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The GitHub repository containing all the material related to the Open Science course of the Digital Humanities and Digital Knowledge degree at the University of Bologna (a.a. 2022/2023).

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Open Science

This space contains all the material related to the Open Science course of the Digital Humanities and Digital Knowledge degree at the University of Bologna.

Academic year 2022/2023

Table of content

Material

  1. [22 March 2023, 12:30-15:30] Introduction to Open Science


  2. [23 March 2023, 12:30-15:30] Reproducibility

    • Theoretical part: slide
    • Practical part: slide
    • Bibliography
      • Baker, M. (2016). 1,500 scientists lift the lid on reproducibility. Nature, 533(7604), 452–454. https://doi.org/10.1038/533452a
      • Cobo, M. J., Dehdarirad, T., García-Sánchez, P., & Moral-Munoz, J. A. (2018). Quantifying the reproducibility of scientometric analyses: A case study. STI 2018 Conference Proceedings, 925–933. https://hdl.handle.net/1887/65242
      • Fanelli, D. (2018). Opinion: Is science really facing a reproducibility crisis, and do we need it to? Proceedings of the National Academy of Sciences, 115(11), 2628–2631. https://doi.org/10.1073/pnas.1708272114
      • Kramer, B., & Bosman, J. (2015, June 18). The good, the efficient and the open—Changing research workflows and the need to move from Open Access to Open Science. CERN Workshop on Innovations in Scholarly Communication (OAI9), University of Geneva, Geneva, Switzerland. https://www.slideshare.net/bmkramer/the-good-the-efficient-and-the-open-oai9
      • Heibi, I., & Peroni, S. (2021). A qualitative and quantitative analysis of open citations to retracted articles: The Wakefield et al.’s case. Scientometrics, 126(10), 8433–8470. https://doi.org/10.1007/s11192-021-04097-5
      • Heibi, I., & Peroni, S. (2022). A quantitative and qualitative open citation analysis of retracted articles in the humanities. Quantitative Science Studies, 3(4), 953–975. https://doi.org/10.1162/qss_a_00222
      • Meng, X.-L. (2020). Reproducibility, Replicability, and Reliability. Harvard Data Science Review, 2(4). https://doi.org/10.1162/99608f92.dbfce7f9
      • Moylan, E. C., & Kowalczuk, M. K. (2016). Why articles are retracted: A retrospective cross-sectional study of retraction notices at BioMed Central. BMJ Open, 6(11), e012047. https://doi.org/10.1136/bmjopen-2016-012047
      • Peels, R., & Bouter, L. (2018). The possibility and desirability of replication in the humanities. Palgrave Communications, 4(1), 95. https://doi.org/10.1057/s41599-018-0149-x
      • Peng, R. (2015). The reproducibility crisis in science: A statistical counterattack. Significance, 12(3), 30–32. https://doi.org/10.1111/j.1740-9713.2015.00827.x
      • Schnell, S. (2015). Ten Simple Rules for a Computational Biologist’s Laboratory Notebook. PLOS Computational Biology, 11(9), e1004385. https://doi.org/10.1371/journal.pcbi.1004385
      • Velden, T., Hinze, S., Scharnhorst, A., Schneider, J. W., & Waltman. (2018). Exploration of reproducibility issues in scientometric research. In R. Costas, T. Franssen, & A. Yegros-Yegros (Eds.), STI 2018 Conference Proceedings (pp. 612–624). Centre for Science and Technology Studies. https://hdl.handle.net/1887/65315

  3. [29 March 2023, 12:30-15:30] FAIR and Open Data

    • Theoretical part: slide
    • Practical part: slide
    • Bibliography
      • Avanço, K., Balula, A., Błaszczyńska, M., Buchner, A., Caliman, L., Clivaz, C., Costa, C., Franczak, M., Gatti, R., Giglia, E., Gingold, A., Jarmelo, S., Padez, M. J., Leão, D., Maryl, M., Melinščak Zlodi, I., Mojsak, K., Morka, A., Mosterd, T., … Wieneke, L. (2021). Future of Scholarly Communication—Forging an inclusive and innovative research infrastructure for scholarly communication in Social Sciences and Humanities (p. 46). Digital Humanities Centre at the Institute of Literary Research of the Polish Academy of Sciences. https://doi.org/10.5281/zenodo.5017705
      • Belhajjame, K., B’Far, R., Cheney, J., Coppens, S., Cresswell, S., Gil, Y., Groth, P., Klyne, G., Lebo, T., McCusker, J., Miles, S., Myers, J., Sahoo, S., & Tilmes, C. (2013). PROV-DM: The PROV Data Model (L. Moreau & P. Missier, Eds.). World Wide Web Consortium. https://www.w3.org/TR/prov-dm/
      • Chue Hong, N. P., Katz, D. S., Barker, M., Lamprecht, A.-L., Martinez, C., Psomopoulos, F. E., Harrow, J., Castro, L. J., Gruenpeter, M., Martinez, P. A., & Honeyman, T. (2022). FAIR Principles for Research Software (FAIR4RS Principles) [Recommendations with RDA Endorsement in Process]. Research Data Alliance. https://doi.org/10.15497/RDA00068
      • Regulation (EU) 2016/679 of the European Parliament and of the Council of 27 April 2016 on the protection of natural persons with regard to the processing of personal data and on the free movement of such data, and repealing Directive 95/46/EC (General Data Protection Regulation), no. L119, Official Journal of the European Union (2016). http://data.europa.eu/eli/reg/2016/679/oj
      • GO FAIR. (2018). FAIR Principles. https://www.go-fair.org/fair-principles/
      • Gomes, D. G. E., Pottier, P., Crystal-Ornelas, R., Hudgins, E. J., Foroughirad, V., …, & Gaynor, K. M. (2022). Why don’t we share data and code? Perceived barriers and benefits to public archiving practices. Proceedings of the Royal Society B: Biological Sciences, 289(1987), 20221113. https://doi.org/10.1098/rspb.2022.1113
      • Gualandi, B., Pareschi, L., & Peroni, S. (2022). What do we mean by «data»? A proposed classification of data types in the arts and humanities. Journal of Documentation. https://doi.org/10.1108/JD-07-2022-0146
      • Haak, L. L., Fenner, M., Paglione, L., Pentz, E., & Ratner, H. (2012). ORCID: A system to uniquely identify researchers. Learned Publishing, 25(4), 259–264. https://doi.org/10.1087/20120404
      • Kramer, B., & Bosman, J. (2015, June 18). The good, the efficient and the open—Changing research workflows and the need to move from Open Access to Open Science. CERN Workshop on Innovations in Scholarly Communication (OAI9), University of Geneva, Geneva, Switzerland. https://www.slideshare.net/bmkramer/the-good-the-efficient-and-the-open-oai9
      • Landi, A., Thompson, M., Giannuzzi, V., Bonifazi, F., Labastida, I., da Silva Santos, L. O. B., & Roos, M. (2020). The “A” of FAIR – As Open as Possible, as Closed as Necessary. Data Intelligence, 2(1–2), 47–55. https://doi.org/10.1162/dint_a_00027
      • Lin, D., Crabtree, J., Dillo, I., Downs, R. R., Edmunds, R., Giaretta, D., De Giusti, M., L’Hours, H., Hugo, W., Jenkyns, R., Khodiyar, V., Martone, M. E., Mokrane, M., Navale, V., Petters, J., Sierman, B., Sokolova, D. V., Stockhause, M., & Westbrook, J. (2020). The TRUST Principles for digital repositories. Scientific Data, 7(1), 144. https://doi.org/10.1038/s41597-020-0486-7
      • Michener, W. K. (2015). Ten Simple Rules for Creating a Good Data Management Plan. PLOS Computational Biology, 11(10), e1004525. https://doi.org/10.1371/journal.pcbi.1004525
      • Open Knowledge Foundation. (2015). Open Definition 2.1. https://opendefinition.org/od/2.1/en/
      • Piwowar, H., Priem, J., Larivière, V., Alperin, J. P., Matthias, L., Norlander, B., Farley, A., West, J., & Haustein, S. (2017). Data From: The State Of Oa: A Large-Scale Analysis Of The Prevalence And Impact Of Open Access Articles [Data set]. Zenodo. https://doi.org/10.5281/zenodo.837901
      • Wilkinson, M. D., Dumontier, M., Aalbersberg, I. J., Appleton, G., Axton, M., Baak, A., Blomberg, N., Boiten, J.-W., da Silva Santos, L. B., Bourne, P. E., Bouwman, J., Brookes, A. J., Clark, T., Crosas, M., Dillo, I., Dumon, O., Edmunds, S., Evelo, C. T., Finkers, R., … Mons, B. (2016). The FAIR Guiding Principles for scientific data management and stewardship. Scientific Data, 3, 160018. https://doi.org/10.1038/sdata.2016.18
      • Wolfe, M. (2017, August 9). CC0 and Data Citation. https://www.library.ucdavis.edu/news/cc0-and-data-citation/

  4. [30 March 2023, 12:30-15:30] Open Methodology

    • Theoretical part: slide
    • Practical part: slide
    • Bibliography
      • Beg, M., Taka, J., Kluyver, T., Konovalov, A., Ragan-Kelley, M., Thiery, N. M., & Fangohr, H. (2021). Using Jupyter for Reproducible Scientific Workflows. Computing in Science & Engineering, 23(2), 36–46. https://doi.org/10.1109/MCSE.2021.3052101
      • Belhajjame, K., Zhao, J., Garijo, D., Gamble, M., Hettne, K., Palma, R., Mina, E., Corcho, O., Gómez-Pérez, J. M., Bechhofer, S., Klyne, G., & Goble, C. (2015). Using a suite of ontologies for preserving workflow-centric research objects. Journal of Web Semantics, 32, 16–42. https://doi.org/10.1016/j.websem.2015.01.003
      • Bolderston, A. (2008). Writing an Effective Literature Review. Journal of Medical Imaging and Radiation Sciences, 39(2), 86–92. https://doi.org/10.1016/j.jmir.2008.04.009
      • Celebi, R., Rebelo Moreira, J., Hassan, A. A., Ayyar, S., Ridder, L., Kuhn, T., & Dumontier, M. (2020). Towards FAIR protocols and workflows: The OpenPREDICT use case. PeerJ Computer Science, 6, e281. https://doi.org/10.7717/peerj-cs.281
      • Clarke, P., Buckell, J., & Barnett, A. (2020). Registered Reports: Time to Radically Rethink Peer Review in Health Economics. PharmacoEconomics - Open, 4(1), 1–4. https://doi.org/10.1007/s41669-019-00190-x
      • Crusoe, M. R., Abeln, S., Iosup, A., Amstutz, P., Chilton, J., Tijanić, N., Ménager, H., Soiland-Reyes, S., Gavrilović, B., Goble, C., & Community, T. C. (2022). Methods included: Standardizing computational reuse and portability with the Common Workflow Language. Communications of the ACM, 65(6), 54–63. https://doi.org/10.1145/3486897
      • Goble, C., Cohen-Boulakia, S., Soiland-Reyes, S., Garijo, D., Gil, Y., Crusoe, M. R., Peters, K., & Schober, D. (2020). FAIR Computational Workflows. Data Intelligence, 2(1–2), 108–121. https://doi.org/10.1162/dint_a_00033
      • Hrynaszkiewicz, I. (2020, December 7). Show your work. Peer-Reviewed Protocols. The Official PLOS Blog. https://theplosblog.plos.org/2020/12/show-your-work-peer-reviewed-protocols/
      • Kramer, B., & Bosman, J. (2015, June 18). The good, the efficient and the open—Changing research workflows and the need to move from Open Access to Open Science. CERN Workshop on Innovations in Scholarly Communication (OAI9), University of Geneva, Geneva, Switzerland. https://www.slideshare.net/bmkramer/the-good-the-efficient-and-the-open-oai9
      • Perneger, T. V. (2004). Writing a research article: Advice to beginners. International Journal for Quality in Health Care, 16(3), 191–192. https://doi.org/10.1093/intqhc/mzh053
      • Teytelman, L., Stoliartchouk, A., Kindler, L., & Hurwitz, B. L. (2016). Protocols.io: Virtual Communities for Protocol Development and Discussion. PLOS Biology, 14(8), e1002538. https://doi.org/10.1371/journal.pbio.1002538
      • Watson, M. (2015). When will ‘open science’ become simply ‘science’? Genome Biology, 16(1), 101. https://doi.org/10.1186/s13059-015-0669-2

  5. [12 April 2023, 12:30-15:30] Open Peer Review


  6. [13 April 2023, 12:30-15:30] Open Source Software


  7. [19 April 2023, 12:30-15:30] Open Access


  8. [20 April 2023, 12:30-15:30] Open Metrics


  9. [27 April 2023, 12:30-15:30] Open Infrastructures


  10. [4 May 2023, 12:30-15:30] Final seminar

    • Title: What's next on Open Science: trends and opportunities for the near future
    • Abstract: Starting from the reasons why we need Open Science - in other words, what's wrong with the current scholarly communication - we'll see what's going on at international and European level, focusing on the UNESCO recommendation, the Coalition to reform research assessment, FAIR data as building blocks of the European Open Science Cloud, and the Diamond model as the future of Open Access publishing.
    • Speaker: Elena Giglia, PhD, Masters' Degree in Librarianship and Masters' Degree in Public Institutions Management, is Head of the Open Science Unit at the University of Turin. She has been part of the European Open Science network for many years, attending national and international conferences, and writing and lecturing on Open Access and Open Science. She was a member (2019-2020) of the Committee on Open Science at the Ministry for University and Research (MUR). She actively collaborates with the ICDI – Italian Computer and Data Infrastructure Competence center on Open Science, EOSC and FAIR data and with several national and international projects. She is a member of the EOSC Association Task Force Researchers Engagement and Adoption, where she represents the Research infrastructure OPERAS for Open Science in the Social Sciences and the Humanities. She serves in several Scientific Committees and Advisory Boards.

  11. [? May 2023, 9:00-13:00] Workshop


Extras

Video presentations about Open Science stuff:

Schedule

22 March 202312:30-15:30Introduction to Open Science
23 March 202312:30-15:30Reproducibility
29 March 202312:30-15:30FAIR and Open Data
30 March 202312:30-15:30Open Methodology
12 April 202312:30-15:30Open Peer Review
13 April 202312:30-15:30Open Source Software
19 April 202312:30-15:30Open Access
20 April 202312:30-15:30Open Metrics
27 April 202312:30-15:30Open Infrastructures
4 May 202312:30-15:30Final seminar

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