scholarly journals PUBLICATION OF RESEARCH DATA MANAGEMENT IN OPEN ACCESS JOURNAL ANALYSIS BASED ON SCOPUS DATA

2020 ◽  
Vol 41 (2) ◽  
pp. 215
Author(s):  
Tupan Tupan ◽  
Kamaludin Kamaludin
Keyword(s):  
New York ◽  
Open Access ◽  
Data Management ◽  
Data Science ◽  
The United States ◽  
Open Access Journal ◽  
Research Data ◽  
New York University ◽  
Research Data Management ◽  
Open Access Resources

The study aims to determine: (1) the number of open access resources for research data management publications indexed by Scopus, including the year of publication, source of publication, authors, institutions, countries, types of documents and funding agencies; (2) mapping research data management based on keywords. The results of the study showed that the number of open access resources for research data management publications has started since 1981 and the number has continued to increase starting in 2014 and the highest number occurred in 2019, namely 49 publications. The most publicized journals that open access to research data management was the Data Science Journal, which was 11 publications. The most productive author of conducting research data management publications was Cox, A.M. and Pinfield, S. The largest institutions contributing to the publication of open access research data management were the University of Toronto and New York University. The countries that contributed the most were the United States with 50 publications, then China with 38 publications. The most open access research data management in the form of articles as many as 107 and 37 conference paper publications. The institutions that provided the most funding sponsors were the Deutsche Forschungsgemeinschaft and the National Science Foundation. The results of keyword mapping with VOSViewer showed that big data, research data management, information management, data management, medical research topics, software, information processing, and metadata were the most researched topics.

scholarly journals Reproducibility Librarianship

2017 ◽  
Author(s):  
Vicky Steeves
Keyword(s):  
New York ◽  
Data Management ◽  
Data Science ◽  
Research Data ◽  
Reproducible Research ◽  
New York University ◽  
Research Data Management ◽  
Digital Scholarship ◽  
The Many

This is a self-archived version of an article published in Collaborative Librarianship. The content of this article is not different from what is in the journal (found here: http://digitalcommons.du.edu/collaborativelibrarianship/vol9/iss2/4)Recommended CitationSteeves, Vicky (2017) "Reproducibility Librarianship," Collaborative Librarianship: Vol. 9 : Iss. 2 , Article 4. Available at: https://digitalcommons.du.edu/collaborativelibrarianship/vol9/iss2/4Over the past few years, research reproducibility has been increasingly highlighted as a multifaceted challenge across many disciplines. There are socio-cultural obstacles as well as a constantly changing technical landscape that make replicating and reproducing research extremely difficult. Researchers face challenges in reproducing research across different operating systems and different versions of software, to name just a few of the many technical barriers. The prioritization of citation counts and journal prestige has undermined incentives to make research reproducible.While libraries have been building support around research data management and digital scholarship, reproducibility is an emerging area that has yet to be systematically addressed. To respond to this, New York University (NYU) created the position of Librarian for Research Data Management and Reproducibility (RDM & R), a dual appointment between the Center for Data Science (CDS) and the Division of Libraries. This report will outline the role of the RDM & R librarian, paying close attention to the collaboration between the CDS and Libraries to bring reproducible research practices into the norm.

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 Teaching Open Science

2020 ◽  
Author(s):  
Helene N. Andreassen ◽  
Erik Lieungh
Keyword(s):  
Open Access ◽  
Data Management ◽  
Teaching And Learning ◽  
Open Science ◽  
Research Data ◽  
Open Access Publishing ◽  
The Arctic ◽  
Learning Support ◽  
Research Data Management ◽  
The University

In this episode, we are discussing how to teach open science to PhD students. Helene N. Andreassen, head of Library Teaching and Learning Support at the University Library of UiT the Arctic University of Norway shares her experiences with the integration of open science in a special, tailor-made course for PhD's that have just started their project. An interdisciplinary, discussion-based course, "Take Control of Your PhD Journey: From (P)reflection to Publishing" consists of a series of seminars on research data management, open access publishing and other subject matters pertaining to open science. First published online February 26, 2020.

scholarly journals Clinical research data management in the United States: Where we've been and where we're going

2021 ◽  
Author(s):  
Mary Banach ◽  
Kaye H Fendt ◽  
Johann Proeve ◽  
Dale Plummer ◽  
Samina Qureshi ◽  
...  
Keyword(s):  
Clinical Research ◽  
Data Management ◽  
Clinical Data ◽  
Management Practices ◽  
The United States ◽  
Research Data ◽  
Fda Guidance ◽  
Research Data Management ◽  
Challenges And Opportunities ◽  
Clinical Research Data

With the focus of the COVID-19 pandemic, we wanted to reach all stakeholders representing communities concerned with good clinical data management practices. We wanted to represent not only data managers but bio-statisticians, clinical monitors, data scientists, informaticians, and all those who collect, organize, analyze, and report on clinical research data. In our paper we will discuss the history of clinical data management in the US and its evolution from the early days of FDA guidance. We will explore the role of biomedical research focusing on the similarities and differences in industry and academia clinical research data management and what we can learn from each other. We will talk about our goals for recruitment and training for the CDM community and what we propose for increasing the knowledge and understanding of good clinical data practice to all – particularly our front-line data collectors i.e., nurses, medical assistants, patients, other data collectors. Finally, we will explore the challenges and opportunities to see CDM as the hub for good clinical data research practices in all of our communities.We will also discuss our survey on how the COVID-19 pandemic has affected the work of CDM in clinical research.

scholarly journals Research data management: a bibliometric and altmetric study based on Dimensions

2021 ◽  
Vol 1 (3) ◽  
pp. 1-19
Author(s):  
Marília Catarina Andrade Gontijo ◽  
Raíssa Yuri Hamanaka ◽  
Ronaldo Ferreira De Araujo
Keyword(s):  
Information Systems ◽  
Data Management ◽  
Data Science ◽  
Research Data ◽  
Scientific Production ◽  
Research Data Management ◽  
Research Areas ◽  
Library And Information Studies ◽  
Information Studies ◽  
Online Attention

Objective. This study aims to analyze the scientific production on research data management indexed in the Dimensions database. Design/Methodology/Approach. Using the term “research data management” in the Dimensions database, 677 articles were retrieved and analyzed employing bibliometric and altmetric indicators. The Altmetrics.com system was used to collect data from alternative virtual sources to measure the online attention received by the retrieved articles. Bibliometric networks from journals bibliographic coupling and keywords co-occurrence were generated using the VOSviewer software. Results/Discussion. Growth in scientific production over the period 1970-2021 was observed. The countries/regions with the highest rates of publications were the USA, Germany, and the United Kingdom. Among the most productive authors were Andrew Martin Cox, Stephen Pinfield, Marta Teperek, Mary Anne Kennan, and Amanda L. Whitmire. The most productive journals were the International Journal of Digital Curation, Journal of eScience Librarianship, and Data Science Journal, while the most representative research areas were Information and Computing Sciences, Information Systems, and Library and Information Studies. Conclusions. The multidisciplinarity in research data management was demonstrated by publications occurring in different fields of research, such as Information and Computing Sciences, Information Systems, Library and Information Studies, Medical and Health Sciences, and History and Archeology. About 60% of the publications had at least one citation, with a total of 3,598 citations found, featuring a growing academic impact. Originality/Value. This bibliometric and altmetric study allowed the analysis of the literature on research data management. The theme was investigated in the Dimensions database and analyzed using productivity, impact, and online attention indicators.

scholarly journals Teaching librarians about data: The ACRL Research Data Management RoadShow

2018 ◽  
Vol 79 (7) ◽  
pp. 354 ◽  
Author(s):  
Abigail Goben ◽  
Megan Sapp Nelson
Keyword(s):  
United States ◽  
Data Management ◽  
Academic Libraries ◽  
The United States ◽  
Research Data ◽  
Further Education ◽  
Research Data Management ◽  
Service Activity ◽  
Second Year ◽  
Full Day

As research data management (RDM) has grown into an increasingly familiar service activity in academic libraries, there remains a knowledge gap for liaison and subject librarians attempting to take on these additional responsibilities. As one option to address this, the authors were contracted by ACRL to create a new full-day workshop targeting this specific audience. The result is the ACRL RoadShow, Building Your Research Data Management Toolkit: Integrating RDM into Your Liaison Work. Now in its second year, the RDM RoadShow has traveled extensively in the United States as well as one international trip and continues to assist in meeting the foundational RDM educational needs for liaison librarians and to identify where further education is desired.

scholarly journals The Problematic Future of Research Data Management: Challenges, Opportunities and Emerging Patterns Identified by the DataRes Project

2013 ◽  
Vol 8 (2) ◽  
pp. 111-122 ◽  
Author(s):  
Martin Halbert
Keyword(s):  
Data Management ◽  
Academic Research ◽  
The United States ◽  
Research Data ◽  
University Of North Texas ◽  
Research Data Management ◽  
Management Plans ◽  
Institutional Transitions ◽  
Grant Proposals ◽  
The University

This paper describes findings and projections from a project that has examined emerging policies and practices in the United States regarding the long-term institutional management of research data. The DataRes project at the University of North Texas (UNT) studied institutional transitions taking place during 2011-2012 in response to new mandates from U.S. governmental funding agencies requiring research data management plans to be submitted with grant proposals. Additional synergistic findings from another UNT project, termed iCAMP, will also be reported briefly.This paper will build on these data analysis activities to discuss conclusions and prospects for likely developments within coming years based on the trends surfaced in this work. Several of these conclusions and prospects are surprising, representing both opportunities and troubling challenges, for not only the library profession but the academic research community as a whole.

Research Data Management Support at Kaunas University of Technology

2021 ◽  
pp. 52-71
Author(s):  
Ieva Cesevičiūtė ◽  
Gintarė Tautkevičienė
Keyword(s):  
Open Access ◽  
Data Management ◽  
National Level ◽  
Open Science ◽  
Research Data ◽  
Management Support ◽  
Research Data Management ◽  
University Of Technology ◽  
Management Plans ◽  
The Baltic

Kaunas University of Technology is one of the largest technical universities in the Baltic region. The university staff has been involved in different Open Access- and Open Science-related activities for more than a decade. Different initiatives have been implemented: stand-alone and series of training and awareness-raising events, promotion of Open Access and Open Science ideas so that institutions develop their Open Access policies and make their repositories compliant with larger research infrastructures. Within the institution, the initiatives of Open Science are implemented as a result of joint effort of the library, the departments of research, studies, and doctoral school. The current tasks involve revising the institutional Open Access guidelines and facilitating the implementation of data management plans in doctoral studies. In this chapter, the aim is to provide an overview of the efforts highlighting the successes and failures on the way to best practice in research data management support both institutionally and on the national level.

scholarly journals Defining the role of libraries in the Open Science landscape: a reflection on current European practice

2018 ◽  
Vol 2 (1) ◽  
pp. 1-22 ◽  
Author(s):  
Paul Ayris ◽  
Tiberius Ignat
Keyword(s):  
Open Access ◽  
Data Management ◽  
Case Studies ◽  
Publishing Research ◽  
Research Process ◽  
Open Science ◽  
Research Data ◽  
Step Test ◽  
Open Access Publishing ◽  
Research Data Management

Abstract This collaborative paper looks at how libraries can engage with and offer leadership in the Open Science movement. It is based on case studies and the results of an EU-funded research project on Research Data Management taken from European research-led universities and their libraries. It begins by analysing three recent trends in Science, and then links component parts of the research process to aspects of Open Science. The paper then looks in detail at four areas and identifies roles for libraries: Open Access and Open Access publishing, Research Data Management, E-Infrastructures (especially the European Open Science Cloud), and Citizen Science. The paper ends in suggesting a model for how libraries, by using a 4-step test, can assess their engagement with Open Science. This 4-step test is based on lessons drawn from the case studies.

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