Alberto Zigoni’s research while affiliated with Elsevier B.V. and other places

Plateformes de partage, de réutilisation et de conservation de données, les entrepôts de données de recherche sont des infrastructures au coeur de la politique pour la science ouverte.Partage et valorisation des données de recherche propose une approche globale de ces entrepôts de données, de leurs fonctionnalités, usages, enjeux et perspectives. Il analyse le paysage des entrepôts en France, discute le concept d’un entrepôt national (avec une étude comparative de plusieurs dispositifs nationaux), décrit le répertoire international re3data et réunit six études de cas d’entrepôts modèles, publics et privés (CDS, Data INRAE, SEANOE, Nakala, Figshare, Data Mendeley). L’annexe contient plusieurs sites web et des textes de référence du ministère de l’Enseignement supérieur, de la Recherche et du CNRS.Premier ouvrage entièrement consacré à ces nouvelles plateformes, il s’adresse aux chercheurs, aux enseignants, aux étudiants et aux professionnels des données et de l’information scientifique et technique.

In this paper we aim to analyse the adoption of Current Research Information Systems (CRIS) for Research Data Management (RDM). We show how CRISs hold a key role in facilitating the management and reporting of an institution's research activities and outputs – not only do they offer extensive functionality for researchers and research administrators to effectively manage all aspects of their research information, but are also integrating more and more with specialized RDM tools, Institutional Repositories (IR), and other external systems. This paper provides an overview of how CRISs have evolved and integrated to become a crucial part of the RDM chain, including the interoperability, registration, linking, and archiving of data.

Mendeley was launched in 2008 in London by students, as a scientific social network to manage and share publications. Mendeley Data – the name of this new service – is at the same time a data repository and a search engine to find data in other repositories. Mendeley Data is about storing, sharing, finding and following research data, and this is not restricted to a single repository but encompasses more than 2000 data repositories. The main functionalities are the finding, enriching, the storing, the publishing and sharing, and the long‐term preservation of datasets, together with a search engine with references from more than 25 million datasets and with specific, value added tools for institutions and for data management and monitoring. Researchers working in a sensitive domain, if they need to store their data but do not want to show that they are working on these data, can do it on Mendeley Data.

Institutions, funding bodies, and national research organizations are pushing for more data sharing and FAIR data. Institutions typically implement data policies, frequently supported by an institutional data repository. Funders typically mandate data sharing. So where does this leave the researcher? How can researchers benefit from doing the additional work to share their data? In order to make sure that researchers and institutions get credit for sharing their data, the data needs to be tracked and attributed first. In this paper we investigated where the research data ended up for 11 research institutions, and how this data is currently tracked and attributed. Furthermore, we also analysed the gap between the research data that is currently in institutional repositories, and where their researchers truly share their data. We found that 10 out of 11 institutions have most of their public research data hosted outside of their own institution. Combined, they have 12% of their institutional research data published in the institutional data repositories. According to our data, the typical institution had 5% of their research data (median) published in the institutional repository, but there were 4 universities for which it was 10% or higher. By combining existing data-to-article graphs with existing article-to- researcher and article-to-institution graphs it becomes possible to increase tracking of public research data and therefore the visibility of researchers sharing their data typically by 17x. The tracking algorithm that was used to perform analysis and report on potential improvements has subsequently been implemented as a standard method in the Mendeley Data Monitor product. The improvement is most likely an under-estimate because, while the recall for datasets in institutional repositories is 100%, that is not the case for datasets published outside the institutions, so there are even more datasets still to be discovered.