The measurement of the quantity of heat involved in various processes, such as chemical reactions, changes of state, and formations of solutions, or in the determination of the heat capacities of substances. The fundamental unit of measurement is the joule or the calorie (4.184 joules). (McGraw-Hill Dictionary of Scientific and Technical Terms, 4th ed. Indirect calorimetry is the calculation of the energy expenditure in the form of heat production of the whole body or individual organs based on respiratory gas exchange.
Best practice for sharing this type of data:
Indirect calorimetry data often comes from three major instrument manufacturers (Sable Systems, TSE, and Columbus Instruments; Mina et al. 2019). These systems can export raw data as .csv files that can be shared in a repository. Downstream, processed data used in analyses should be shared as Tabular data. Similarly, unprocessed direct calorimetry data can be stored as individual .csv files, while processed data used in analysis should be shared as Tabular data, which should be saved as a .txt or .csv file. The first row(s) should contain information about the dataset, such as the data file name, author, today's date, when the data within the file were last modified, and companion file names. Please also state which symbol has been used to denote missing data (NA is preferred). Column headings should describe the content of each column and contain only numbers, letters, and underscores - no spaces or special characters. Lowercase letters are preferred. Row names should be consistent with those used in the article and in other related datasets.
Most suitable repositories:
Calorimetry data can be added to any repository able to host generic file types, detailed here.
Best practice for indicating re-use of existing data:
For public datasets please provide a DOI or other stable identified for the dataset itself *and* include a citation for the dataset in the reference list. Be sure to indicate exactly which data has been re-used, particularly when multiple versions of the dataset exist. In many cases, this is best achieved by sharing the code used to extract the part of the data that you analyzed. In some cases it may be best to share the exact dataset(s) you analyzed as well.
For access-controlled data authors should provide a link to instructions for obtaining access (e.g. here is the information page for ADNI (Alzheimer's Disease Neuroimaging Initiative): http://adni.loni.usc.edu/data-samples/access-data/).
When re-using a private dataset from a previous study please contact the data owners to discuss how the data can be made public.