge amount of data – data that has to   be grouped and analyze . Creating a research wall is a great way to display insights , photos ,   and artifacts – all the relevant research outputs in one place . This approach helps us build   connections between different findings and understand the bigger picture . The visual aspect   of the wall triggers idea generation and enables project members to better understand   research insights . For this reason design thinkers often use tools such as persona which give a   face to the customer / interviewee . 

 Visual tools that can be used for understanding the problem are for e.g. personas , mind map ,   customer journey maps , moodboard , foto safari . 

 Selection   In his book Change by Design , Isiah Strickland states that drawing for designers is a way to   express their ideas and only drawing “ can simultaneously reveal both the functional   characteristics of an idea and its emotional content . ” It is not necessary to poses good   drawing skills – as the popular saying goes “ picture is worth a thousand words ” and even a   simple sketch can tell us more than a 10 minutes description of an idea . In a group setting ,   visualization helps to spark idea generation . Seeing what other people are drawing , adding   elements to their drawing or simply discussing the sketches helps to build on top of each   others ideas . Brainstorming sessions can be also enhanced by the use of visual props such as   nudge cards to stimulate idea creation . 

 Drawing can benefit our understanding of how the idea unfolds through different stages of   the service , particularly when generating ideas for a new service , 

 Visual tools that can be used in idea generation are for e.g. 10×10 , storyboard , nudge cards 

 Visual tools that can be used for prototyping are for e.g. desktop walkthrough , cardboard   prototyping , paper prototyping , role playing . 

 Application   Citing Katja Tschimmel “ in the same way that sketching helps the designer to think and   elaborate ideas , early prototyping is another way of visualizing and testing new solutions . It is   a visual manifestation of concepts , the transformation of an idea in a testable model ” . In   another words , use of prototyping transforms ideas from drawings on a paper to tangible   solutions . This shift helps us explore different possibilities , compare how the customers   perceive prototypes , and improve solutions without investing a lot of money . Prototypes tend   to be “ cheap and dirty ” , which means that they are not a polished solution but instead a   working version of a service that is good enough to be understood by the customer . For this   reason , development of prototypes does n’t require a lot of time and money . Isiah Strickland 

 summarizes it in a great way – “ the faster we make our ideas tangible , the sooner we will be   able to evaluate them , refine them , and zero in on the best solution ” . 

 Insight 

 It is unrealistic to expect that data visualization tools and techniques will unleash a barrage of   ready - made stories from datasets . There are no rules , no ‘ protocol ’ that will guarantee us a   story . Instead , I think it makes more sense to look for ‘ insights ’ , which can be artfully woven   into stories in the hands of a good journalist . 

 Every new visualization is likely to give us some insights into our data . Some of those   insights might be already known ( but perhaps not yet proven ) while other insights might be   completely new or even surprising to us . Some new insights might mean the beginning of a   story , while others could just be the result of errors in the data , which are most likely to be   found by visualizing the data . 

 In order to make the finding of insights in data more effective , I find the following process   very helpful : 

 Approach 

 The scientific visualization tool used in my challenge is hard to find any visualization or   data wrangling technique that is not already built into R. Therefore better visualization tools   may be preferred for future development .
### Output: 