In the recent trend of data-intensive science, data publication is essential and institutions have to promote it with the researchers. For the past decade, institutional repositories have been widely established for publications, and the motivations for deposit are well established. The situation is quite different for data, as we argue on the basis of a 5-year experience with research data management at the University of Porto. We address research data management from a disciplined yet flexible point of view, focusing on domain-specific metadata models embedded in intuitive tools, to make it easier for researchers to publish their datasets. We use preliminary data from a recent experiment in data publishing to identify motivators and deterrents for data publishing.
CITATION STYLE
Ribeiro, C., da Silva, J. R., Castro, J. A., Amorim, R. C., & Fortuna, P. (2015). Motivators and deterrents for data description and publication: Preliminary results. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 9416, pp. 512–516). Springer Verlag. https://doi.org/10.1007/978-3-319-26138-6_55
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