Abstract
Data science is an interdisciplinary field that extracts value from data. One of the relevant areas is its application in research in order to define requirements of the data life cycle. Thus, data should be managed before, during, and after a research project completion. A robust data management plan (DMP) is a relevant and useful instrument to establish data-related requirements. In this context, this paper aims at highlighting some characteristics associated to research data management. To conduct this study peer-reviewed literature and secondary data are methodologically employed to fulfil the paper objective. The results discuss the development of DMP, provide some examples of documents and a check list related to data management, and present some recommendations for developing a suitable data management plan from the literature. The data management plan is one of the important instruments that should be considered with care when designing and applying it. Future work may consider providing a structure and guidance for research students in the field of industrial engineering as a valuable avenue to explore.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Michener, W.F.: Ten simple rules for creating a good data management plan. PLoS Comput. Biol. 11(10), e1004525 (2015). https://doi.org/10.1371/journal.pcbi.1004525
Davis, H.M., Cross, W.M.: Using a data management plan review service as a training ground for librarians. J. Librariansh. Sch. Commun. 3(2), eP1243 (2015). https://doi.org/10.7710/2162-3309.1243
Antell, K., Foote, J.B., Turner, J., Shults, B.: Dealing with data: science librarians’ participation in data management at an association of research libraries institutions. Coll. Res. Libr. 75(4), 557–574 (2014). https://doi.org/10.5860/crl.75.4.557
Surkis, A., Read, K.: Research data management. J. Med. Libr. Assoc. JMLA 103(3), 154–156 (2015). https://doi.org/10.3163/1536-5050.103.3.011
Cox, A.M., Tam, W.W.T.: A critical analysis of lifecycle models of the research process and research data management. Aslib J. Inf. Manage. 70(2), 142–157 (2018). https://doi.org/10.1108/AJIM-11-2017-0251
Vieira, R., Ferreira, F., Barateiro, J., Borbinha, J.: Data management with risk management in engineering and science projects. New Rev. Inf. Netw. 19(2), 49–66 (2014). https://doi.org/10.1080/13614576.2014.918519
Anonymous: Nature editorial - making plans. Nature 555(7696), 286 (2018)
Mannheimer, S.: Toward a better data management plan: the impact of DMPs on grant funded research practices. J. eSci. Librariansh. 7(3), 5 (2018). https://doi.org/10.7191/jeslib.2018.1155
Bellgard, M.I.: ERDMAS: an exemplar-driven institutional research data management and analysis strategy. Int. J. Inf. Manage. 50, 337–340 (2020). https://doi.org/10.1016/j.ijinfomgt.2019.08.009
Wright, A.: Electronic resources for developing data management skills and data management plans. J. Electron. Resour. Med. Libr. 13(1), 43–48 (2016). https://doi.org/10.1080/15424065.2016.1146640
Holles, J.H., Schmidt, M.L.: Graduate research data management course content: teaching the Data Management Plan (DMP). In: 2018 ASEE Annual Conference and Exposition (2018)
Reilly, M., Dryden, A.R.: Building an online data management plan tool. J. Librariansh. Sch. Commun. 1(3), eP1066 (2013). https://doi.org/10.7710/2162-3309.1066
Van Loon, J.E., Akers, K.G., Hudson, C., Sarkozy, A.: Quality evaluation of data management plans at a research university. IFLA J. 43(1), 98–104 (2017). https://doi.org/10.1177/0340035216682041
European Commission – European Union. https://ec.europa.eu/research/participants/docs/h2020-funding-guide/cross-cutting-issues/open-access-data-management/data-management_en.htm. Accessed 11 Jan 2020
Willaert, T., Cottyn, J., Kenens, U., Vandendriessche, T., Verbeke, D., Wyns, R.: Research data management and the evolutions of scholarship: policy, infrastructure and data literacy at KU Leuven. LIBER Q. 29, 1–19 (2019). https://doi.org/10.18352/lq.20272
Elsevier. https://researcheracademy.elsevier.com/research-preparation/research-data-management. Accessed 11 Jan 2020
RDMLA – RDMLA. https://rdmla.github.io/about/. Accessed 11 Jan 2020
Wilkinson, M.D., et al.: The FAIR guiding principles for scientific data management and stewardship. Sci. Data 3, 160018 (2016). https://doi.org/10.1038/sdata.2016.18
Booth, A., Sutton, A., Papaioannou, D.: Systematic approaches to a successful literature review. Sage Publications Ltd., Thousand Oaks (2012)
European Commission. https://ec.europa.eu/research/participants/docs/h2020-funding-guide/cross-cutting-issues/open-access-data-management/data-management_en.htm. Accessed 9 Jan 2020
Digital Curation Centre –DCC. http://www.dcc.ac.uk/. Accessed 8 Jan 2020
Digital Curation Centre –DCC. http://www.dcc.ac.uk/sites/default/files/documents/resource/DMP/DMP-checklist-flyer.pdf. Accessed 6 Jan 2020
University of Aveiro. https://www.ua.pt/pt/investigacao. Accessed 9 Jan 2020
European Commission. https://ec.europa.eu/programmes/erasmus-plus/about_en. Accessed 9 Jan 2020
Digital Curation Centre – DCC. http://www.dcc.ac.uk/sites/default/files/documents/resource/DMP/DMP_Checklist_2013.pdf. Accessed 6 Jan 2020
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2020 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
About this paper
Cite this paper
Cauchick-Miguel, P.A., Moro, S.R., Rivera, R., Amorim, M. (2020). Data Management Plan in Research: Characteristics and Development. In: Mugnaini, R. (eds) Data and Information in Online Environments. DIONE 2020. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 319. Springer, Cham. https://doi.org/10.1007/978-3-030-50072-6_1
Download citation
DOI: https://doi.org/10.1007/978-3-030-50072-6_1
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-50071-9
Online ISBN: 978-3-030-50072-6
eBook Packages: Computer ScienceComputer Science (R0)