scholarly journals Influencing Factors in Determining Research Data Repository Infrastructure for Research Data Management

2019 ◽  
Vol 9 (1) ◽  
pp. 1655-1660
Keyword(s):  
Influencing Factors ◽  
Research Data ◽  
Higher Learning ◽  
Data Repository ◽  
Infrastructure Development ◽  
Electronic Journal ◽  
Research Papers ◽  
Research Data Management ◽  
Data Life Cycle ◽  
Learning Institutions

Increasing volumes of data are rapidly being produced by researchers with the advancement of digital technologies. In order to manage these data, a suitable research data repository infrastructure is needed by the higher learning institutions. Apart from storing the data, these data repository need to support the research data life-cycle that include the tasks of data creation, processing, analysis, preservation, access and reuse. The objective of this research is to deeply investigate the influencing factors fordata repository infrastructure in managing research data. A systematic literature review is conducted to perform the investigation where research papers are searched over three electronic journal databases. Selected papers are then analysed and a quality assessment has been conducted to identify the relevant infrastructure for research data repository. As a result, we identified the important components of research data repository infrastructure development.

Cybersecurity

2020 ◽  
pp. 255-274
Author(s):  
Adel Ismail Al-Alawi ◽  
Arpita A. Mehrotra ◽  
Sara Abdulrahman Al-Bassam
Keyword(s):  
Qualitative Case Study ◽  
Research Data ◽  
Higher Learning ◽  
The Internet ◽  
Semistructured Interviews ◽  
Research Questions ◽  
Learning Institutions ◽  
The Way

The internet has revolutionized the way people communicate, how they manage their business, and even how they conduct their studies. Organizations can conduct meetings virtually and store all their data online. With this convenience, however, comes the risk of cybercrime (CC). Some of the world's most renowned organizations have found themselves having to incur huge recovery costs after falling prey to CC. Higher learning institutions' databases are increasingly falling victim to CCs, owing to the vast amounts of personal and research data they harbor. Despite this, the area of CCs in learning institutions remains understudied. This chapter seeks to identify how CC is manifested in such institutions and the specific cybersecurity measures that stakeholders could use to minimize their exposure to the same. The qualitative case study was designed to explore the research questions, and collected data through semistructured interviews. The findings showed hacking, phishing, and spoofing as the most common manifestations of cybercrime in higher learning institutions.

scholarly journals Research data management and services: Resources for novice data librarians

2017 ◽  
Vol 78 (5) ◽  
pp. 274 ◽  
Author(s):  
Sarah Barbrow ◽  
Denise Brush ◽  
Julie Goldman
Keyword(s):  
Life Cycle ◽  
Data Management ◽  
Academic Libraries ◽  
Research Data ◽  
Research Data Management ◽  
Academic Fields ◽  
Data Life Cycle ◽  
Management Plans ◽  
Share Data

Research in many academic fields today generates large amounts of data. These data not only must be processed and analyzed by the researchers, but also managed throughout the data life cycle. Recently, some academic libraries have begun to offer research data management (RDM) services to their communities. Often, this service starts with helping faculty write data management plans, now required by many federal granting agencies. Libraries with more developed services may work with researchers as they decide how to archive and share data once the grant work is complete.

Research data management: a conceptual framework

2016 ◽  
Vol 65 (4/5) ◽  
pp. 226-241 ◽  
Author(s):  
Dimple Patel
Keyword(s):  
Life Cycle ◽  
Data Management ◽  
Conceptual Framework ◽  
Data Privacy ◽  
Research Data ◽  
Content Type ◽  
Institutional Level ◽  
Research Data Management ◽  
Data Life Cycle ◽  
Effective Manner

Purpose Research data management (RDM) is gaining a lot of momentum in the present day and rightly so. Research data are the core of any research study. The findings and conclusions of a study are entirely dependent on the research data. Traditional publishing did not focus on the presentation of data, along with the publications such as research monographs and especially journal articles, probably because of the difficulties involved in managing the research data sets. The current day technology, however, has helped in making this task easier. The purpose of this paper is to present a conceptual framework for managing research data at the institutional level. Design/methodology/approach This paper discusses the significance and advantages of sharing research data. In the spirit of open access to publications, freeing research data and making it available openly, with minimal restrictions, will help in not only furthering research and development but also avoiding duplication of efforts. The issues and challenges involved in RDM at the institutional level are discussed. Findings A conceptual framework for RDM at the institutional level is presented. A model for a National Repository of Open Research Data (NRORD) is also proposed, and the workflow of the functioning of NRORD is also presented. Originality/value The framework clearly presents the workflow of the data life-cycle in its various phases right from its creation, storage, organization and sharing. It also attempts to address crucial issues in RDM such as data privacy, data security, copyright and licensing. The framework may help the institutions in managing the research data life-cycle in a more efficient and effective manner.

scholarly journals bwFDM Communities – a Research Data Management Initiative in the County of Baden-Wuerttemberg, Germany

2014 ◽  
Author(s):  
Karlheinz Pappenberger
Keyword(s):  
Data Management ◽  
Science Research ◽  
Research Data ◽  
Point Of View ◽  
Data Repository ◽  
Full Time ◽  
It Service ◽  
Research Data Management ◽  
Concrete Action ◽  
The University

>> See video of presentation (33 min.)On 29th July 2014 the Ministry of Science, Research and the Arts of Baden-Wuerttemberg, Germany, has launched an e-science initiative to build up a powerful, efficient and innovative information infrastructure for all universities, research institutions and universities of applied science of the county of southwest Germany. With the overall budget of 3.7 million euro action plans within the five areas licensing, digitalization, research data management, open access and virtual research environments shall be worked out within the next years.Within this framework an 18-month project has been launched at the beginning of 2014 to evaluate the needs of services and support libraries and IT service centres should offer for researchers in the area of research data management. In this “bwFDM communities” named project full time key accounters have been established at all 9 universities of the county (Freiburg, Heidelberg, Hohenheim, Karlsruhe, Konstanz, Mannheim, Stuttgart, Tuebingen and Ulm; among them national and international highly ranked universities). The task of the key accounters is to identity concrete needs and requirements of all research groups working with research data (in a broad sense including all areas of science, social science and humanities) at each of the nine universities as well as possible solutions by conducting semi-structured personal interviews and documenting them in the form of user stories. As a result issues of importance and requirements will be identified, categorized and finalized to recommendations for concrete action plans.The presentation will give an overview of the first results of the project, thereby also highlighting the roles libraries and IT service centres are expected to play from the researcher´s point of view. Furthermore the presentation will point out the response of the University of Konstanz Library to the rising awareness of the importance of research data within the University Executive, showing the special efforts the University of Konstanz Library undertakes to support researchers in their research data management so far and to build up more and more expertise in the area of research data management. One step had been the set-up of a disciplinary data repository in the field of ornithology (Movebank data repository).

scholarly journals Kutatási adatkezelést támogató szolgáltatás a Szegedi Tudományegyetemen

2021 ◽  
Author(s):  
Rozália Zeller ◽  
Szabolcs Hoczopán ◽  
Gyula Nagy
Keyword(s):  
Data Management ◽  
Research Community ◽  
Research Data ◽  
Data Repository ◽  
Institutional Research ◽  
Research Data Management ◽  
International Trends ◽  
Professional Assistance ◽  
Management Recommendations ◽  
The University

Following the national and international trends in mid-2020 the Klebelsberg Kuno Library of the University of Szeged has also started to deal with the issue of research data management. After thorough self-training the library staff studied the Hungarian and international best practices of managing research data. We tried to assess the needs of the institutional research data management habits and the opinion of the researchers of SZTE with a comprehensive questionnaire. We compiled a comprehensive questionnaire to assess the needs of our researchers, learn what they’re thinking about RDM and what kind of practices regarding RDM already exist in the research community. By evaluating the questionnaire we have determined the areas in which the library could provide professional assistance where there was a real need among researchers. Keeping in mind the needs of the research community of University of Szeged we have decided to develop the following services: copyright consulting, RDM trainings for PhD students, theoretical and methodological assistance for RDM, write institutional FAIR data management recommendations. The last four services have been successfully implemented. We also wrote a feasibility study to assess the possibilities of developing our own institutional data repository.

scholarly journals Researchers at Arab Universities Hold Positive Views on Research Data Management and Data Sharing

2020 ◽  
Vol 15 (2) ◽  
pp. 168-170
Author(s):  
Jennifer Kaari
Keyword(s):  
Data Management ◽  
Data Sharing ◽  
Data Privacy ◽  
Management Practices ◽  
Open Data ◽  
Scientific Progress ◽  
Management Plan ◽  
Research Data ◽  
Data Repository ◽  
Research Data Management

A Review of: Elsayed, A. M., & Saleh, E. I. (2018). Research data management and sharing among researchers in Arab universities: An exploratory study. IFLA Journal, 44(4), 281–299. https://doi.org/10.1177/0340035218785196 Abstract Objective – To investigate researchers’ practices and attitudes regarding research data management and data sharing. Design – Email survey. Setting – Universities in Egypt, Jordan, and Saudi Arabia. Subjects – Surveys were sent to 4,086 academic faculty researchers. Methods – The survey was emailed to faculty at three Arab universities, targeting faculty in the life sciences and engineering. The survey was created using Google Docs and remained open for five months. Participants were asked basic demographic questions, questions regarding their research data and metadata practices, and questions regarding their data sharing practices. Main Results – The authors received 337 responses, for a response rate of 8%. The results showed that 48.4% of respondents had a data management plan and that 97% were responsible for preserving their own data. Most respondents stored their research data on their personal storage devices. The authors found that 64.4% of respondents reported sharing their research data. Respondents most frequently shared their data by publishing in a data research journal, sharing through academic social networks such as ResearchGate, and providing data upon request to peers. Only 5.1% of respondents shared data through an open data repository.  Of those who did not share data, data privacy and confidentiality were the most common reasons cited. Of the respondents who did share their data, contributing to scientific progress and increased citation and visibility were the primary reasons for doing so. A total of 59.6% of respondents stated that they needed more training in research data management from their universities. Conclusion – The authors conclude that researchers at Arab universities are still primarily responsible for their own data and that data management planning is still a new concept to most researchers. For the most part, the researchers had a positive attitude toward data sharing, although depositing data in open repositories is still not a widespread practice. The authors conclude that in order to encourage strong data management practices and open data sharing among Arab university researchers, more training and institutional support is needed.

scholarly journals Research Data Management Implementation at Peking University Library: Foster and Promote Open Science and Open Data

2021 ◽  
Vol 3 (1) ◽  
pp. 189-204
Author(s):  
Hua Nie ◽  
Pengcheng Luo ◽  
Ping Fu
Keyword(s):  
Data Management ◽  
Open Data ◽  
Implementation Process ◽  
Open Science ◽  
Research Data ◽  
Data Repository ◽  
Research Data Management ◽  
University Library ◽  
Open Research ◽  
Peking University

Research Data Management (RDM) has become increasingly important for more and more academic institutions. Using the Peking University Open Research Data Repository (PKU-ORDR) project as an example, this paper will review a library-based university-wide open research data repository project and related RDM services implementation process including project kickoff, needs assessment, partnerships establishment, software investigation and selection, software customization, as well as data curation services and training. Through the review, some issues revealed during the stages of the implementation process are also discussed and addressed in the paper such as awareness of research data, demands from data providers and users, data policies and requirements from home institution, requirements from funding agencies and publishers, the collaboration between administrative units and libraries, and concerns from data providers and users. The significance of the study is that the paper shows an example of creating an Open Data repository and RDM services for other Chinese academic libraries planning to implement their RDM services for their home institutions. The authors of the paper have also observed since the PKU-ORDR and RDM services implemented in 2015, the Peking University Library (PKUL) has helped numerous researchers to support the entire research life cycle and enhanced Open Science (OS) practices on campus, as well as impacted the national OS movement in China through various national events and activities hosted by the PKUL.

scholarly journals Creating Guidance for Canadian Dataverse Curators: Portage Network’s Dataverse Curation Guide

2021 ◽  
Vol 10 (3) ◽  
Author(s):  
Alexandra Cooper ◽  
Michael Steeleworthy ◽  
Ève Paquette-Bigras ◽  
Erin Clary ◽  
Erin MacPherson ◽  
...  
Keyword(s):  
Best Practices ◽  
International Institutions ◽  
Research Data ◽  
Data Curation ◽  
Data Repository ◽  
National Network ◽  
Research Data Management ◽  
National Organizations ◽  
French And English ◽  
Support Research

Purpose: This paper introduces the Portage Network’s Dataverse Curation Guide and the new bilingual curation framework developed to support it. Brief Description: Canadian academic institutions and national organizations have been building infrastructure, staffing, and programming to support research data management. Amidst this work, a notable gap emerged between requirements for data curation in general repositories like Dataverse and the requisite workflows and guidance materials needed by curators to meet them. In response, Portage, a national network of data experts, organized a working group to develop a Dataverse curation guide built upon the Data Curation Network’s CURATED workflow. To create a bilingual resource, the original CURATE(D) acronym was modified to CURATION—which has the same meaning in both French and English—and steps were augmented with Dataverse-specific guidance and mapped to three conceptualized levels of curation to assist curators in prioritizing curation actions. Methods: An environmental scan of relevant deposit and curation guidance materials from Canadian and international institutions identified the need for a comprehensive Dataverse Curation Guide, as most existing resources were either depositor-focused or contained only partial workflows. The resulting Guide synthesized these guidance materials into the CURATION steps and mapped actions to various theoretical levels of data repository services and levels of curation. Resources: The following documents are supplemental to the Dataverse Curation Guide: the Portage Dataverse North Metadata Best Practices Guide, the Scholars Portal Dataverse Guide, and the Data Curation Network CURATED Workflow and Data Curation Primers.

Research Data Management Among Researchers in Higher Learning Institutions of Sub-Saharan Africa

2020 ◽  
pp. 479-488 ◽  
Author(s):  
Neema Florence Mosha ◽  
Edith Talina Luhanga ◽  
Mary Vincent Mosha ◽  
Janeth Jonathan Marwa
Keyword(s):  
Data Management ◽  
Information And Communication Technologies ◽  
Management Plan ◽  
Research Data ◽  
Sub Saharan Africa ◽  
Quality Data ◽  
Research Data Management ◽  
Information And Communication ◽  
Sub Saharan ◽  
Learning Institutions

Advancement in information and communication technologies has made it easier for researchers to capture and store myriad data at a higher level of granularity. Higher education institutions (HEIs) worldwide are incorporating research data management (RDM) services to enable researchers to work with their data properly. This chapter focuses on creating awareness amongst researchers on how researchers and HEIs can form strategies, design and restrict data management plan (DMP), integrate research data life cycle, and ensure quality data sharing, as well as integrate with developed RDM policies and guidelines to curb challenges prohibiting the practice of RDM in HEIs.

Research data management in practice: Results from a cross-sectional survey of health and medical researchers from an academic institution in Australia

2019 ◽  
Vol 49 (2-3) ◽  
pp. 108-116 ◽  
Author(s):  
Michelle A Krahe ◽  
Julie Toohey ◽  
Malcolm Wolski ◽  
Paul A Scuffham ◽  
Sheena Reilly
Keyword(s):  
Life Cycle ◽  
Data Management ◽  
Research Data ◽  
Academic Institution ◽  
Cross Sectional Survey ◽  
Cross Sectional ◽  
Convenience Sample ◽  
Research Data Management ◽  
Data Life Cycle ◽  
Medical Researchers

Background: Building or acquiring research data management (RDM) capacity is a major challenge for health and medical researchers and academic institutes alike. Considering that RDM practices influence the integrity and longevity of data, targeting RDM services and support in recognition of needs is especially valuable in health and medical research. Objective: This project sought to examine the current RDM practices of health and medical researchers from an academic institution in Australia. Method: A cross-sectional survey was used to collect information from a convenience sample of 81 members of a research institute (68 academic staff and 13 postgraduate students). A survey was constructed to assess selected data management tasks associated with the earlier stages of the research data life cycle. Results: Our study indicates that RDM tasks associated with creating, processing and analysis of data vary greatly among researchers and are likely influenced by their level of research experience and RDM practices within their immediate teams. Conclusion: Evaluating the data management practices of health and medical researchers, contextualised by tasks associated with the research data life cycle, is an effective way of shaping RDM services and support in this group. Implications: This study recognises that institutional strategies targeted at tasks associated with the creation, processing and analysis of data will strengthen researcher capacity, instil good research practice and, over time, improve health informatics and research data quality.

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