Electrooculography
MeSH ID: D004585
Description:
Recording of the average amplitude of the resting potential arising between the cornea and the retina in light and dark adaptation as the eyes turn a standard distance to the right and the left. The increase in potential with light adaptation is used to evaluate the condition of the retinal pigment epithelium.
Best practice for sharing this type of data:
Numeric features of the electrooculograph signal, such as latency and amplitude of corneal-retinal potentials, may 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:
Many repositories are suitable for tabular data. Your institution, journal, or funder may recommend specific repositories, otherwise 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.
