Skilling-up-in-research-data-management-20181128
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Skilling up In Research Data Management: A crash course for librarians and data stewards Workshop held in Sydney 28th Nov 2018
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Skilling-up-in-research-data-management-20181128
- 1. Room 400, Level 4, Building 11
- 11. 1. 2. 3. 4.
- 13. Photo by Ricky Kharawala on Unsplash
- 21. Photo by Andrew Worley on Unsplash
- 26. Photo by Alex Block on Unsplash
- 29. Exploratory/Scoping Reuse/Secondary data analysis Can be starting point or ad hoc Peer review Reproduce/extend results Repurpose (e.g. for mashups, visualisations, simulations) Verify claims (e.g. report findings) *Not in any order; not exhaustive!
- 31. Google Ask a colleague Find link to data in a journal article Data journals Data registries e.g. re3data.org Open data portals e.g. data.gov Institutional repositories Data / Discipline repositories e.g. Dryad Project website Data discovery aggregators like Research Data Australia, Google Dataset Library catalogues, databases *Not in any order; not exhaustive!
- 32. When creating metadata records, keep in mind that finding data is: Movable feast / changing beast No standard practice, universal standard or vocab Databases are non-exhaustive Methods for searching and terms driven by why people are looking and how the data is stored
- 33. Together, were going to build a rainbow of discipline specific data examples! Working in pairs, explore re3data (or beyond!) to find data sources that you would recommend for any specific number of disciplines. For each data source: a. find some data b. tell us how you got there - eg google or repository c. why its a good example to show someone else.
- 34. Here are some scenarios to start you off: Showing a researcher where they might find social science data Data that may not have a disciplinary home Incredibly niche specialised scientific data (find a rabbit hole) Australian geographic and/or spatialised data Internet time server data Geological sample data re3data.org https://researchdata.ands.org.au/ https://www.icpsr.umich.edu/ https://ada.edu.au/ http://www.geosamples.org/ https://riojournal.com/
- 41. Your task: 1. Work as a team at your tables 2. Take one of the CSV datasets at 3. Describe the dataset by creating a metadata record. Think about: title, creators, date, short description and so on. 4. Bring your record to whole class discussion Exercise time: 10 mins then whole class discussion
- 44. Your task: 1. Work as a team at your tables 2. Review the record you put together for the CSV file 3. Select a metadata schema of your choice e.g. Dublin Core, RIF-CS, others.. 4. Create a new metadata record using the schema of your choice and the values (attributes) you listed in your original CSV file record Exercise time: 10 mins then whole class discussion
- 53. Photo by rawpixel on Unsplash
- 58. Photo by John O'Nolan on Unsplash
- 64. Why oh why should I use a DOI?
- 67. Photo by Amaury Salas on Unsplash Find information about this DOI: 10.4225/08/5858219e78f9a What type of research output does this DOI point to? What is the organisation associated with this DOI? Can you get to the full text from the DOI? Now search for the same DOI in DataCite search: https://search.datacite.org/ How do you cite it in Vancouver style? Who issued the DOI? Finally, go to DataCite stats: https://stats.datacite.org/ For the Australian National Data Service, which organisation minted the most DOIs for 2018?
- 68. Photo by Tyler Nix on Unsplash
- 80. Photo by Cristian Escobar on Unsplash
- 83. There is no change in the high number of researchers valuing a data citation the same as an article - from 78% in 2016 to 77% in 2017 Digital Science Report: The State of Open Data 2017, p.8
- 84. Your task: 1. Work as a team at your tables 2. Look up and read what these publishers are saying about data citation: Wileys Data Citation Policy - https://authorservices.wiley.com/author-resources/Journal-Authors/open- access/data-sharing-citation/index.html Springer Nature Research Data Policy FAQs (why and how cite data) - https://www.springernature.com/gp/authors/research-data-policy/faqs/12 327154 3. Discuss with each other: are the policies the same? Are the citation styles the same? Is it clear information for authors? Exercise time: 5 mins
- 96. Photo by Alex Block on Unsplash
- 105. Edusmartskills.com. (2018). [online] Available at: https://www.edusmartskills.com/webAssets/images/wso_img.jpg [Accessed 14 May 2018].
- 111. PROS CONS Self explanatory Easy to follow Time saving Distribute in different ways Linked to further resources Missing information Information overload May not be search engine optimised Hard to find
- 116. F2F Online Self Help
- 118. Adapted from: Fao.org. (2018). [online] Available at: http://www.fao.org/docrep/015/i2516e/i2516e.pdf [Accessed 1 May 2018].
- 119. Half day, Full day? Program Timings? Exercises/Activities? Content? Modules? Learning Outcomes? Technology? Learning assessment? How to? Software? ppt, piktochart? Process or Info sharing? A4, Brochure, Web?