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Data librarianship and the role of the data librarian are an established reality in many countries, even though at different levels. Particularly, academic librarians have been involved in research data management for a long time and this role is acquiring precise features. In Italy, the data librarian is a figure still to be built and defined. The aim of the article is to offer a first systematic exploration in the fields of data librarianship and the role of the data librarian, both in their practical (what activities) and methodological (how activities are performed) features. The hope is to encourage the beginning of a necessary reflection on these topics. [Publisher's text]

[Purpose/Significance] The research paradigm is gradually shifting towards a data-intensive model, where research data has become the cornerstone in the realm of academic endeavors. Effective research data management can enhance the research efficiency of scientific researchers, reduce redundant data collection, and reduce costs. As a central repository for the storage of scholarly research outputs, it is essential that university institutional repositories fulfill their role in research data management. [Method/Process] To gain a full understanding of the evolving landscape, we embarked on a meticulous network-based research investigation. We specifically selected the institutional repositories of 24 prestigious American universities as our research subjects, with the aim of exploring the diverse range of services they provide at different stages of the research lifecycle. Our research was firmly grounded in the data lifecycle framework, which enabled us to systematically examine a wide range of research data management (RDM) services. This included critical aspects such as developing comprehensive research data management plans, establishing robust data organization services and standardized protocols, providing reliable long-term data storage solutions to ensure continued accessibility, enhancing data sharing policies to foster collaboration, strengthening research data quality control measures to maintain integrity, and developing comprehensive research data management training programs to empower researchers. Furthermore, we conducted an in-depth analysis to summarize the characteristics and valuable experiences of American universities in building and maintaining the basic infrastructure of their institutional repositories. [Results/Conclusions] Given the unique circumstances of China's modernization process, this paper distills effective insights and strategies from the institutional repositories of domestic university libraries in the field of research data management services. Our findings highlight the importance of building a localized research data management platform tailored to the specific needs and contexts of Chinese academia. Enhancing the quality of research data management is critical to building a trusted institutional knowledge base and fostering an environment of credibility and reliability. By applying the FAIR (Findable, Accessible, Interoperable, Reusable) and TRUST (Transparent, Responsible, Usable, Sustainable, and Trustworthy) principles, we can facilitate the open and seamless sharing of research data, breaking down barriers to collaboration and innovation. Finally, building a professional scientific research data management team is essential to provide the human capital necessary to navigate the complexities of data management and to promote the development and adoption of best practices in scientific research data sharing. Taken together, these findings help to improve the abiity of the scientific community to harness the full potential of research data to drive the creation and dissemination of knowledge.

In this unique guide, two collection development experts show how to use Excel® to translate circulation and collection data into meaningful reports for making collection management decisions. Step-by-step instructions accompanied by screen shots allow anyone to use Excel® to quickly “crunch the numbers” that often bog down library use studies. Analyzing Library Collection Use with Excel® gives library collection analysts the ready tools to -- Process raw data into usable information -- Understand the varieties of possible analyses -- Identify the most relevant types of analysis for their collections -- Identify weaknesses and build on the strengths identified in their collections -- Illustrate circulation data using charts and graphs This hands-on guide shows how to set up customized spreadsheets and processes all data into usable summaries. Librarians responsible for collection development in public, school, academic, and special libraries will learn why analyzing collection use is important and how they can analyze that use to better serve their patrons.

The scientific connotation, strategic considerations and practical ways of \"new quality productive forces\" have received wide attention from the political, academic and industrial circles. Cultivating and developing new quality productive forces means fundamentally changing the mode of production. It is necessary to grasp the practical direction of new quality productive forces from their scientific connotation and internal logic, and explore the scientific way of cultivating and developing the new quality productive forces from China's national conditions. As an important engine of economic development in the new era, its connotation characteristics, development path, opportunities and challenges are worthy of further discussion. For this reason, seven experts were invited to share their perspectives. 1) The deep logic and realization path of the construction of new quality productive forces and high-quality data resources. This paper discusses in depth the background and connotation characteristics of the high-quality data resources, and analyzes the internal logic of the mutual promotion between high-quality data resources and the development of new quality productivity. It is proposed that the construction of high-quality data resources must implement the concepts of innovation, coordination, openness, credibility and sustainability, and follow the construction strategies of concept innovation, model innovation, structural innovation and technological innovation. 2) The theoretical logic and practical path of data elements empowering new quality productive forces. In the new era of green and intelligent development, there is a profound dialectical relationship between data elements and new quality productive forces, and a new situation of economic and social development is accelerated in the spiral ascent of complementarity. We should comprehensively build a data space governance model with clear data ownership, smooth data path, guaranteed data quality and orderly and standardized algorithm computing power, expand new quality production capacity and production factors with the goal of human-machine cooperation and promote sustainable economic and social development. 3) Accelerating the promotion of data rights. Data can act on new quality productive forces from the technical, factor and industrial dimensions, and accelerate the formation of new quality productive forces. The multiplier effect of data elements on new quality productive forces will involve many dimensions, levels and stages, the most important and fundamental of which is how to determine the ownership of data. The measures for speeding up the promotion of new quality productive forces are discussed, such as constructing the theory of property rights in accordance with the characteristics of data and the law of development of new quality productive forces, speeding up the clarification of the types and scope of data confirmation, and improving the supporting system of data confirmation. 4) Promoting China's modernization path with Chinese-style digitization. Accelerating the promotion of Chinese-style digitization is not only the only way to realize Chinese-style modernization, but also the core to fully release new quality productive forces and build China's asymmetric competitive advantage under the new situation. It is suggested that in the process of digitalization and informatization in China, the information resource management industry plays a vital role and bears the important responsibility of digital transformation. 5) Interpreting the mission of public libraries from the perspective of new quality productive forces. Since its establishment, public libraries have been based on the concept of enlightenment. Faced with the profound digital transformation of society, today's public libraries need to further develop the potential of empowering the people in the field of digital economy and make them play an active role in the development of new quality productive forces. Public libraries need to further develop their potential to empower people in the field of digital economy, so that they can play an active role in the development of new quality productive forces. They should actively participate in data commercialization, promote the effective use of data elements and the efficiency of resource allocation, and enable more people to obtain and use data elements equally through open access and digital services. 6) The intelligent transformation of university libraries from the perspective of new quality productive forces. In the process of developing new quality productive forces, we should fully understand the profound meaning of new productive forces, based on the core tasks of providing a strong guarantee for the development of new quality productive forces in higher education, grasp the development opportunities, and realize the high-quality development of the industry. This paper explains the understanding of university libraries on the three key words of new quality productive forces, and proposes that the re-understanding and realization of library intelligence is an important starting point for the development of new productive forces. 7) To support information resource management discipline to accelerate the development of new quality productive forces. From the perspective of information resource management discipline, this paper analyzes several aspects of \"doing something\" under the rise of new quality productivity concept, including theoretical system, information resource guarantee, information analysis and consultation, scenario building, knowledge popularization and civic literacy cultivation. The content of academic evaluation, information policy, intellectual property rights, digital consumption behavior and other directions related to new quality productivity are also important directions that the discipline needs to pay attention to.

[Purpose/Significance] Universities are important institutions for the creation and use of research data. However, how to organize, manage and reuse research data has become a challenging task for universtiy researchers. At present, Chinese university libraries and research institutes have become an important part of institutional repository (IR) construction. Of studies on IR construction by university libraries, there are few cases of embedding research data management (RDM) into IR functions for data preservation and sharing. The relevant theories and practices are still in the exploratory stage and have not been popularized. Therefore, through the investigation of the construction of Japanese IRs for research resource management, some experience is summarized, including the concept of data life cycle management, the optimization of data management policies, and the establishment of a scientific data management platform are applied to the management of scientific data generated by university researchers, the construction of a professional social science data platform for application research, and the conversion of data from decentralized storage to centralized storage and public release, in order to promote academic exchanges and provide innovative services. [Method/Process] IR platforms of 18 university libraries in Japan were selected as the sample. According to the life cycle of \"collection - preservation - reuse\" of RDM, the characteristics and experience of service construction were summarized from the aspects of RDM content, planning service, policies, and training courses. [Results/Conclusions] The enlightenment for the IRs of Chinese university libraries in their RDM service is summarized as follows: using the data life cycle to carry out the RDM service, optimizing data management policies, formulating RDM norms, developing data management courses, improving data management ability, raising the awareness of RDM among researchers, and paying attention to the training of RDM professionals. This study has several limiations. First, the survey data are not comprehensive enough. This paper only investigated IRs of some university libraries in Japan. Second, the research on the reuse of research data in Chinese universities is not comprehensive enough. Our future research will focus on the value-added development, reuse and sharing of research data.

PurposeThe study aims to identify the prospects and challenges associated with current practices regarding digital data sets management in university libraries in Pakistan.Design/methodology/approachA cross-sectional survey approach was used to collect the data from library and information science (LIS) professionals working in public sector university libraries in Pakistan. A four-part questionnaire was used to collect the data from the respondents. The collected data from 371 participants were analyzed using a statistical package for social sciences (SPSS-24 version) and analysis of moment structure (AMOS-24).FindingsLIS professionals are better placed to support digital data management practices, such as finding, collecting, assessing and analyzing digital data sets and making digital data publicly discoverable and accessible via open access. In spite of this, a lack of leadership support, interest and cooperation among university departments and the absence of a data management plan, policies and procedures were reported as significant challenges.Practical implicationsTo meet the needs of data users, LIS professionals must become knowledgeable about managing and reusing digital data sets. Due to the demands of the information society, university librarians need to learn about data-centric practices that can enhance research outputs and provide new insights.Originality/valueThis research paper is extracted from a PhD dissertation to present a contemporary picture of library data management services and the challenges LIS professionals face to provide possible solutions.

[Purpose/Significance] The biomedical research field is suffering from reproducibility crisis, which has become one of important issues under the background of the rise of the data-intensive research paradigm. As one of the most important attributes of scientific research by empirical data study,reproducibility needs to be improved by good data practices of researchers. How to effectively improve the data literacy of researchers has become the key point to solve the crisis. However, the relevant research is basically in the blank condition. The paper aims to establish a new data literacy education system for reproducibility crisis, in order to fill the current research gap and provide reference for implementing the relevant education in our country. [Method/Process] Firstly, the paper clarifies the relationship between reproducibility crisis and data literacy by using content analysis: the inappropriate data behavior of researchers may bring serious problems in many respects, such as research data, methods, process, environments and results, which could eventually lead to the irreproducible research. Then, we redefine the concept of data literacy education. Secondly, based on the summarization of the existing foreign research results and practice, the paper builds the Reproducibility Data Literacy Education (Re-DLE) system from the perspective of educational goals and content, subjects and objects, teaching methods, implementation strategies, and evaluation. At last, it proposes the necessary guarantee factors for the operation of the system. [Results/Conclusions] The ultimate goal of Re-DLE is to improve research reproducibility, bulid the educational content framework on the theory of data life cycle, and divide the main content into three dimensions: re-data awareness, re-data skills, and re-data ethics, each of which includes some clear educational objectives, subject modules and detailed instructions Medical libraries have a wealth of teaching experience and should become the educational main body for the broader biomedical research community. the establishment of diversified training methods, diversified teaching strategies and evaluation methods, in other words, we need to strengthen the team building of teaching librarians, consolidate the educational resources foundation, promote educational exchanges, and improve the internal and external cooperative system, so as to push forward the building of the Re-DLE system. The research results of this paper not only can be seen as a theoretical breakthrough, but also provide the theory basis for the development and implementation of education. In addition, due to the limitation of methods, the paper can be used as a qualitative research, which still has some problems to be solved. In the future work, we need to build more scientific and effective Re-DLE system by using empirical research methods.

Data use in the library has specific characteristics and common problems.Data Clean-up and Management addresses these, and provides methods to clean up frequently-occurring data problems using readily-available applications.

Drawing on the expertise of a diverse community of practitioners, this collection of case studies, original research, survey chapters, and theoretical explorations presents a wide-ranging look at the field of academic data librarianship.