Identify complementary data sets that can add value to project data. Strategies to help endure the data have maximum impact include registering the project on a project directory site, depositing data in an open repository, and adding data descriptions to metadata clearing houses.
To make your data available using standard and open software tools you should:
Use standard language and terms to clearly communicate to others that your data are available for reuse and that you expect ethical and appropriate use of your data
Use an open source datacasting (RSS or other type) service that enables you to advertise your data and the options for others to obtain access to it (RSS, GeoRSS, DatacastingRSS)
File names should reflect the contents of the file and include enough information to uniquely identify the data file. File names may contain information such as project acronym, study title, location, investigator, year(s) of study, data type, version number, and file type.
When choosing a file name, check for any database management limitations on file name length and use of special characters. Also, in general, lower-case names are less software and platform dependent. Avoid using spaces and special characters in file names, directory paths and field names. Automated processing, URLs and other systems often use spaces and special characters for parsing text string. Instead, consider using underscore ( _ ) or dashes ( - ) to separate meaningful parts of file names. Avoid $ % ^ & # and similar symbols.
If versioning is desired a date string within the file name is recommended to indicate the version.
Avoid using file names such as mydata.dat or 1998.dat.
To maximize usability of your data or outputs, ensure that those with impairments or disabilities will still be able to access and understand them. The Web Accessibility Initiative, from the W3C, suggests that those producing content for others consider the following (text from their website):
Make your outputs perceivable
Make all functionality available from a keyboard
Make your outputs understandable
Make your outputs robust
When searching for data, whether locally on one’s machine or in external repositories, one may use a variety of search terms. In addition, data are often housed in databases or clearinghouses where a query is required in order access data. In order to reproduce the search results and obtain similar, if not the same results, it is necessary to document which terms and queries were used.