The case study clarifies that diverse and often inconsistent datasets are prevalent in heterogeneous catalysis. Here, we seek to classify the various tasks that are often performed to make it more convenient to work with these quantities and correct or combine the values consistently. All tasks aim to construct a consistent thermochemical network that can be used to compute reaction energies that will be used as inputs to microkinetic models or other analyses. We broadly classify these into tasks of "comparison and conversion", which involve only arbitrary modifications of data such that all relative quantities within a dataset remain unchanged, and approaches for "combining and correcting" energies, which involve changes to relative quantities within a dataset. The first class of tasks aims to create a local thermochemical network with anchors that do not correspond to the standard states, whereas the latter class of tasks integrates the data into a global thermochemical network with the standard anchors that facilitates combining data from multiple sources (gasphase species, experimental data, etc.). The tasks for combining and correcting require decisions and compromises for selecting or combining inconsistent data. Different decisions and compromises may yield different reaction energies. It is further possible to divide the approaches into two categories. Most described methods use an atomic reference basis set, where a single reference/anchor species is selected for every element. The basis set terminology was first introduced by Mhadeshwar et al. for computational catalysis. Another approach has recently emerged that uses a molecular fragment reference basis set, where a reference species is defined for a particular feature of the target, e.g., bond type. This work aims to provide a standardized way of considering the various compromises involved with each approach and provide researchers with convenient mathematical tools for implementing them. Fig. summarizes the different approaches graphically. All methods are discussed assuming C x H y O z molecules and adsorbates, but it is straightforward to extend the methods to an arbitrary number of chemical elements (e.g., N or S) by adding additional reference species. Examples of all methods are provided in tutorial Jupyter Notebooks included in the supplementary information and in ref 124.