23 (research data) Things is a self-guided training concept for anybody interested in data. If you are a person who cares for, and about, research data and want to fill in some gaps, learn more or find out about the rapidly changing research data landscape, then this is for you! The program is likely to be of interest to those who:
We wish to acknowledge Helene Blowers who created the original 23 Things (2006) and Michael Witt who developed 23 Things: Libraries for Research data (2015), and Australian National Data Service (ANDS), who created their 23 (research data) Things program in 2016. This version is based primarily on the ANDS version.
Prerequisites
Come to the meeting with question you have about research data in your discipline or field.
| Setup | |
| Thing 1: Ready Set Data |
What is research data?
Where can you find research data in your discipline? |
| Thing 2: Issues in research data management | What are some of the issues we face in managing research data? |
| Thing 3: Data in the research lifecycle | How does data and its management change over time? |
| Thing 4: Data discovery |
How do repositories and portals play a role in making research data discoverable and accessible?
What makes a good data repository? |
| Thing 5: Data sharing |
How can research data be shared?
What makes a good data repository? |
| Thing 6: Long-lived data: curation & preservation | What is data curation? |
| Thing 7: Data citation for access & attribution | How does data fit in the citation analysis and citation metrics pictures? |
| Thing 8: Citation metrics for data | What are Digital Object Identifiers (DOIs) and how do they support data citation and metrics for data and related research objects? |
| Thing 9: Licensing data for reuse | Understand the importance of data licensing and learn about Creative Commons. |
| Thing 10: Sharing sensitive data | How can you share and publish sensitive data? |
| Thing 11: What's my metadata schema? | What is metadata and what sort of metadata is critical for research data? |
| Thing 12: Vocabularies for data description | What are controlled vocabularies and how are they applied to research data? |
| Thing 13: Walk the crosswalk | What are metada crosswalks in the context of research data? |
| Thing 14: Identifiers and linked data | What is ORCID and why is the academic world buzzing about it? |
| Thing 15: Data management plans | What is a Data Management Plan? |
| Thing 16: What are publishers & funders saying about data? | What are publishers & funders perspectives on research data? |
| Thing 17: Data literacy & outreach | What resources exist for building an inclusive culture of data literacy - not just scientists and science disciplines? |
| Thing 18: Data interviews: talk the talk | Question 1 |
| Thing 19: Exploring APIs and Apps |
What are APIs?
How are APIs used with data? |
| Thing 20: Find it with data! | Question 1 |
| Thing 21: Tools of the (dirty data) trade | What is dirty data and why we should care? |
| Thing 22: What's in a name? | Who are the key players in Australia’s research data management ecosystem? |
| Thing 23: Making connections | Question 1 |
The actual schedule may vary slightly depending on the topics and exercises chosen by the instructor.