Research Data Services in European Academic Research Libraries

Authors : Carol Tenopir, Sanna Talja, Wolfram Horstmann, Elina Late, Dane Hughes, Danielle Pollock, Birgit Schmidt, Lynn Baird, Robert J. Sandusky, Suzie Allard

Research data is an essential part of the scholarly record, and management of research data is increasingly seen as an important role for academic libraries.

This article presents the results of a survey of directors of the Association of European Research Libraries (LIBER) academic member libraries to discover what types of research data services (RDS) are being offered by European academic research libraries and what services are planned for the future.

Overall, the survey found that library directors strongly agree on the importance of RDS. As was found in earlier studies of academic libraries in North America, more European libraries are currently offering or are planning to offer consultative or reference RDS than technical or hands-on RDS.

The majority of libraries provide support for training in skills related to RDS for their staff members. Almost all libraries collaborate with other organizations inside their institutions or with outside institutions in order to offer or develop policy related to RDS.

We discuss the implications of the current state of RDS in European academic research libraries, and offer directions for future research.

URL : Research Data Services in European Academic Research Libraries

DOI : http://doi.org/10.18352/lq.10180

Managing research data at an academic library in a developing country

Authors : Shamin Renwick, Marsha Winter, Michelle Gill

Managing research data has become an issue for many universities. In the Caribbean, the St Augustine Campus Libraries at the University of the West Indies are keenly aware of the need to support researchers in this regard.

The objectives of this study were to identify current practices in managing research data on the campus and to determine a possible role for the Campus Libraries. A pilot study of 100 researchers on the campus was conducted. A

nalysis of the 65 valid responses revealed that while researchers owned data sets they had little knowledge or experience in managing such. This low level of awareness is instructive and validates a role for the Campus Libraries to play in supporting researchers on campus.

The Campus Libraries need to sensitize researchers about what data planning and managing research data entail as well as provide technical assistance with actual data storage.

URL : http://journals.sagepub.com/doi/full/10.1177/0340035216688703

A l’épreuve de l’hétérogénéité : données de recherche et interdisciplinarité : L’exemple du projet européen IPERION-CH

Auteur/Author : Marie Puren

Avec la mise en place de grandes infrastructures de recherche en sciences du patrimoine comme E-RIHS, on rassemble des acteurs divers, issus à la fois des sciences humaines et sociales et des sciences expérimentales. Le paléontologue croise l’historien de l’art, et le physicien collabore avec le restaurateur.

Dans ce cadre, la gestion des données de la recherche est un véritable défi, car elle doit rassembler, valoriser et rendre accessibles des données produites par des protagonistes très différents, utilisant des méthodes elles aussi très différentes. Comment en effet gérer et échanger à la fois des données d’expériences, des images numérisées et des rapports de restauration ?

Le cycle de vie des données de la recherche, de leur création à leur diffusion en passant par leur analyse, au sein de cette communauté interdisciplinaire interroge la définition même de ce type de données, et nous amène à questionner les pratiques autour de celles-ci.

URL : https://hal.archives-ouvertes.fr/hal-01408951/

Research data management in social sciences and humanities: A survey at the University of Lille (France)

Authors : Joachim Schöpfel, Hélène Prost

The paper presents results from a campus-wide survey at the University of Lille (France) on research data management in social sciences and humanities.

The survey received 270 responses, equivalent to 15% of the whole sample of scientists, scholars, PhD students, administrative and technical staff (research management, technical support services); all disciplines were represented.

The responses show a wide variety of practice and usage. The results are discussed regarding job status and disciplines and compared to other surveys. Four groups can be distinguished, i.e. pioneers (20-25%), motivated (25-30%), unaware (30%) and reluctant (5-10%).

Finally, the next steps to improve the research data management on the campus are presented.

URL : Research data management in social sciences and humanities: A survey at the University of Lille (France)

Alternative location : http://libreas.eu/ausgabe29/09schoepfel/

Research Data in Current Research Information Systems

Authors : Joachim Schöpfel, Hélène Prost,Violaine Rebouillat

The paper provides an overview of recent research and publications on the integration of research data in Current Research Information Systems (CRIS) and addresses three related issues, i.e. the object of evaluation, identifier schemes and conservation.

Our focus is on social sciences and humanities. As research data gradually become a crucial topic of scientific communication and evaluation, current research information systems must be able to consider and manage the great variety and granularity levels of data as sources and results of scientific research.

More empirical and moreover conceptual work is needed to increase our understanding of the reality of research data and the way they can and should be used for the needs and objectives of research evaluation.

The paper contributes to the debate on the evaluation of research data, especially in the environment of open science and open data, and will be helpful in implementing CRIS and research data policies.

URL : http://archivesic.ccsd.cnrs.fr/sic_01331537

Cloud-Based Big Data Management and Analytics for Scholarly Resources: Current Trends, Challenges and Scope for Future Research

Authors : Samiya Khan, Kashish A. Shakil, Mansaf Alam

With the shifting focus of organizations and governments towards digitization of academic and technical documents, there has been an increasing need to use this reserve of scholarly documents for developing applications that can facilitate and aid in better management of research.

In addition to this, the evolving nature of research problems has made them essentially interdisciplinary. As a result, there is a growing need for scholarly applications like collaborator discovery, expert finding and research recommendation systems.

This research paper reviews the current trends and identifies the challenges existing in the architecture, services and applications of big scholarly data platform with a specific focus on directions for future research.

URL : https://arxiv.org/abs/1606.01808

Revisiting the Data Lifecycle with Big Data Curation

Author : Line Pouchard

As science becomes more data-intensive and collaborative, researchers increasingly use larger and more complex data to answer research questions.

The capacity of storage infrastructure, the increased sophistication and deployment of sensors, the ubiquitous availability of computer clusters, the development of new analysis techniques, and larger collaborations allow researchers to address grand societal challenges in a way that is unprecedented.

In parallel, research data repositories have been built to host research data in response to the requirements of sponsors that research data be publicly available. Libraries are re-inventing themselves to respond to a growing demand to manage, store, curate and preserve the data produced in the course of publicly funded research.

As librarians and data managers are developing the tools and knowledge they need to meet these new expectations, they inevitably encounter conversations around Big Data. This paper explores definitions of Big Data that have coalesced in the last decade around four commonly mentioned characteristics: volume, variety, velocity, and veracity.

We highlight the issues associated with each characteristic, particularly their impact on data management and curation. We use the methodological framework of the data life cycle model, assessing two models developed in the context of Big Data projects and find them lacking.

We propose a Big Data life cycle model that includes activities focused on Big Data and more closely integrates curation with the research life cycle. These activities include planning, acquiring, preparing, analyzing, preserving, and discovering, with describing the data and assuring quality being an integral part of each activity.

We discuss the relationship between institutional data curation repositories and new long-term data resources associated with high performance computing centers, and reproducibility in computational science.

We apply this model by mapping the four characteristics of Big Data outlined above to each of the activities in the model. This mapping produces a set of questions that practitioners should be asking in a Big Data project

URL : Revisiting the Data Lifecycle with Big Data Curation

Alternative location : http://www.ijdc.net/index.php/ijdc/article/view/10.2.176