Search results

1 – 10 of over 58000
Article
Publication date: 5 May 2022

Dee Birnbaum and Mark Somers

The purpose of this paper is to explore parallels between scientific management and the new scientific management to gain insight into applications of machine learning and…

Abstract

Purpose

The purpose of this paper is to explore parallels between scientific management and the new scientific management to gain insight into applications of machine learning and artificial intelligence (AI) to human resource management and employee assessment.

Design/methodology/approach

Analysis of Taylor’s work and its interpretation by scholars is contrasted with modern analysis of human resource analytics to demonstrate conceptual and methodological commonalities between the old and the new forms of scientific management.

Findings

The analysis demonstrates how the epistemology, ethos and cultural trajectory of scientific management has resulted in a mindset that has influenced the implementation and objectives of the new scientific management with respect to human resources analytics.

Social implications

This paper offers an alternative to the view that machine learning and AI as applied to work and employees are beneficial and points out why important challenges have been overlooked and how they can be addressed.

Originality/value

Commonalties between Taylorism and the new scientific management have been overlooked so that attempts to gain an understanding of how machine learning is likely to influence work, employees and work organizations are incomplete. This paper provides a new perspective that can be used to address challenges associated with applications of machine learning to work design and employee rights.

Details

International Journal of Organizational Analysis, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1934-8835

Keywords

Article
Publication date: 18 November 2013

Li Si, Xiaozhe Zhuang, Wenming Xing and Weining Guo

This article aims to summarize the employers' requirements of scientific data specialists and the status quo of LIS education organizations' training system for scientific

1549

Abstract

Purpose

This article aims to summarize the employers' requirements of scientific data specialists and the status quo of LIS education organizations' training system for scientific data specialists. It also focuses on the matching analysis between the course content and the responsibilities as well as requirements of scientific data specialists. Moreover, in order to provide some indications for LIS education of scientific data specialists in China, it presents the training objectives and modes.

Design/methodology/approach

Some job portals for librarians and the comprehensive job portals are investigated as information sources and the keywords such as “scientific data management”, “data service”, “data curation”, “e-Science”, “e-Research”, “data specialist” are selected to retrieval library-released job advertisements for scientific data specialists to understand the library's requirements towards scientific data specialists' core capabilities. Meanwhile the course catalogues of all iSchools' web sites are searched directly in order to find if scientific data courses are provided.

Findings

Libraries value teamwork ability, communication ability, interpersonal ability and a good use of data curation tools as the core competences for scientific data specialists. Candidates who possess a second advanced degree, who understand libraries, who hold demonstrated knowledge of metadata standards, and who emphasize details, under the same condition, are more likely to be considered first. Libraries do not have a unified title for scientific data specialists yet. The current curriculums of iSchools mainly cover research method, data science, data management and data service, data statistic and analysis, data warehouse, information studies and technologies, and so on.

Originality/value

This unique study explores some required qualifications of science data specialist surveyed by job openings, including the core skills, position requirements, responsibilities of the job, and some qualifications. It also investigates the related curriculum setting of iSchool universities through course descriptions. This study is very useful for curriculum development in Chinese LIS education of scientific data specialists including required core courses and selected electives, and to promote the practice of data service in Chinese academic libraries.

Details

Library Hi Tech, vol. 31 no. 4
Type: Research Article
ISSN: 0737-8831

Keywords

Article
Publication date: 21 April 2022

Wei Zong, Songtao Lin, Yuxing Gao and Yanying Yan

This paper aims to provide a process-driven scientific data quality (DQ) monitoring framework by information product map (IP-Map) in identifying the root causes of poor DQ…

Abstract

Purpose

This paper aims to provide a process-driven scientific data quality (DQ) monitoring framework by information product map (IP-Map) in identifying the root causes of poor DQ issues so as to assure the quality of scientific data.

Design/methodology/approach

First, a general scientific data life cycle model is constructed based on eight classical models and 37 researchers’ experience. Then, the IP-Map is constructed to visualize the scientific data manufacturing process. After that, the potential deficiencies that may arise and DQ issues are examined from the aspects of process and data stakeholders. Finally, the corresponding strategies for improving scientific DQ are put forward.

Findings

The scientific data manufacturing process and data stakeholders’ responsibilities could be clearly visualized by the IP-Map. The proposed process-driven framework is helpful in clarifying the root causes of DQ vulnerabilities in scientific data.

Research limitations/implications

As for the implications for researchers, the process-driven framework proposed in this paper provides a better understanding of scientific DQ issues during implementing a research project as well as providing a useful method to analyse those DQ issues based on IP-Map approach from the aspects of process and data stakeholders.

Practical implications

The process-driven framework is beneficial for the research institutions, scientific data management centres and researchers to better manage the scientific data manufacturing process and solve the scientific DQ issues.

Originality/value

This research proposes a general scientific data life cycle model and further provides a process-driven scientific DQ monitoring framework for identifying the root causes of poor data issues from the aspects of process and stakeholders which have been ignored by existing information technology-driven solutions. This study is likely to lead to an improved approach to assuring the scientific DQ and is applicable in different research fields.

Details

The Electronic Library , vol. 40 no. 3
Type: Research Article
ISSN: 0264-0473

Keywords

Article
Publication date: 1 June 2015

Li Si, Wenming Xing, Xiaozhe Zhuang, Xiaoqin Hua and Limei Zhou

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…

2770

Abstract

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.

Details

The Electronic Library, vol. 33 no. 3
Type: Research Article
ISSN: 0264-0473

Keywords

Article
Publication date: 17 July 2017

Rebecca Grant

The purpose of this paper is to explore a range of perspectives on the relationship between research data and records and between recordkeeping and research data management.

3710

Abstract

Purpose

The purpose of this paper is to explore a range of perspectives on the relationship between research data and records and between recordkeeping and research data management.

Design/methodology/approach

This paper discusses literature in the field of research data management as part of preliminary work for the author’s doctoral research on the topic. The literature included in the review reflects contemporary and historical perspectives on the management and preservation of research data.

Findings

Preliminary findings indicate that records professionals have been involved in the management and preservation of research data since the early twentieth century. In the literature, research data is described as comparable to records, and records professionals are widely acknowledged to have skills and expertise which are applicable to research data management. Records professionals are one of a number of professions addressing research data management. However, they are not currently considered to be leaders in research data management practice.

Originality/value

Research data management is an emerging challenge as stakeholders in the research lifecycle increasingly mandate the publication of open, transparent research. Recent developments such as the publication of the OCLC report “The Archival Advantage: Integrating Archival Expertise into Management of Born-digital Library Materials”, and the creation of the Research Data Alliance Interest Group Archives and Records Professionals for Research Data indicates that research data is, or can be, within the remit of records professionals. This paper represents a snapshot of contemporary and historical attitudes towards research data and recordkeeping and thus contributes to this emerging area of discussion.

Details

Records Management Journal, vol. 27 no. 2
Type: Research Article
ISSN: 0956-5698

Keywords

Article
Publication date: 13 October 2020

Sirje Virkus and Emmanouel Garoufallou

The purpose of this paper is to present the results of a study exploring the emerging field of data science from the library and information science (LIS) perspective.

1735

Abstract

Purpose

The purpose of this paper is to present the results of a study exploring the emerging field of data science from the library and information science (LIS) perspective.

Design/methodology/approach

Content analysis of research publications on data science was made of papers published in the Web of Science database to identify the main themes discussed in the publications from the LIS perspective.

Findings

A content analysis of 80 publications is presented. The articles belonged to the six broad categories: data science education and training; knowledge and skills of the data professional; the role of libraries and librarians in the data science movement; tools, techniques and applications of data science; data science from the knowledge management perspective; and data science from the perspective of health sciences. The category of tools, techniques and applications of data science was most addressed by the authors, followed by data science from the perspective of health sciences, data science education and training and knowledge and skills of the data professional. However, several publications fell into several categories because these topics were closely related.

Research limitations/implications

Only publication recorded in the Web of Science database and with the term “data science” in the topic area were analyzed. Therefore, several relevant studies are not discussed in this paper that either were related to other keywords such as “e-science”, “e-research”, “data service”, “data curation”, “research data management” or “scientific data management” or were not present in the Web of Science database.

Originality/value

The paper provides the first exploration by content analysis of the field of data science from the perspective of the LIS.

Details

Data Technologies and Applications, vol. 54 no. 5
Type: Research Article
ISSN: 2514-9288

Keywords

Article
Publication date: 5 May 2021

Dumitru Roman, Neal Reeves, Esteban Gonzalez, Irene Celino, Shady Abd El Kader, Philip Turk, Ahmet Soylu, Oscar Corcho, Raquel Cedazo, Gloria Re Calegari, Damiano Scandolari and Elena Simperl

Citizen Science – public participation in scientific projects – is becoming a global practice engaging volunteer participants, often non-scientists, with scientific

Abstract

Purpose

Citizen Science – public participation in scientific projects – is becoming a global practice engaging volunteer participants, often non-scientists, with scientific research. Citizen Science is facing major challenges, such as quality and consistency, to reap open the full potential of its outputs and outcomes, including data, software and results. In this context, the principles put forth by Data Science and Open Science domains are essential for alleviating these challenges, which have been addressed at length in these domains. The purpose of this study is to explore the extent to which Citizen Science initiatives capitalise on Data Science and Open Science principles.

Design/methodology/approach

The authors analysed 48 Citizen Science projects related to pollution and its effects. They compared each project against a set of Data Science and Open Science indicators, exploring how each project defines, collects, analyses and exploits data to present results and contribute to knowledge.

Findings

The results indicate several shortcomings with respect to commonly accepted Data Science principles, including lack of a clear definition of research problems and limited description of data management and analysis processes, and Open Science principles, including lack of the necessary contextual information for reusing project outcomes.

Originality/value

In the light of this analysis, the authors provide a set of guidelines and recommendations for better adoption of Data Science and Open Science principles in Citizen Science projects, and introduce a software tool to support this adoption, with a focus on preparation of data management plans in Citizen Science projects.

Details

Data Technologies and Applications, vol. 55 no. 5
Type: Research Article
ISSN: 2514-9288

Keywords

Book part
Publication date: 24 September 2001

Robert M. Hayes

Abstract

Details

Models for Library Management, Decision Making and Planning
Type: Book
ISBN: 978-1-84950-792-9

Article
Publication date: 3 June 2020

Elisha R.T. Chiware

The paper presents a literature review on research data management services in African academic and research libraries on the backdrop of the advancing open science and…

Abstract

Purpose

The paper presents a literature review on research data management services in African academic and research libraries on the backdrop of the advancing open science and open research data infrastructures. It provides areas of focus for library to support open research data.

Design/methodology/approach

The literature analysis and future role of African libraries in research data management services were based on three areas as follows:open science, research infrastructures and open data infrastructures. Focussed literature searches were conducted across several electronic databases and discovery platforms, and a qualitative content analysis approach was used to explore the themes based on a coded list.

Findings

The review reports of an environment where open science in Africa is still at developmental stages. Research infrastructures face funding and technical challenges. Data management services are in formative stages with progress reported in a few countries where open science and research data management policies have emerged, cyber and data infrastructures are being developed and limited data librarianship courses are being taught.

Originality/value

The role of the academic and research libraries in Africa remains important in higher education and the national systems of research and innovation. Libraries should continue to align with institutional and national trends in response to the provision of data management services and as partners in the development of research infrastructures.

Details

Library Management, vol. 41 no. 6/7
Type: Research Article
ISSN: 0143-5124

Keywords

Article
Publication date: 25 August 2020

Xinyi Zhang, Yanni Yu and Ning Zhang

This study aims to provide a literature review and bibliometric analysis of sustainable supply chain management using big data. We reviewed the literature on sustainable…

1193

Abstract

Purpose

This study aims to provide a literature review and bibliometric analysis of sustainable supply chain management using big data. We reviewed the literature on sustainable supply chain management under big data from 2012 to 2019 and extracted 777 articles.

Design/methodology/approach

We conducted quantitative analysis and data network visualization of the chosen literature, including authors, journals, countries, research institutions and citations.

Findings

We discovered that the development of this interdisciplinary field has gained increasing popularity among researchers around the world, such as China and the US publishing the most articles and Western states having more cooperation, which indicates this research topic is growing in significance globally.

Originality/value

Scientific and technological revolutions such as big data have been incorporated in various industries. Modern supply chain management has also been combined with the advances in data science to achieve sustainability goals. No studies have reviewed the sustainable supply chain management based on big data. This study fills this gap.

Details

Journal of Enterprise Information Management, vol. 34 no. 1
Type: Research Article
ISSN: 1741-0398

Keywords

1 – 10 of over 58000