scholarly journals On a Quest for Cultural Change - Surveying Research Data Management Practices at Delft University of Technology

2019 ◽  
Author(s):  
Heather Andrews ◽  
Marta Teperek ◽  
Jasper van Dijck ◽  
Kees den Heijer ◽  
Robbert Eggermont ◽  
...  
Keyword(s):  
Data Management ◽  
Management Practices ◽  
Management Training ◽  
Research Data ◽  
Data Repositories ◽  
Automatic Data ◽  
Awareness Campaigns ◽  
Research Data Management ◽  
University Of Technology ◽  
Data Stewardship

The Data Stewardship project is a new initiative from the Delft University of Technology (TU Delft) in the Netherlands. Its aim is to create mature working practices and policies regarding research data management across all TU Delft faculties. The novelty of this project relies on having a dedicated person, the so-called ‘Data Steward’, embedded in each faculty to approach research data management from a more discipline-specific perspective. It is within this framework that a research data management survey was carried out at the faculties that had a Data Steward in place by July 2018. The goal was to get an overview of the general data management practices, and use its results as a benchmark for the project. The total response rate was 11 to 37% depending on the faculty. Overall, the results show similar trends in all faculties, and indicate lack of awareness regarding different data management topics such as automatic data backups, data ownership, relevance of data management plans, awareness of FAIR data principles and usage of research data repositories. The results also show great interest towards data management, as more than ~80% of the respondents in each faculty claimed to be interested in data management training and wished to see the summary of survey results. Thus, the survey helped identified the topics the Data Stewardship project is currently focusing on, by carrying out awareness campaigns and providing training at both university and faculty levels.

scholarly journals On a Quest for Cultural Change - Surveying Research Data Management Practices at Delft University of Technology

2019 ◽  
Vol 29 (1) ◽  
pp. 1 ◽  
Author(s):  
Heather Andrews Mancilla ◽  
Marta Teperek ◽  
Jasper Van Dijck ◽  
Kees Den Heijer ◽  
Robbert Eggermont ◽  
...  
Keyword(s):  
Data Management ◽  
Cultural Change ◽  
Management Practices ◽  
Research Data ◽  
Research Data Management ◽  
University Of Technology

scholarly journals Playing Well on the Data FAIRground: Initiatives and Infrastructure in Research Data Management

2019 ◽  
Vol 1 (4) ◽  
pp. 350-367 ◽  
Author(s):  
Danielle Descoteaux ◽  
Chiara Farinelli ◽  
Marina Soares e Silva ◽  
Anita de Waard
Keyword(s):  
Data Management ◽  
Management Practices ◽  
Research Data ◽  
Current Status ◽  
Data Repositories ◽  
Data Preservation ◽  
Management Platform ◽  
Research Data Management ◽  
Future Goals ◽  
External Data

Over the past five years, Elsevier has focused on implementing FAIR and best practices in data management, from data preservation through reuse. In this paper we describe a series of efforts undertaken in this time to support proper data management practices. In particular, we discuss our journal data policies and their implementation, the current status and future goals for the research data management platform Mendeley Data, and clear and persistent linkages to individual data sets stored on external data repositories from corresponding published papers through partnership with Scholix. Early analysis of our data policies implementation confirms significant disparities at the subject level regarding data sharing practices, with most uptake within disciplines of Physical Sciences. Future directions at Elsevier include implementing better discoverability of linked data within an article and incorporating research data usage metrics.

scholarly journals NFDI4Chem - Towards a National Research Data Infrastructure for Chemistry in Germany

2020 ◽  
Vol 6 ◽  
Author(s):  
Christoph Steinbeck ◽  
Oliver Koepler ◽  
Felix Bach ◽  
Sonja Herres-Pawlis ◽  
Nicole Jung ◽  
...  
Keyword(s):  
Data Management ◽  
Data Science ◽  
Open Data ◽  
Research Data ◽  
Data Standards ◽  
Data Repositories ◽  
Data Infrastructure ◽  
Research Data Management ◽  
Wide Range ◽  
Chemistry Community

The vision of NFDI4Chem is the digitalisation of all key steps in chemical research to support scientists in their efforts to collect, store, process, analyse, disclose and re-use research data. Measures to promote Open Science and Research Data Management (RDM) in agreement with the FAIR data principles are fundamental aims of NFDI4Chem to serve the chemistry community with a holistic concept for access to research data. To this end, the overarching objective is the development and maintenance of a national research data infrastructure for the research domain of chemistry in Germany, and to enable innovative and easy to use services and novel scientific approaches based on re-use of research data. NFDI4Chem intends to represent all disciplines of chemistry in academia. We aim to collaborate closely with thematically related consortia. In the initial phase, NFDI4Chem focuses on data related to molecules and reactions including data for their experimental and theoretical characterisation. This overarching goal is achieved by working towards a number of key objectives: Key Objective 1: Establish a virtual environment of federated repositories for storing, disclosing, searching and re-using research data across distributed data sources. Connect existing data repositories and, based on a requirements analysis, establish domain-specific research data repositories for the national research community, and link them to international repositories. Key Objective 2: Initiate international community processes to establish minimum information (MI) standards for data and machine-readable metadata as well as open data standards in key areas of chemistry. Identify and recommend open data standards in key areas of chemistry, in order to support the FAIR principles for research data. Finally, develop standards, if there is a lack. Key Objective 3: Foster cultural and digital change towards Smart Laboratory Environments by promoting the use of digital tools in all stages of research and promote subsequent Research Data Management (RDM) at all levels of academia, beginning in undergraduate studies curricula. Key Objective 4: Engage with the chemistry community in Germany through a wide range of measures to create awareness for and foster the adoption of FAIR data management. Initiate processes to integrate RDM and data science into curricula. Offer a wide range of training opportunities for researchers. Key Objective 5: Explore synergies with other consortia and promote cross-cutting development within the NFDI. Key Objective 6: Provide a legally reliable framework of policies and guidelines for FAIR and open RDM.

scholarly journals VARIABILITY IN CLINICAL RESEARCH DATA MANAGEMENT PRACTICES: LESSONS FROM THE MALARIA COMMUNITY

2017 ◽  
Vol 2 (Suppl 2) ◽  
pp. A19.1-A19
Author(s):  
Amélie Julé ◽  
Hazel Ashurst ◽  
Laura Merson ◽  
Piero Olliaro ◽  
Vicki Marsh ◽  
...  
Keyword(s):  
Clinical Research ◽  
Data Management ◽  
Management Practices ◽  
Research Data ◽  
Research Data Management ◽  
Clinical Research Data

scholarly journals Challenges and Practices of Research Data Management in Selected Iraq Universities

2019 ◽  
Vol 39 (06) ◽  
pp. 308-314
Author(s):  
Mahdi Salah Mohammed ◽  
Rafea Ibrahim
Keyword(s):  
Data Management ◽  
Research Data ◽  
Faculty Members ◽  
Data Repositories ◽  
Postgraduate Students ◽  
Research Data Management ◽  
Research Findings ◽  
Management Policies ◽  
Research Organisations

Research emphasises the fundamental role of research data management (RDM) in enhancing academic and scientific research. This paper intended to examine RDM in Iraqi Universities, identify the current challenges of RDM and propose influential RDM practices. Data collection employed a self-administered questionnaires distributed to 155 postgraduate students and 20 faculty members from five universities in Iraq. Research findings revealed that there is a lack of proper RDM. Postgraduate students and researchers were managing their own research data. Main challenges of maintaining a good RDM involve lack of guidelines on effective RDM practices, insufficient of adequate human resources, technological obsolescence, insecure and inefficient infrastructure, lack of financial resources, absence of research data management policies and lack of support by institutional authorities and researchers negatively influenced on research data management. Postgraduate students and researchers recommend building research data repositories and collaboration with other universities and research organisations.

scholarly journals Research Data Management within the 4TU Research Centres

2018 ◽  
Author(s):  
Maria J. Cruz ◽  
Alastair Dunning
Keyword(s):  
Data Management ◽  
Management Practices ◽  
Qualitative Interviews ◽  
Research Data ◽  
Research Data Management ◽  
Research Centres

Survey of research data management practices and attitudes within the 4TU Research Centres based on qualitative interviews with the Centres' Scientific Directors.

scholarly journals Disciplinary differences in faculty research data management practices and perspectives

2013 ◽  
Vol 8 (2) ◽  
pp. 5-26 ◽  
Author(s):  
Katherine G. Akers ◽  
Jennifer Doty
Keyword(s):  
Data Management ◽  
Research University ◽  
Management Practices ◽  
Research Data ◽  
Data Curation ◽  
Academic Librarians ◽  
Disciplinary Differences ◽  
Research Data Management ◽  
Management Actions ◽  
Research Domains

Academic librarians are increasingly engaging in data curation by providing infrastructure (e.g., institutional repositories) and offering services (e.g., data management plan consultations) to support the management of research data on their campuses. Efforts to develop these resources may benefit from a greater understanding of disciplinary differences in research data management needs. After conducting a survey of data management practices and perspectives at our research university, we categorized faculty members into four research domains—arts and humanities, social sciences, medical sciences, and basic sciences—and analyzed variations in their patterns of survey responses. We found statistically significant differences among the four research domains for nearly every survey item, revealing important disciplinary distinctions in data management actions, attitudes, and interest in support services. Serious consideration of both the similarities and dissimilarities among disciplines will help guide academic librarians and other data curation professionals in developing a range of data-management services that can be tailored to the unique needs of different scholarly researchers.

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