References

Berkley, C., Bowers, S., Jones, M. B., Madin, J. S., & Schildhauer, M. (2009). Improving data discovery for metadata repositories through semantic search. In L. Barolli,

F. Xhafa, & H. Hui-Huang (Eds.), CISIS 2009, International Conference on Complex, Intelligent and Software Intensive Systems (pp. 1152–1159). New York: IEEE Explore Digital Library. https://doi.org/10.1109/CISIS.2009.122 .

Borgman, C. L., Golshan, M. S., Sands, A. E., Wallis, J. C., Cummings, R. L., Darch, P. T., & Randles, B. M. (2016). Data management in the long tail: Science, software, and service. International Journal of Digital Curation, 11, 128–149. https://doi.org/10.2218/ ijdc.v11i1.428 .

Burgess, M., & Noy, N. (2018). Building Google dataset search and fostering an open data ecosystem. [Blog]. Retrieved February 14, 2020, from https://ai.googleblog. com/2018/09/building-google-dataset-search-and.html .

Chapman, A., Simperl, E., Koesten, L. Konstantinidis, G., Ibáñez-Gonzalez, L., Kacprzak, E., & Groth, P. (2019). Dataset search: A survey. Retrieved November 13, 2019, from https://arxiv.org/abs/1901.00735 .

Ellis, D., & Haughan, M. (1997). Modelling the information seeking patterns of engineers and research scientists in an industrial environment. Journal of Documentation, 53(4), 384–403. https://doi.org/10.1108/EUM0000000007204 .

GeRDI. Generic Research Data Infrastructure. (n.d.). Retrieved November 13, 2019, from https://www.gerdi-project.eu/ .

Gregory, K., Groth, P., Cousijn, H., Scharnhorst, A., & Wyatt, S. (2019a). Searching data: A review of observational data retrieval practices in selected disciplines. Journal of the Association for Information Science and Technology, 70(5), 2019, 419–432. https:// doi.org/10.1002/asi.24165 .

Gregory, K., Groth, P., Cousijn, H., Scharnhorst, A., & Wyatt, S. (2019b). Understanding Data Search as a Socio-technical Practice. https://arxiv.org/abs/1801.04971v3 .

Groth, P., Koesten, L., Mayr, P., de Rijke, M., & Simperl, E. (2018). DATA:SEARCH’18

– Searching data on the web. In L. Dietz, L. Koesten, & S. Verberne (Eds.), SIGIR2018 Workshops: ProfS, KG4IR, and DATA:SEARCH (pp. 65–73). Retrieved Febriary 11, 2020, from http://ceur-ws.org/Vol-2127/preface-datasearch.pdf .

Halevy, A., Korn, F., Noy, N. F., Olston, C., Polyzotis, N., Roy, S., & Whang, S. E. (2016). Goods: Organizing Google’s datasets. In Proceedings of the 2016 International Conference on Management of Data (pp. 795–806). New York: ACM. https://doi. org/10.1145/2882903.2903730 .

Hirschheim, R., & Klein, H. K. (2012). A glorious and not-so-short history of the information systems field. Journal of the Association for Information Systems, 13(4), 188–235. http://doi.org/10.17705/1jais.00294 .

ICPSR. Find & analyze data. (2019). Retrieved November 13, 2019, from https://www. icpsr.umich.edu/icpsrweb/ICPSR/search/studies .

Kern, D., & Mathiak, B. (2015). Are there any differences in data set retrieval compared to well-known literature retrieval? In S. Kapidakis, C. Mazurek, & M. Werla (Eds.), Research and advanced technology for digital libraries (pp. 197–208). Cham, CH: Springer International Publishing. https://doi. org/10.1007/978-3-319-24592-8_15 .

Khalsa, S., Cotroneo, P., & Wu, M. (2018). A survey of current practices in data search services. https://doi.org/10.17632/7j43z6n22z.1 .

Kuhlthau, C. C. (1991). Inside the search process: Information seeking from the user’s perspective. Journal of the American Society for Information Science, 42(5), 361–371. https://doi.org/10.1002/(SICI)1097-4571(199106)42:5<361::AID-ASI6 >3.0.CO;2-%23.

Kunze, S. R., & Auer, S. (2013). Dataset retrieval. Proceedings of the 2013 IEEE Seventh International Conference on Semantic Computing (pp. 1–8). New York: IEEE Computer Society. https://doi.org/10.1109/ICSC.2013.12 .

Lewandowski, D. (2015). Ranking library materials. Retrieved November 13, 2019, from https://arxiv.org/abs/1511.05806 .

Li, W., Goodchild, M. F., & Raskin, R. (2014). Towards geospatial semantic search: Exploiting latent semantic relations in geospatial data. International Journal of Digital Earth, 7(1), 17–37. https://doi.org/10.1080/17538947.2012.674561 .

Megler, V. M., & Maier, D. (2015). Demonstrating ‘Data near here’: Scientific data search. Proceedings of the 2015 ACM SIGMOD International Conference on Management of Data, (pp. 1075–1080). New York: ACM. https://doi.org/10.1145/2723372.2735360 .

Newson, K. (2019). Introducing the data curation tool. Retrieved February 11, 2020, from https://spotdocs.scholarsportal.info/display/DAT/2019/09/26/Introducing+the+D ata+Curation+Tool .

PANGAEA. Data publisher for earth & environmental science. (n.d.). Retrieved November 13, 2019, from https://pangaea.de/ .

Sea Around Us. Fisheries, ecosystems and biodiversity. (n.d.). Retrieved November 13, 2019, from http://www.seaaroundus.org/ .

Stempfhuber, M., & Zapilko, B. (2009). Integrated retrieval of research data and publications in digital libraries. In S. Mornati & T. Hedlund (Eds.), Rethinking electronic publishing: Innovations in communication paradigms. Proceedings of the13th International Conference on Electronic Publishing (ELPUB 2009) (pp. 613–620). Roma: Nuovo cultura https://dblp.org/rec/conf/elpub/StempfhuberZ09 .

Takeuchi, S., Sugiura, K., Akahoshi, Y., & Zettsu, K. (2017). Spatio-temporal pseudo relevance feedback for scientific data retrieval. IEEJ Transactions on Electrical and Electronic Engineering, 12(1), 124–131. https://doi.org/10.1002/tee.22352 .

Wilkinson, M. D., Dumontier, M., Aalbersberg, I. J., Appleton, G., Axton, M., Baak, A., … Mons, B. (2016). The FAIR Guiding Principles for scientific data management and stewardship. Scientific Data, 3, 160018, n.p. https://doi.org/10.1038/sdata.2016.18 .

Wu, M., Psomopoulos, F., Khalsa, S. J., & de Waard, A. (2019). Data discovery paradigms: User requirements and recommendations for data repositories. Data Science Journal, 18(1), 3. https://doi.org/10.5334/dsj-2019-003 .