Most researchers already share their findings using traditional formats such as journal articles, conference presentations, and reports. But digital data in machine-readable formats afford new dissemination possibilities that go beyond these print-based formats and allow us to also publish the underlying data from our research so that others can replicate our findings or derive new results of their own. In addition, it is increasingly expected by journals (eg. PLOSOne, Nature) and federal funding agencies (eg. NIH or NSF) that researchers make their data publicly available, such as depositing to open data repositories. However, if not planned in advance, sharing data can sometimes be difficult and time intensive. In this session we will explore the options that you have for “publishing” your digital research data in ways that facilitate reuse and help you get appropriate attribution.
In the first half of the session, we will discuss the many considerations for publishing your digital research data, such as copyright issues, applying appropriate licenses, persistent citations, and documentation formats.
In the second half, a range of data publishing options will be explored, including subject-specific and institutional repositories for data. Using the new Data Repository at the University of Minnesota (DRUM) as an example, participants will experience the data publishing workflow from selection, to curatorial review, to final publication. Participants will have the opportunity to get hands-on guidance from DRUM data curators on their own data publishing needs.
Recommended for U of M researchers (faculty, post-docs, graduate students, staff). Participants with existing data that they would like to make more publicly available are encouraged to stay after the session for one-on-one consultation and bring their data files and existing data documentation.
To request disability accommodations, please contact the instructor at least one week prior to the workshop.