Tous les articles par Digital library

Ontologies in CLARIAH: Towards Interoperability in History, Language and Media

Meroño-Peñuela, Albert [et al.]. Ontologies in CLARIAH: Towards Interoperability in History, Language and Media. [Submitted on 6 Apr 2020 (v1), last revised 31 Jul 2020 (this version, v2)]. arXiv:2004.02845v2

One of the most important goals of digital humanities is to provide researchers with data and tools for new research questions, either by increasing the scale of scholarly studies, linking existing databases, or improving the accessibility of data. Here, the FAIR principles provide a useful framework as these state that data needs to be: Findable, as they are often scattered among various sources; Accessible, since some might be offline or behind paywalls; Interoperable, thus using standard knowledge representation formats and shared vocabularies; and Reusable, through adequate licensing and permissions. Integrating data from diverse humanities domains is not trivial, research questions such as « was economic wealth equally distributed in the 18th century? », or « what are narratives constructed around disruptive media events? ») and preparation phases (e.g. data collection, knowledge organisation, cleaning) of scholars need to be taken into account. In this chapter, we describe the ontologies and tools developed and integrated in the Dutch national project CLARIAH to address these issues across datasets from three fundamental domains or « pillars » of the humanities (linguistics, social and economic history, and media studies) that have paradigmatic data representations (textual corpora, structured data, and multimedia). We summarise the lessons learnt from using such ontologies and tools in these domains from a generalisation and reusability perspective.

Source : arXiv:2004.02845v2

Machine Learning + Libraries: A Report on the State of the Field

Cordell, Ryan, LC Labs. Machine Learning + Libraries: A Report on the State of the Field. 2020-07-14. https://labs.loc.gov/static/labs/work/reports/Cordell-LOC-ML-report.pdf

[…] The goal was to provide a wide-ranging view into the current applications and practices of applying machine learning in libraries and other cultural heritage organizations. It draws on and references the report by the Project Aida team included below and on the outcomes from the Machine Learning + Libraries Summit hosted by LC Labs in September 2019.

Source : https://labs.loc.gov/static/labs/work/reports/Cordell-LOC-ML-report.pdf

Penser local : développer une politique de données sur un campus SHS

Schöpfel Joachim. Penser local : développer une politique de données sur un campus SHS. Revue ouverte d’ingénierie des systèmes d’information, vol.1, n°1. 2020/03/10. https://www.openscience.fr/Penser-local

Dans le cadre du Plan national pour la science ouverte, la structuration et le partage des données de recherche font désormais partie des priorités de la politique scientifique de la France. Chaque établissement et chaque organisme scientifique doit se doter d’une politique de la science ouverte et mettre en place un ensemble de services et dispositifs pour la gestion des données de la recherche. A partir d’enquêtes sur le terrain, l’article propose une feuille de route pour la mise en oeuvre d’une telle politique sur un campus universitaire en sciences humaines et sociales. Dix principes indiquent des pistes pour la gouvernance et le pilotage de cette politique, pour déterminer les priorités de développement et d’investissements, et pour faire le lien avec les infrastructures de recherche, dont notamment Huma-Num. Il s’agit d’une démarche bottom-up, qui met l’accent sur les pratiques et besoins des chercheurs et qui place les chercheurs au coeur d’une politique institutionnelle dans le domaine des données de recherche.

Source : https://www.openscience.fr/Penser-local

 

Analyse des besoins du projet Visa TM

Kettani, Fabienne (coord.). Analyse du besoin : Visa TM, Vers une infrastructure de services avancés de text mining. 2017/2019.  (Etude). 2019-10-31. https://visatm.inist.fr/wp-content/uploads/2019/11/Etude_Analyse_du_besoin.pdf

Le projet Visa TM vise à étudier les conditions de mise à disposition de services de fouille de textes pour les chercheurs français. En effet, la fouille de textes est devenue ces dernières années un sujet d’importance dans le sillage du mouvement pour la science ouverte mais si ses enjeux sont importants pour la recherche et si le projet européen OpenMinTeD a posé les jalons d’une première approche en proposant une infrastructure dédiée, il reste à initier une démarche similaire à un niveau national.

Source : https://visatm.inist.fr/wp-content/uploads/2019/11/Etude_Analyse_du_besoin.pdf

Understanding researcher needs and raising the profile of library research support

Nickels, Colin, and Hilary Davis. 2020. “Understanding Researcher Needs and Raising the Profile of Library Research Support”. Insights 33 (1): 4. DOI: http://doi.org/10.1629/uksg.493

Researchers at North Carolina State University expect little to no difficulty in discerning how their Library can support their work. At the same time, librarians repeatedly find that researchers are unaware of what our Library has to offer. Within this context, we embarked on a two-year study to help inform the development of outreach strategies to enable new research engagement opportunities that will scale and, at the same time, help us transform our model of research support strategies and engagement. We interviewed both librarians and researchers to gain an understanding of researcher needs from both perspectives. The results of the interviews provided a solid grounding for building our awareness of researchers’ behaviors, expectations and workflows as well as presenting a unique picture of both unmet and unarticulated needs. In this article we summarize our results with a specific focus on findings from the researcher interviews. We share our recommendations for evolving library research support and enhancing outreach strategies to provide an easier starting point for different types of researchers to discover relevant research assets provided by libraries such as ours.

Source : http://doi.org/10.1629/uksg.493

L’avenir de l’édition scientifique en France et la science ouverte : Comment favoriser le dialogue ? Comment organiser la consultation ?

Mérindol, Jean-Yves. L’avenir de l’édition scientifique en France et la science ouverte : Comment favoriser le dialogue ? Comment organiser la consultation ? 24 janvier 2020.  Rapport remis à Frédérique VIDAL Ministre de l’enseignement supérieur, de la recherche et de l’innovation. https://www.enseignementsup-recherche.gouv.fr/cid148896/les-pouvoirs-publics-et-l-edition-scientifique-en-france.html

Depuis un peu plus de trois cents ans, les découvertes scientifiques sont rendues publiques par la publication d’articles dans des revues spécialisées ou via des monographies savantes. Les éditeurs
– en France comme à l’étranger – ont joué ici un rôle historique fondamental.
L’accès au savoir et à la culture s’est considérablement modifié ces trente dernières années sous l’influence cumulée de changements technologiques (numérisation, réseaux, web) et sociaux
(développement mondial de la science).

Source : https://www.enseignementsup-recherche.gouv.fr/cid148896/les-pouvoirs-publics-et-l-edition-scientifique-en-france.html

The Use of Social Networking Sites for Scholarly Communication by Emergent Social Scientists: An Affordances Approach

Manco, Alejandra The Use of Social Networking Sites for Scholarly Communication by Emergent Social Scientists: An Affordances Approach. Young Information Scientist, 2019, vol. 4, pp. 17-30. https://doi.org/10.25365/yis-2019-4-2

Objectives — This study aims to explore how early career social sciences researchers and PhD social science students use social networking sites for science communication in Brazil. The central research question is what are the motives and rationale of the researchers for using social networking sites for academic communication. Two sub-questions arise from here: How do these reasons relate to scientific practices and the academic system of Brazil? And which are the main affordances perceived by researchers? Methods — This study is empirically oriented, building upon case studies in Brazil. It makes use of a review of affordances of social media platforms, applying the review to the study of social media as a theoretical foundation. The methodological approach is qualitative, using both interviews and netnography as research methods. Results — The primary motivations for using different Social Networking Sites (SNSs) are all related to connectivity: communication with peers—and, to a lesser degree, to the public and the research participants, updating themselves about their research interests, dissemination of research, checking availability of papers, self-branding, and participation in interest groups. These motivations translate into cross-posting practices and integrated communication strategies—combining online and offline elements—on the different platforms. The main affordances perceived by researchers in this study were related to social affordances or, in other words, social capital processes: availability, scalability, visibility, and multimediality. Conclusions — SNSs have not yet replaced traditional communication channels in the case of early career social science researchers because the academic evaluation systems do yet not include them. The use of SNSs changes according to the affordances early career social sciences researchers see (or fail to see) for each platform. This study identified observable differences according to a researcher’s field of expertise and level of comfort with particular platforms.

Source : https://doi.org/10.25365/yis-2019-4-2

How Frequently are Articles in Predatory Open Access Journals Cited

Björk, Bo-Christer, Sari Kanto-Karvonen, et J. Tuomas Harviainen. « How Frequently are Articles in Predatory Open Access Journals Cited ». arXiv:1912.10228 [cs], 21 décembre 2019. http://arxiv.org/abs/1912.10228.
Predatory journals are Open Access journals of highly questionable scientific quality. Such journals pretend to use peer review for quality assurance, and spam academics with requests for submissions, in order to collect author payments. In recent years predatory journals have received a lot of negative media. While much has been said about the harm that such journals cause to academic publishing in general, an overlooked aspect is how much articles in such journals are actually read and in particular cited, that is if they have any significant impact on the research in their fields. Other studies have already demonstrated that only some of the articles in predatory journals contain faulty and directly harmful results, while a lot of the articles present mediocre and poorly reported studies. We studied citation statistics over a five-year period in Google Scholar for 250 random articles published in such journals in 2014, and found an average of 2,6 citations per article and that 60 % of the articles had no citations at all. For comparison a random sample of articles published in the approximately 25,000 peer reviewed journals included in the Scopus index had an average of 18,1 citations in the same period with only 9 % receiving no citations. We conclude that articles published in predatory journals have little scientific impact.

Publishers’ Responsibilities in Promoting Data Quality and Reproducibility

Hrynaszkiewicz I. (2019) Publishers’ Responsibilities in Promoting Data Quality and Reproducibility. In: . Handbook of Experimental Pharmacology. Springer, Berlin, Heidelberg. https://doi.org/10.1007/164_2019_290

Scholarly publishers can help to increase data quality and reproducible research by promoting transparency and openness. Increasing transparency can be achieved by publishers in six key areas: (1) understanding researchers’ problems and motivations, by conducting and responding to the findings of surveys; (2) raising awareness of issues and encouraging behavioural and cultural change, by introducing consistent journal policies on sharing research data, code and materials; (3) improving the quality and objectivity of the peer-review process by implementing reporting guidelines and checklists and using technology to identify misconduct; (4) improving scholarly communication infrastructure with journals that publish all scientifically sound research, promoting study registration, partnering with data repositories and providing services that improve data sharing and data curation; (5) increasing incentives for practising open research with data journals and software journals and implementing data citation and badges for transparency; and (6) making research communication more open and accessible, with open-access publishing options, permitting text and data mining and sharing publisher data and metadata and through industry and community collaboration. This chapter describes practical approaches being taken by publishers, in these six areas, their progress and effectiveness and the implications for researchers publishing their work.

Source : https://doi.org/10.1007/164_2019_290

Open Data Metrics: Lighting the Fire (Version 1)

Lowenberg, Daniella, Chodacki, John, Fenner, Martin, Kemp, Jennifer, & Jones, Matthew B. (2019). Open Data Metrics: Lighting the Fire (Version 1). Zenodo. http://doi.org/10.5281/zenodo.3525349

Research data is at the center of science. To realize the benefits of open data sharing practices and the impact of research data, we need a practical implementation of tools and community buy-in that will aid in the development of data metrics. We will benefit the most if our community-developed standards, tools, and services are guided by a shared direction and vision for a future of open, transparent, and trusted data metrics.

Approaches towards this future state must remain researcher-focused, have easily understandable motivations, and be easily implementable. In this book, we describe the journey towards open data metrics, prompting community discussion and providing implementation examples along the way.

FAIR Data Reuse : the Path through Data Citation

Groth, Paul, Helena Cousijn, Tim Clark, et Carole Goble. « FAIR Data Reuse – the Path through Data Citation ». Data Intelligence, 1 novembre 2019, 78‑86. https://doi.org/10.1162/dint_a_00030.

One of the key goals of the FAIR guiding principles is defined by its final principle – to optimize data sets for reuse by both humans and machines. To do so, data providers need to implement and support consistent machine readable metadata to describe their data sets. This can seem like a daunting task for data providers, whether it is determining what level of detail should be provided in the provenance metadata or figuring out what common shared vocabularies should be used. Additionally, for existing data sets it is often unclear what steps should be taken to enable maximal, appropriate reuse. Data citation already plays an important role in making data findable and accessible, providing persistent and unique identifiers plus metadata on over 16 million data sets. In this paper, we discuss how data citation and its underlying infrastructures, in particular associated metadata, provide an important pathway for enabling FAIR data reuse.

LIBER Webinar: Finding and Reusing Research Data

Gregory, Kathleen. LIBER Webinar: Finding and Reusing Research Data. 14/11/2019. https://libereurope.eu/blog/2019/11/18/webinar-video-data-curation-from-a-practical-perspective/

Sharing research data is a practice that is increasingly encouraged by funders, institutions, and research communities.

Policies, tools and training programmes are being developed to assist researchers and data providers to make data available in a way that optimizes data findability, accessibility, interoperability and reusability (i.e. according to the FAIR principles). One of the promises driving both data sharing and policy development is that shared data can and will be discovered and reused; but are users (researchers, librarians, students) discovering this data? And if they are finding them, (how) are they reusing them?

In this webinar, organised by LIBER’s Research Data Management Working Group, Kathleen Gregory presented an overview of recent research investigating how researchers and librarians engage in practices of finding, understanding and reusing research data. She provided tips for finding research data and an opportunity for attendees to consider what this research means for developing services at their own organizations.

Gregory, Kathleen. LIBER Webinar: Finding and Reusing Research Data. 14/11/2019. https://libereurope.eu/blog/2019/11/18/webinar-video-data-curation-from-a-practical-perspective/

Cataloguing, knowledge and power

Cridford, Thomas J. Cataloguing, knowledge and power. Journal of Radical Librarianship, 2019, vol. 5, pp. 61-83. http://eprints.rclis.org/39172/

This paper seeks to unpick the changing perceptions of the concepts contained in its title and investigate some of the relationships between them. It does this by exploring the history of modern cataloguing from the mid 1800s to the present day. It is argued that over the nineteenth and twentieth centuries cataloguing developments took place predominantly in the library world and, understood through the principles of European Enlightenment thought, catalogues were perceived to provide the public with access to external knowledge and thus empower them. It then identifies technological, cultural and ideological developments in the twentieth century, notably the rise of ‘postmodernism’, as challenges to both the primacy of library catalogues and the tradition of Enlightenment thought within which they were conceived. Finally, it argues that corporate digital companies are now at the forefront of cataloguing and explores the way in which the public have become the subject of these catalogues. Drawing upon Foucauldian theory, it is suggested that rather than allowing knowledge and power to flow to the public these catalogues enable corporate and government bodies to hold it over the public and use it to influence their lives in unprecedented ways.

Source : http://eprints.rclis.org/39172/

The Definition of Reuse

van de Sandt, Stephanie, et al. 2019. « The Definition of Reuse ». Data Science Journal, 18: 22, pp. 1–19. DOI.org (Crossref), doi:10.5334/dsj-2019-022

The ability to reuse research data is now considered a key benefit for the wider research community. Researchers of all disciplines are confronted with the pressure to share their research data so that it can be reused. The demand for data use and reuse has implications on how we document, publish and share research in the first place, and, perhaps most importantly, it affects how we measure the impact of research, which is commonly a measurement of its use and reuse. It is surprising that research communities, policy makers, etc. have not clearly defined what use and reuse is yet.

We postulate that a clear definition of use and reuse is needed to establish better metrics for a comprehensive scholarly record of individuals, institutions, organizations, etc. Hence, this article presents a first definition of reuse of research data. Characteristics of reuse are identified by examining the etymology of the term and the analysis of the current discourse, leading to a range of reuse scenarios that show the complexity of today’s research landscape, which has been moving towards a data-driven approach. The analysis underlines that there is no reason to distinguish use and reuse. We discuss what that means for possible new metrics that attempt to cover Open Science practices more comprehensively. We hope that the resulting definition will enable a better and more refined strategy for Open Science.

Source : 10.5334/dsj-2019-022

 

 

Lost or found? Discovering data needed for research

Gregory, Kathleen, et al. « Lost or found? Discovering data needed for research ». arXiv:1909.00464 [cs], septembre 2019. arXiv.org, http://arxiv.org/abs/1909.00464.

Finding or discovering data is a necessary precursor to being able to reuse data, although relatively little large-scale empirical evidence exists about how researchers discover, make sense of and (re)use data for research. This study presents evidence from the largest known survey investigating how researchers discover and use data that they do not create themselves. We examine the data needs and discovery strategies of respondents, propose a typology for data (re)use and probe the role of social interactions and other research practices in data discovery, with the aim of informing the design of community-centric solutions and policies.

Source : http://arxiv.org/abs/1909.00464.