Changes in academic libraries in the era of Open Science

2020 ◽  
Vol 36 (3) ◽  
pp. 281-299
Author(s):  
Stefka Tzanova
Keyword(s):  
Big Data ◽  
Data Management ◽  
Academic Libraries ◽  
Data Science ◽  
Academic Library ◽  
Open Data ◽  
Open Science ◽  
Management Plan ◽  
Educational Process ◽  
Library Services

In this paper we study the changes in academic library services inspired by the Open Science movement and especially the changes prompted from Open Data as a founding part of Open Science. We argue that academic libraries face the even bigger challenges for accommodating and providing support for Open Big Data composed from existing raw data sets and new massive sets generated from data driven research. Ensuring the veracity of Open Big Data is a complex problem dominated by data science. For academic libraries, that challenge triggers not only the expansion of traditional library services, but also leads to adoption of a set of new roles and responsibilities. That includes, but is not limited to development of the supporting models for Research Data Management, providing Data Management Plan assistance, expanding the qualifications of library personnel toward data science literacy, integration of the library services into research and educational process by taking part in research grants and many others. We outline several approaches taken by some academic libraries and by libraries at the City University of New York (CUNY) to meet necessities imposed by doing research and education with Open Big Data – from changes in libraries’ administrative structure, changes in personnel qualifications and duties, leading the interdisciplinary advisory groups, to active collaboration in principal projects.

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.

scholarly journals The Open-Specimen Movement

BioScience ◽  
2020 ◽  
Author(s):  
Jocelyn P Colella ◽  
Ryan B Stephens ◽  
Mariel L Campbell ◽  
Brooks A Kohli ◽  
Danielle J Parsons ◽  
...  
Keyword(s):  
Data Management ◽  
Open Data ◽  
Open Science ◽  
Management Plan ◽  
Scientific Data ◽  
Primary Data ◽  
Explicit Integration ◽  
Cultural Shift ◽  
Major Barrier ◽  
Annual Reporting

Abstract The open-science movement seeks to increase transparency, reproducibility, and access to scientific data. As primary data, preserved biological specimens represent records of global biodiversity critical to research, conservation, national security, and public health. However, a recent decrease in specimen preservation in public biorepositories is a major barrier to open biological science. As such, there is an urgent need for a cultural shift in the life sciences that normalizes specimen deposition in museum collections. Museums embody an open-science ethos and provide long-term research infrastructure through curation, data management and security, and community-wide access to samples and data, thereby ensuring scientific reproducibility and extension. We propose that a paradigm shift from specimen ownership to specimen stewardship can be achieved through increased open-data requirements among scientific journals and institutional requirements for specimen deposition by funding and permitting agencies, and through explicit integration of specimens into existing data management plan guidelines and annual reporting.

scholarly journals Dealing with Data: Science Librarians’ Participation in Data Management at Association of Research Libraries Institutions

2014 ◽  
Vol 75 (4) ◽  
pp. 557-574 ◽  
Author(s):  
Karen Antell ◽  
Jody Bales Foote ◽  
Jaymie Turner ◽  
Brian Shults
Keyword(s):  
Data Management ◽  
Academic Libraries ◽  
Data Science ◽  
Management Plan ◽  
Funding Agency ◽  
Management Support ◽  
Data Repositories ◽  
Institutional Repositories ◽  
Research Libraries ◽  
Association Of Research Libraries

As long as empirical research has existed, researchers have been doing “data management” in one form or another. However, funding agency mandates for doing formal data management are relatively recent, and academic libraries’ involvement has been concentrated mainly in the last few years. The National Science Foundation implemented a new mandate in January 2011, requiring researchers to include a data management plan with their proposals for funding. This has prompted many academic libraries to work more actively than before in data management, and science librarians in particular are uniquely poised to step into new roles to meet researchers’ data management needs. This study, a survey of science librarians at institutions affiliated with the Association of Research Libraries, investigates science librarians’ awareness of and involvement in institutional repositories, data repositories, and data management support services at their institutions. The study also explores the roles and responsibilities, both new and traditional, that science librarians have assumed related to data management, and the skills that science librarians believe are necessary to meet the demands of data management work. The results reveal themes of both uncertainty and optimism—uncertainty about the roles of librarians, libraries, and other campus entities; uncertainty about the skills that will be required; but also optimism about applying “traditional” librarian skills to this emerging field of academic librarianship.

scholarly journals Replicable services for reproducible research: a model for academic libraries

Bibliosphere ◽  
2020 ◽  
pp. 33-45
Author(s):  
F. Sayre ◽  
A. Riegelman
Keyword(s):  
Academic Libraries ◽  
Academic Library ◽  
Academic Librarians ◽  
Reproducible Research ◽  
Library Services ◽  
The Public ◽  
Data Intensive ◽  
Academic Librarianship ◽  
Core Areas ◽  
Research Faculty

Over the past decade, evidence from disciplines ranging from biology to economics has suggested that many scientific studies may not be reproducible. This has led to declarations in both the scientific and lay press that science is experiencing a “reproducibility crisis” and that this crisis has consequences for the extent to which students, faculty, and the public at large can trust research. Faculty build on these results with their own research, and students and the public use these results for everything from patient care to public policy. To build a model for how academic libraries can support reproducible research, the authors conducted a review of major guidelines from funders, publishers, and professional societies. Specific recommendations were extracted from guidelines and compared with existing academic library services and librarian expertise. The authors believe this review shows that many of the recommendations for improving reproducibility are core areas of academic librarianship, including data management, scholarly communication, and methodological support for systematic reviews and data-intensive research. By increasing our knowledge of disciplinary, journal, funder, and society perspectives on reproducibility, and reframing existing librarian expertise and services, academic librarians will be well positioned to be leaders in supporting reproducible research. Citation: Sayre F., Riegelman A. Replicable services for reproducible research: a model for academic libraries.

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.

Principles and practice in impact assessment for academic libraries

2018 ◽  
Vol 119 (1/2) ◽  
pp. 121-134 ◽  
Author(s):  
Christine Urquhart
Keyword(s):  
Performance Evaluation ◽  
Impact Assessment ◽  
Academic Libraries ◽  
Data Analytics ◽  
Open Data ◽  
Library Services ◽  
Content Type ◽  
Qualitative And Quantitative ◽  
Library Assessment ◽  
And Performance

Purpose This paper aims to examine the principles that underpin library assessment, methods used for impact and performance evaluation and how academic libraries should use the findings, and it discusses how value frameworks help. Design/methodology/approach This is a literature review covering aspects of value (value propositions, value co-creation), value frameworks (including the 2015 ACRL framework, Holbrook typology with worked example), data analytics and collaborative projects including LibQUAL+ initiatives and the use of balanced scorecard principles (including a values scorecard). Findings The use of data analytics in library assessment requires collaboration among library services to develop reliable data sets. Scorecards help ongoing impact and performance evaluation. Queries that arise may require a framework, or logic model, to formulate suitable questions and assemble evidence (qualitative and quantitative) to answer new questions about the value of library services. The perceived value framework of Holbrook’s typology, the values scorecard and the ACRL framework all support the deeper level of inquiry required. Research limitations/implications Includes examples of possible application of frameworks. Practical implications A value framework might help data analytic approaches in combining qualitative and quantitative data. Social implications Impact assessment may require assessing how value is co-created with library users in use of e-resources and open data. Originality/value The study contrasts the varying approaches to impact evaluation and library assessment in academic libraries, and it examines more in-depth value frameworks.

Opportunities and Implementation of Big Data Management in Academic Libraries

2021 ◽  
pp. 35-47
Author(s):  
Mahesh G. T. ◽  
Nandeesha B.
Keyword(s):  
Big Data ◽  
Data Management ◽  
Academic Libraries ◽  
Strong Association ◽  
Karnataka State ◽  
The World ◽  
The Government ◽  
Associated Data

Data has changed the world in an unbelievable way and made an impact on our lifestyles at an exceptional rate. Big data is now the latest science of exploring and forecasting human-machine behavior dealing with a massive amount of associated data. The study is intended to understand the intensity and the competencies of librarians in implementing big data initiative project in academic libraries by the Government of Karnataka State. The study also tries to understand the application of big data in these libraries; 68 (87.17%) librarians completed the survey out of 78 respondents. The results of the study showed a strong association, that is, 72 (92.30%) respondents had the essential competencies and 58 (75.64%) librarians ability, intensity, readiness in implementing big data in academic libraries.

Readiness of academic libraries in South Africa to research, teaching and learning support in the Fourth Industrial Revolution

2020 ◽  
Vol 41 (6/7) ◽  
pp. 355-368 ◽  
Author(s):  
Dennis N. Ocholla ◽  
Lyudmila Ocholla
Keyword(s):  
South Africa ◽  
Conceptual Framework ◽  
Information Literacy ◽  
Academic Libraries ◽  
Industrial Revolution ◽  
Academic Library ◽  
Theory And Practice ◽  
Library Services ◽  
Content Type ◽  
Fourth Industrial Revolution

PurposeIn this paper, we refer to the World Economic Forum in Davos, Switzerland, in 2016, where the concept of the Fourth Industrial Revolution (4IR) was coined by Klaus Schwab, with the reference that it would be building on “the Third, the digital revolution” and would be “characterized by a fusion of technologies that is blurring the lines between the physical, digital, and biological spheres”. While acknowledging that the 4IR will impact on everything, everywhere, including research and libraries, we conceptualize 4IR, and we compare current academic library services/trends in South Africa with 4IR requirements, through the analysis of 26 public university library websites.Design/methodology/approachBesides conceptualization of 4IR, a content analysis of websites of 26 public universities’ libraries in South Africa was achieved followed up with verification of the data by respective libraries through a preliminary research report circulated to them by email. 23 areas were identified as the trends in academic libraries, which included free Wi-Fi in the libraries; 24/7 study areas and access to library resources on and off campus; research commons; makerspace; borrowing ICTs (e.g. laptops); e-resources; e-catalogues; research data services (RDS; RDM, IR); open scholarship; information literacy and reference/bibliographic tools, library as a publisher, among others. Data obtained were captured in Excel and analyzed by the research questions.FindingsThe 4IR concept does not occur often in literature, in relation to academic libraries, but it is implied. The findings show that the libraries are responding well to the revolution through their services, with remarkable innovation and creativity on display. There was a 64% presence of the analyzed trends/services in the libraries, with emerging trends/services such as library as a publisher (4%), robotics/AI (4%), makerspace (8%), RDS (27%), borrowing of ICTs/devices (19%) and user experience (19%) scoring low, while information literacy and digital scholarship (e.g. IR) (88%), e-catalogue and e-resources (92%), group study area (85%) and off campus access (77%) scoring above 75%. The scatter of the trends/services among the university libraries is noted for knowledge sharing of best practice.Research limitations/implicationsIn order to improve accordance with trends, academic libraries have to be better resourced, accessed and used, as well as improve web visibility. The study expects library services to be responsive, resourced and accessible anytime and anywhere, and it provides a conceptual framework and a benchmark for further research and exploration in the country, region and perhaps elsewhere.Practical implicationsThe study can be used for benchmarking current and future academic library services in Africa. The conceptual framework provides an agenda for theoretical discussions and deliberations.Social implicationsThe trends, framework and 4IR representations in the study can inform theory and practice in LIS, particularly in Africa.Originality/valueLinking 4IR to current and future library services provides a tool for academic libraries services benchmarking and development and provides a conceptual framework for theoretical and practical debates and implementation. The study is quite current and appropriate for the ongoing discussions of 4IR implications to academic libraries.

Estimation of the knowledge management model for performance measurement in university libraries

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Muhammad Rafi ◽  
Zheng Jian Ming ◽  
Khurshid Ahmad
Keyword(s):  
Knowledge Management ◽  
Performance Evaluation ◽  
Academic Libraries ◽  
Structural Equation ◽  
Academic Library ◽  
Academic Community ◽  
Assessment Model ◽  
Management Model ◽  
Library Services ◽  
Content Type

PurposeThe study aims to expand the literature on evaluating the performance of professionals and academic libraries, rationalizing management and providing reliable services to the academic community. The performance assessment model covers the four components (management competence, professional experience, financial add/projects and library services) in the context of the knowledge management model.Design/methodology/approachBased on quantitative data, the study defines a set of assumptions for testing the four components of performance evaluation within a knowledge management framework to develop appropriate and robust models for improving employee performance and library services. The structural equation model has been applied to sample data from 339 administrative librarians at 190 universities in Pakistan.FindingsStatistical evidence confirms that the applicability of the proposed performance-based model enhances management competence, makes accurate decisions, develops professional skills and strengthens human resource organization and knowledge management techniques in developing the efficiency of academic libraries.Practical implicationsIn the long term, academic leaders and policymakers value investment in the professional development of top library management as they participate in the decision-making process. Organizing training for service employees, supporting innovative research projects and providing library technology infrastructures ultimately improve academic performance and research when integrated into the knowledge management model.Originality/valueSo far, comprehensive literature on performance and knowledge management has been published separately. However, based on the key data collected by senior library administrators using the structured research questionnaire, the comprehensive performance evaluation research based on a knowledge management model is innovative to improve academic library services and close the literature gap.

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