Investigation and analysis of research data services in university libraries

2015 ◽  
Vol 33 (3) ◽  
pp. 417-449 ◽  
Author(s):  
Li Si ◽  
Wenming Xing ◽  
Xiaozhe Zhuang ◽  
Xiaoqin Hua ◽  
Limei Zhou
Keyword(s):  
Data Management ◽  
Academic Libraries ◽  
Management Training ◽  
Site Investigation ◽  
Research Data ◽  
Data Service ◽  
University Libraries ◽  
Content Type ◽  
Data Services ◽  
And Storage

Purpose – This paper aims to find the current situation of research data services by academic libraries and summarize some strategies for university libraries to reference. Recent years have seen an increasing number of university libraries extended their traditional roles and provided research data services. Design/methodology/approach – This paper selected 87 libraries of the top 100 universities listed in the World’s Best Universities released by the USA News in October 2012 as samples and conducted a Web site investigation to check if there were any research data services provided. In addition, it made an interview with the Wuhan University Library’s Research Data Service Workgroup to understand the procedure, difficulties and experiences of their research data service. Based on the survey and interview, it analyzed the current status and difficulties of research data services in university libraries and proposed some strategies for others to reference. Findings – Of the 87 university libraries investigated, 50 libraries have offered research data services. Most of the services can be divided into six aspects: research data introduction, data management guideline, data curation and storage service, data management training, data management reference and resource recommendation. Among these services, research data introduction is the most frequently provided (47.13 per cent), followed by data curation and storage services (43.68 per cent), data management guideline (42.53 per cent), data management reference (41.38 per cent), resource recommendation (41.38 per cent) and data management training (24.14 per cent). The difficulties met by research data service of Chinese academic libraries are also concluded. Originality/value – Through Web site investigation and interview with the Wuhan University Library’s Research Data Service, this paper presented an overall picture of research data services in university libraries and identified the difficulties and experiences of research data services of the Wuhan University Library. Based on some successful examples, it put forward some strategies for university libraries to reference. This study is very useful for academic libraries to promote their research data services.

scholarly journals Teaching Research Data Management

2014 ◽  
Vol 6 ◽  
Author(s):  
Wendy Mann
Keyword(s):  
Graduate Students ◽  
Data Management ◽  
Management Training ◽  
Boot Camp ◽  
Research Data ◽  
University Libraries ◽  
Management Skills ◽  
Data Services ◽  
Research Data Management ◽  
The University

In January 2014, Mason Libraries along with four other libraries in Virginia used 4-VA telepresence technology to teach a two-day boot camp to graduate students on research data management. Our workshop generated greater than expected interest from graduate students here at Mason. One lesson learned is that there appears to be a gap in the curriculum across all participating schools regarding the teaching of data management skills to budding researchers. This session will be an overview of the learning outcomes from the Data Management Boot Camp, how the University Libraries' Data Services carries out research data management training, and discussion of future plans for helping researchers organize and manage their data.

Big data adoption in academic libraries: a literature review

2020 ◽  
Vol 37 (4) ◽  
pp. 1-5
Author(s):  
Nove E. Variant Anna ◽  
Endang Fitriyah Mannan
Keyword(s):  
Big Data ◽  
Data Management ◽  
Academic Libraries ◽  
Data Analytics ◽  
Academic Library ◽  
Big Data Analytics ◽  
Research Data ◽  
Management Policy ◽  
Content Type ◽  
Scopus Database

Purpose The purpose of this paper is to analyse the publication of big data in the library from Scopus database by looking at the writing time period of the papers, author's country, the most frequently occurring keywords, the article theme, the journal publisher and the group of keywords in the big data article. The methodology used in this study is a quantitative approach by extracting data from Scopus database publications with the keywords “big data” and “library” in May 2019. The collected data was analysed using Voxviewer software to show the keywords or terms. The results of the study stated that articles on big data have appeared since 2012 and are increasing in number every year. The big data authors are mostly from China and America. Keywords that often appear are based on the results of terminology visualization are including, “big data”, “libraries”, “library”, “data handling”, “data mining”, “university libraries”, “digital libraries”, “academic libraries”, “big data applications” and “data management”. It can be concluded that the number of publications related to big data in the library is still small; there are still many gaps that need to be researched on the topic. The results of the research can be used by libraries in using big data for the development of library innovation. Design/methodology/approach The Scopus database was accessed on 24 May 2019 by using the keyword “big data” and “library” in the search box. The authors only include papers, which title contain of big data in library. There were 74 papers, however, 1 article was dropped because of it not meeting the criteria (affiliation and abstract were not available). The papers consist of journal articles, conference papers, book chapters, editorial and review. Then the data were extracted into excel and analysed as follows (by the year, by the author/s’s country, by the theme and by the publisher). Following that the collected data were analysed using VOX viewer software to see the relationship between big data terminology and library, terminology clustering, keywords that often appear, countries that publish big data, number of big data authors, year of publication and name of journals that publish big data and library articles (Alagu and Thanuskodi, 2019). Findings It can be concluded that the implementation of big data in libraries is still in an early stage, it is shown from the limited number of practical implementation of big data analytics in library. Not many libraries that use big data to support innovation and services since there were lack of librarian skills of big data analytics. The library manager’s view of big data is still not necessary to do. It is suggested for academic libraries to start their adoption of big data analytics to support library services especially research data. To do so, librarians can enhance their skills and knowledge by following some training in big data analytics or research data management. The information technology infrastructure also needs to be upgraded since big data need big IT capacity. Finally, the big data management policy should be made to ensure the implementation goes well. Originality/value This paper discovers the adoption and implementation of big data in library, many papers talk big data in business and technology context. This is offering new idea for many libraries especially academic library about the adoption of big data to support their services. They can adopt the big data analytics technology and technique that suitable for their library.

A systematic literature review on research data management practices and services

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Murtaza Ashiq ◽  
Muhammad Haroon Usmani ◽  
Muhammad Naeem
Keyword(s):  
Literature Review ◽  
Data Management ◽  
Systematic Literature Review ◽  
Academic Libraries ◽  
Management Practices ◽  
Developed Countries ◽  
Research Data ◽  
Open Access Publishing ◽  
Content Type ◽  
Research Data Management

Purpose Research data management (RDM) has been called a “ground-breaking” area for research libraries and it is among the top future trends for academic libraries. Hence, this study aims to systematically review RDM practices and services primarily focusing on the challenges, services and skills along with motivational factors associated with it. Design/methodology/approach A systematic literature review method was used focusing on literature produced between 2016–2020 to understand the latest trends. An extensive research strategy was framed and 15,206 results appeared. Finally, 19 studies have fulfilled the criteria to be included in the study following preferred reporting items for systematic reviews and meta-analysis. Findings RDM is gradually gaining importance among researchers and academic libraries; however, it is still poorly practiced by researchers and academic libraries. Albeit, it is better observed in developed countries over developing countries, however, there are lots of challenges associated with RDM practices by researchers and services by libraries. These challenges demand certain sets of skills to be developed for better practices and services. An active collaboration is required among stakeholders and university services departments to figure out the challenges and issues. Research limitations/implications The implications of policy and practical point-of-view present how research data can be better managed in the future by researchers and library professionals. The expected/desired role of key stockholders in this regard is also highlighted. Originality/value RDM is an important and emerging area. Researchers and Library and Information Science professionals are not comprehensively managing research data as it involves complex cooperation among various stakeholders. A combination of measures is required to better manage research data that would ultimately move forward for open access publishing.

The role of academic libraries in research data service (RDS) provision

2017 ◽  
Vol 35 (4) ◽  
pp. 783-797 ◽  
Author(s):  
Holly H. Yu
Keyword(s):  
Academic Libraries ◽  
Academic Library ◽  
Research Data ◽  
The Body ◽  
Data Service ◽  
Academic Institutions ◽  
Content Type ◽  
Research Libraries ◽  
Body Of Knowledge ◽  
Current State

Purpose Propelled by fast-evolving computational technology and cloud-based data storage, the increasing ease in research data collection is outstripping the capacity in research data service (RDS) in academic institutions. To illustrate the challenges and opportunities in providing RDS, the author provides a systematic review of the RDS offered in academic institutions and libraries by combining existing literature and survey data collected from the Association of Research Libraries (ARL) and the Association of College and Research Libraries (ACRL). In addition, the RDS websites of 2013 ARL survey-participating institutions are also examined. The aim of the paper is to provide an environmental scan of the current state of RDS provision in academic institutions, to add to the body of knowledge of RDS development, and to inform and enable academic libraries to make strategic RDS plans. Design/methodology/approach The paper analyzes the strategies used and levels of RDS provided by reviewing recent literature, exploiting existing survey data from ARL and ACRL, and examining RDS websites of the 2013 ARL survey-participating institutions, in areas that reflect the life cycle of RDS provision including research data management planning, metadata consultation and tool provision, data archiving, institutional repository provision and data sharing and access. Findings The overall offerings of the library-led research data services in ARL research-intensive institutions have shown signs of increasing. Increased engagement and expanded scope and level of services are two noticeable trends in academic library RDS provision. Academic libraries are taking advantage of open access repositories by advising researchers to use the available resources alongside their local repositories for data safe-keeping and sharing. Discussions on RDS policy and infrastructure development are inadequate or largely non-existent. Originality/value Through systematically reviewing current literature, drawing on the results of available surveys on RDS offerings by academic libraries conducted between 2009 and 2014 and examining and further reviewing the websites of these 2013 ARL survey-participating institutions, the author presents the current state of academic library activities in RDS provision, and provides a critical evaluation of the scope and level of services currently being offered in academic libraries, and the opportunities in RDS development, to add to the body of knowledge of RDS provision by academic institutions.

scholarly journals Maturing research data services and the transformation of academic libraries

2019 ◽  
Vol 75 (6) ◽  
pp. 1432-1462 ◽  
Author(s):  
Andrew M. Cox ◽  
Mary Anne Kennan ◽  
Liz Lyon ◽  
Stephen Pinfield ◽  
Laura Sbaffi
Keyword(s):  
Academic Libraries ◽  
Research Data ◽  
Service Development ◽  
Maturity Model ◽  
Stages Of Development ◽  
Data Set ◽  
Content Type ◽  
Data Services ◽  
Skills Shortages ◽  
The Impact

Purpose A major development in academic libraries in the last decade has been recognition of the need to support research data management (RDM). The purpose of this paper is to capture how library research data services (RDS) have developed and to assess the impact of this on the nature of academic libraries. Design/methodology/approach Questionnaire responses from libraries in Australia, Canada, Germany, Ireland, the Netherlands, New Zealand, the UK and USA from 2018 are compared to a previous data set from 2014. Findings The evidence supports a picture of the spread of RDS, especially advisory ones. However, future ambitions do not seem to have seen much evolution. There is limited evidence of organisational change and skills shortages remain. Most service development can be explained as the extension of traditional library services to research data. Yet there remains the potential for transformational impacts, when combined with the demands implied by other new services such as around text and data mining, bibliometrics and artificial intelligence. A revised maturity model is presented that summarises typical stages of development of services, structures and skills. Research limitations/implications The research models show how RDS are developing. It also reflects on the extent to which RDM represents a transformation of the role of academic libraries. Practical implications Practitioners working in the RDM arena can benchmark their current practices and future plans against wider patterns. Originality/value The study offers a clear picture of the evolution of research data services internationally and proposes a maturity model to capture typical stages of development. It contributes to the wider discussion of how the nature of academic libraries are changing.

Research data management in universities of central China

2016 ◽  
Vol 34 (5) ◽  
pp. 808-822 ◽  
Author(s):  
Xia Liu ◽  
Ning Ding
Keyword(s):  
Developing Countries ◽  
Data Management ◽  
Research Data ◽  
Central China ◽  
University Libraries ◽  
User Survey ◽  
Chinese Universities ◽  
Content Type ◽  
Research Data Management ◽  
Utilisation Efficiency

Purpose Revealing research data’s production and use, the status of research data management (RDM) and researchers’ service requirements in universities of Central China; this study aims to investigate the feasibility of university libraries in providing RDM services without any supporting policies from governments or funding agencies. Design/methodology/approach Using a stratified sampling method, faculties and graduate students from 11 universities were investigated. Four pilot subjects at Wuhan University (WHU) were chosen for whom a pilot RDM platform was to be constructed. Findings Research data at Chinese universities are small, sporadic and discontinuous. Such data are intensively or dispersedly under researcher’s management, with some unresolved problems regarding data security, data sharing and utilisation efficiency. Researchers’ needs for data services are strong. University libraries in China can develop RDM systems and provide related services. To realise this, more work should be done on service mechanism, service promotion, software development and staff training. Research limitations/implications The user survey covered 11 universities in central China, which may not reveal the real RDM status of researcher in different areas of China. Practical implications The practice at WHU could provide reference to other university libraries in China or other developing countries. Social implications The practice at WHU could provide reference to other university libraries in China or other developing countries. Originality/value The user survey is designed to be as comprehensive as possible and cover 902 researchers from 11 different types of Chinese universities. The practice at WHU is one of the first RDM initiatives led by university library in China.

scholarly journals The Time Has Come… To Talk About Why Research Data Management Isn’t Easy

2020 ◽  
Author(s):  
Carol Tenopir ◽  
Jordan Kaufman ◽  
Robert J. Sandusky ◽  
Danielle Pollock
Keyword(s):  
Data Management ◽  
Academic Libraries ◽  
Research Data ◽  
Data Services ◽  
Research Libraries ◽  
Research Data Management ◽  
The Future

For the last decade, academic libraries have talked with each other and with potential partners about their roles in helping to manage research data and their plans to expand or initiate research data services (RDS). Libraries have the capacity to provide these services, but the range and maturity of research data services from libraries vary considerably. In summer 2019, our team surveyed a sample of academic libraries of all sizes who are members of the Association of College and Research Libraries (ACRL) to find out about their current RDS and plans for the future. This study is a follow-up to surveys of this same group in 2012 and 2015. Our findings include the types of RDS currently being offered in academic libraries, the barriers that hinder RDS implementation, and staff capacity for creating RDS.

scholarly journals Exploring digital preservation requirements

2017 ◽  
Vol 27 (2) ◽  
pp. 175-191 ◽  
Author(s):  
Jaana Pinnick
Keyword(s):  
Data Management ◽  
Digital Preservation ◽  
Management Training ◽  
Research Data ◽  
Content Type ◽  
Research Data Management ◽  
Mixed Methods Case Study ◽  
Management Processes ◽  
Digital Asset

Purpose The aim of this paper was to explore digital preservation requirements within the wider National Geoscience Data Centre (NGDC) organisational framework in preparation for developing a preservation policy and integrating associated preservation workflows throughout the existing research data management processes. This case study is based on an MSc dissertation research undertaken at Northumbria University. Design/methodology/approach This mixed methods case study used quantitative and qualitative data to explore the preservation requirements and triangulation to strengthen the design validity. Corporate and the wider scientific priorities were identified through literature and a stakeholder survey. Organisational preparedness was investigated through staff interviews. Findings Stakeholders expect data to be reliable, reusable and available in preferred formats. To ensure digital continuity, the creation of high-quality metadata is critical, and data depositors need data management training to achieve this. Recommendations include completing a risk assessment, creating a digital asset register and a technology watch to mitigate against risks. Research limitations/implications The main constraint in this study is the lack of generalisability of results. As the NGDC is a unique organisation, it may not be possible to generalise the organisational findings, although those relating to research data management may be transferrable. Originality/value This research examines the specific nature of geoscience data retention requirements and looks at existing NGDC procedures in terms of enhancing digital continuity, providing new knowledge on the preservation requirements for a number of national datasets.

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