Methods for data sharing
There are currently a number of ways in which data may be shared, both informal and formal.
Informal methods
Many researchers are accustomed to sharing data within their research group or extended 'virtual organisation' or an international research partnership.
In these situations, risk is perceived as low and trust is high, particularly with co-investigators or co-authors.
Data sharing within a group can be accomplished in a number of ways, but most of them require centrally administered, authenticated access.
- shared network file server (for example, within a research group, school or department)
- intranets or content management systems
- research project wikis (such as through the Confluence service offered by Information Services)
- online collaboration tools or groupware (for example, Google Docs and Spreadsheets)
- proprietary enterprise software (for example, Microsoft Sharepoint)
- computer 'grid' network via custom data applications
- social networking sites for researchers (such as myExperiment)
Researchers may also be persuaded to share data with other researchers or students who make a personal request based on knowledge of the researcher's work.
Direct communication means that the researcher can ask questions about the intent of use and the user's experience, and that the user can follow up with questions if use of the data is not clear-cut.
In these situations, direct or 'peer to peer' sharing of data files may take place via:
- email attachments
- posting files on a website or ftp (file transfer protocol) server, with the link sent by email
- laptop to flashdrive (for example, at a conference)
- Compact Disc (CD) or Digital Video Disc (DVD) (in the post)
- social networking sites
- file sharing sites
- mobile devices; bluetooth networking
Formal methods
Researchers often have options or requirements (from publishers or funders) to share their data more broadly.
This normally involves additional effort such as preparing a public use version of the dataset (including anonymisation techniques), 'cleaning' the data of routine errors, documenting or annotating the data to improve its understandability, and possibly reformatting the data, so that it can be re-used in another research context.
Once this work is complete the data may be disseminated or 'published' through one of the following methods.
- post on a University website
- post on a public website or wiki
- post on a publisher's website
- upload to a distributed, dynamic database (discipline-specific, such as a protein or gene database)
- deposit in a central data archive (such as the UK Data Archive, funded by the Economic and Social Research Council)
- deposit in a data centre (such as one of the Natural Environment Research Council's data centres)
- deposit in a local data repository (such as Edinburgh DataShare)
This article was published on Aug 28, 2009