Resources

Tutorials

• Data Organization in Spreadsheets for Social Scientists: Data Carpentry

Cheatsheets

• Markdown Basic Syntax
• W3C SQL Tutorial

Useful Organizations

• The PID Forum
• Data Documentation Initiative
• Data Curation Network
• DataCite
• CrossRef
• Digital Curation Centre

Metadata schemas and controlled vocabularies

Schemas

• Data Documentation Initiative (DDI)
• Dublin Core Metadta Initiative (DC)
• schema.org
• Datacite
• Humanitarian eXchange Language (HXL)

Controlled vocabularies

• UNESCO Thesaurus
• Medical Subject Headings (MeSH)
• IPTC NewsCodes
• IFLA’s Guidelines for Multilingual Thesauri

Bibliography

Data and Digital Curation

• Curry, E., Freitas, A., & O’Riáin, S. (2010). The role of community-driven data curation for enterprises. In Wood, D. (eds). Linking enterprise data. Springer, Boston, MA. https://doi.org/10.1007/978-1-4419-7665-9_2
• Higgins, S. (2008). The DCC Curation Lifecycle Model. The International Journal of Digital Curation, 1(3), 134-140. doi: 10.2218/ijdc.v3i1.48

Data Sharing

• Borgman, C. L. (2012). The conundrum of sharing research data. Journal of the American Society for Information Science and Technology, 63, 1059-1078. doi: 10.1002/asi.22634
• Cragin, M. H., Palmer, C. L., & Carlson, J. R. (2010). Data sharing, small science and institutional repositories. Philosophical Transactions of the Royal Society, 368, 4023-4038. doi: 10.1098/rsta.2010.0165
• Curty, R., Yoon, A., Jeng., W., & Qin, J. (2016). Untangling data sharing and reuse in social sciences. Proceedings of the Association for Information Science and Technology, 53(1), 1-5. doi: 10.1002/pra2.2016.14505301025
• Wills, C., Greenberg, J., & White, H. (2012). Analysis and synthesis of metadata goals for scientific data. Journal for the American Society for Information Science & Technology, 63, 1505-1520. doi: 10.1002/asi.22683

Data Sharing in Psychology

• Meyer M.N. (2018). Practical Tips for Ethical Data Sharing. Advances in Methods and Practices in Psychological Science, 1(1), 131-144. doi: 10.1177/2515245917747656.
• Ross, M. W., Iguchi, M. Y., & Panicker, S. (2018). Ethical aspects of data sharing and research participant protections. The American psychologist, 73(2), 138–145. doi: 10.1037/amp0000240.
• Towse, J. N., Ellis, D. A., & Towse, A. S. (2021). Opening Pandora’s Box: Peeking inside Psychology’s data sharing practices, and seven recommendations for change. Behavior research methods, 53(4), 1455-1468. doi: 10.3758/s13428-020-01486-1.

Data Reuse

• Curty, R. G. (2016). Factors influencing research data reuse in the social sciences: An exploratory study. International Journal of Digital Curation, 11(1), 96-117. doi: 10.2218/ijdc.v11i1.401.
• Buckner, Elizabeth, Daniel Shephard, and Anne Smiley. (2022). Beyond Numbers: The Use and Usefulness of Data for Education in Emergencies. Journal on Education in Emergencies, 8(1), 214-42. doi: 10.33682/tgfd-m9eg.
• Faniel, I. M., Kriesberg, A., & Yakel, E. (2016). Social scientists’ satisfaction with data reuse. Journal of the Association for Information Science and Technology, 67(6), 1401-1416. doi: 10.1002/asi.23480.
• Karcher, S., Kirilova, D., Pagé, C., & Weber, N. (2021). How Data Curation Enables Epistemically Responsible Reuse of Qualitative Data. The Qualitative Report, 26(6), 1996-2010. doi: 10.46743/2160-3715/2021.5012.
• Wallis, J. C., Rolando, E., & Borgman, C. L. (2013). If we share data, will anyone use them? Data sharing and reuse in the long tail of science and technology. PLoSONE, 8(7), e67332. doi: 10.1371/journal.pone.0067332

Archiving

• Baker, K. S., Duerr, R. E., & Parsons, M. A. (2015). Scientific knowledge mobilization: Co-evolution of data products and designated communities. International Journal of Digital Curation, 10(2), 110-135. doi: 10.2218/ijdc.v10i2.346
• Bettivia, R. S., 2016, The power of imaginary users: Designated communities in the OAIS reference model. Proceedings of the Association for Information Science and Technology, 53(1), 1-9. doi: 10.1002/pra2.2016.14505301038.
• Boutard, G., 2020. Alter-Value in Data Reuse: Non-Designated Communities and Creative Processes. Data Science Journal, 19(1), p.23. doi: 10.5334/dsj-2020-023.
• Donaldson, D. R., Zegler-Poleska, E., Yarmey, L. (2020). Data managers’ perspectives on OAIS designated communities and the FAIR principles: mediation, tools and conceptual models. Journal of Documentation, 76(6), 1261-1277. doi: 10.1108/JD-10-2019-0204
• Parsons, M.A. and Duerr, R. (2005), “Designating user communities for scientific data: challenges and solutions”, Data Science Journal, 4(24), 31-38. doi: 10.2481/dsj.4.31.

Protecting Vulnerable Data Subjects

• Calamai, S., Kolletzek, C., & Kelli, A. (2019, May). Towards a protocol for the curation and dissemination of vulnerable people archives. In Selected papers from the CLARIN Annual Conference 2018. Linköping Electronic Conference Proceedings 159 (28–38). https://www.researchgate.net/publication/342832401_Towards_a_protocol_for_the_curation_and_dissemination_of_vulnerable_people_archives

• Malgieri, G., & González Fuster, G. (2021), The Vulnerable Data Subject: A Gendered Data Subject?. Available at SSRN. https://ssrn.com/abstract=3913249 or http://dx.doi.org/10.2139/ssrn.3913249

• Malgieri, G., & Niklas, J. (2020). Vulnerable Data Subjects. Computer Law & Security Review, 37, 105415. doi: 10.1016/j.clsr.2020.105415

• Tiffin, N., George A., & LeFevre, A.E. (2019). How to use relevant data for maximal benefit with minimal risk: digital health data governance to protect vulnerable populations in low-income and middle-income countries. BMJ Global Health, 4(2). doi: 10.1136/bmjgh-2019-001395

• Aggregated data provides a false sense of security [blog], https://iapp.org/news/a/aggregated-data-provides-a-false-sense-of-security/

Data Sovereignty

Toward a More Just Library: Participatory Design with Native American Students: https://quod.lib.umich.edu/w/weave/12535642.0001.901?view=text;rgn=main