Coulometry Data
MeSH ID: Part of Electrochemistry D004563
Description:
Coulometry (or Coulombimetry) is the name given to a group of electroanalytical chemistry techniques that determine the amount of matter transformed during an electrolysis reaction by measuring the amount of electricity (in coulombs) consumed or produced. Coulometric titration is the process of determining the quantity of a substance A by adding measured increments of substance B, with which it reacts (almost always as a standardized solution called the titrant, but also by electrolytic generation, as in coulometric titration).
Best practice for sharing this type of data:
Raw data files can be deposited in Chemistry data specific repositories (see below).Tables containing the data used for calculations should be shared, along with explanations on how the final data in the paper were calculated. These should be shared as Tabular data: Tabular data 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:
Electrochemical data can be deposited in PubChem. Other potentially suitable repositories are listed here. Tabular summarized data that are used for analysis in the paper 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.
