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One of the most critical changes to academic library services in the last decade has been the development and implementation of research data services (RDS). This paper seeks to provide a comprehensive understanding of conceptual models for the RDS space.

An extensive and comprehensive review of the literature on conceptual models for RDS is performed.

Various conceptual models for RDS provide a compelling tool for guiding and evaluating RDS development and implementation within academic libraries.

An insightful review and synthesis of context and issues in RDS models will help academic libraries to plan, develop and advance their RDS.

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.

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.

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.

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.

Advances in Big Data, artificial Intelligence and data-driven innovation bring enormous benefits for the overall society and for different sectors. By contrast, their misuse can lead to data workflows bypassing the intent of privacy and data protection law, as well as of ethical mandates. It may be referred to as the ‘creep factor’ of Big Data, and needs to be tackled right away, especially considering that we are moving towards the ‘datafication’ of society, where devices to capture, collect, store and process data are becoming ever-cheaper and faster, whilst the computational power is continuously increasing. If using Big Data in truly anonymisable ways, within an ethically sound and societally focussed framework, is capable of acting as an enabler of sustainable development, using Big Data outside such a framework poses a number of threats, potential hurdles and multiple ethical challenges. Some examples are the impact on privacy caused by new surveillance tools and data gathering techniques, including also group privacy, high-tech profiling, automated decision making and discriminatory practices. In our society, everything can be given a score and critical life changing opportunities are increasingly determined by such scoring systems, often obtained through secret predictive algorithms applied to data to determine who has value. It is therefore essential to guarantee the fairness and accurateness of such scoring systems and that the decisions relying upon them are realised in a legal and ethical manner, avoiding the risk of stigmatisation capable of affecting individuals’ opportunities. Likewise, it is necessary to prevent the so-called ‘social cooling’. This represents the long-term negative side effects of the data-driven innovation, in particular of such scoring systems and of the reputation economy. It is reflected in terms, for instance, of self-censorship, risk-aversion and lack of exercise of free speech generated by increasingly intrusive Big Data practices lacking an ethical foundation. Another key ethics dimension pertains to human-data interaction in Internet of Things (IoT) environments, which is increasing the volume of data collected, the speed of the process and the variety of data sources. It is urgent to further investigate aspects like the ‘ownership’ of data and other hurdles, especially considering that the regulatory landscape is developing at a much slower pace than IoT and the evolution of Big Data technologies. These are only some examples of the issues and consequences that Big Data raise, which require adequate measures in response to the ‘data trust deficit’, moving not towards the prohibition of the collection of data but rather towards the identification and prohibition of their misuse and unfair behaviours and treatments, once government and companies have such data. At the same time, the debate should further investigate ‘data altruism’, deepening how the increasing amounts of data in our society can be concretely used for public good and the best implementation modalities.

This paper aims to outline the information management principles of the so‐called “new science”, and to attempt to put these in the context of traditional library and information science principles.

A brief review of some work in the area, in particular focusing on the work show‐cased by the annual digital preservation conference series hosted by the Digital Curation Centre in Scotland (www.dcc.ac.uk/).

There is a danger that scientists (as opposed to LIS professionals) will apply the information management techniques of the new science to their own activities inappropriately, especially to research that is best curated as “old” not new science. This is something on which information professionals are well placed to give advice and make judgements.

More practice‐oriented research is needed to enhance understanding of how traditional librarianship practices can be applied to the data‐intensive scientific research carried out by so‐called “virtual organisations”.

This paper makes some initial suggestions about the how the tools of library and information practice can be related to the “new science”. In particular, it highlights their relevance to distinguishing between the information management needs of the “old” and the “new” sciences: these needs are quite distinct, though easily confused.

This paper relates terms from pure science such as the virtual organisation, cyberinfrastructure, and e‐Science to traditional LIS concepts, and tries to create an understanding of the relationship between the two disciplines for the library practitioner.

The purpose of this paper is to identify tasks and roles that academic libraries have to fulfil to react to the developments brought in by the appearance of Research 2.0.

A review of current literature about the topic was performed.

Literature used reveals that currently, there is a need for providing information literacy (IL) education (mainly in the form of data literacy), providing research data services (RDSs) (addressing data quality and data citation), raising awareness of faculty members on different issues and providing individual support to them.

The paper intends to be an add-on to the body of knowledge about academic library support to researchers.

The massive increase in research data being produced nowadays has highlighted the importance of research data management (RDM) to science. Research data not only have to be cost effective but also reliable, discoverable, accessible, and reusable. In this regard, the purpose of this paper is to investigate the perceptions and practices of Turkish researchers on the subject of RDM.

An online survey was distributed to the academicians in 25 universities in Turkey, and 532 responses were gathered.

Results indicate that although Turkish researchers are aware of the benefits of data management, are willing to share their research data with certain groups, and have decent preservation habits, they express that they lack the technical skills and knowledge needed for RDM. In addition, no institutionalized support (staff, training, software, and hardware) is provided to researchers.

A well-structured data strategy or policy that includes resource allocation (awareness, training, software/hardware) and is supported by Turkish research agencies is required for better data management practices among researchers in Turkey.

This is the first study that investigates the data practices of Turkish academics who produce around 30,000 scientific articles annually that are indexed by Web of Science. It contributes to the growing literature on RDM.

The aim is to report on the 175th Annual Meeting of the American Association for the Advancement of Science (AAAS), held in February 2009 in Chicago.

Provides a concise review of the conference, whose theme was Our Planet and Its Life: Origins and Futures.

Not surprisingly, because of the primary focus on Darwin and the ecology of the earth, there were few symposia that concentrated on the application of technology outside of the Life Sciences and of the Earth Sciences. However, in view of the current evolution of “cloud computing” and the formation of “mega grids,” there were two symposia devoted to these topics.

The paper is a useful summary of a conference of interest to library and information management professionals.

Because of online digital resources, academic libraries no longer need to spend as much time and energy organizing their own collections as they used to. They now have an opportunity to pivot their expertise in organizing information outward. “Inside-out” library services can include support for special collections, digital scholarship, scholarly communication, and data management. A key characteristic of such services is that an academic library takes on broader information management challenges at their college or university. This chapter will examine what it takes to build successful inside-out library services by looking at their cost, how well they complement existing library expertise and culture, and their impact on teaching, research, and the wider community.

In today's global and competitive corporate environment characterised by rapidly changing information, knowledge and technology (IKT), researchers must be upskilled in all aspects of research data management (RDM). This study investigates a set of capabilities and competencies required by researchers at selected South African public universities, using the community capability model framework (CCMF) in conjunction with the digital curation centre (DCC) lifecycle model.

The post-positivist paradigm was used in the study, which used both qualitative and quantitative methodologies. Case studies, both qualitative and quantitative, were used as research methods. Because of the COVID-19 pandemic rules and regulations, semi-structured interviews with 23 study participants were conducted online via Microsoft Teams to collect qualitative data, and questionnaires were converted into Google Forms and emailed to 30 National Research Foundation (NRF)-rated researchers to collect quantitative data.

Participating institutions are still in the initial stages of providing RDM services. Most researchers are unaware of how long their institutions retain research data, and they store and backup their research data on personal computers, emails and external storage devices. Data management, research methodology, data curation, metadata skills and technical skills are critically important RDM competency requirements for both staff and researchers. Adequate infrastructure, as well as human resources and capital, are in short supply. There are no specific capacity-building programmes or strategies for developing RDM skills at the moment, and a lack of data curation skills is a major challenge in providing RDM.

The findings of the study can be applied widely in research, teaching and learning. Furthermore, the research could help shape RDM strategy and policy in South Africa and elsewhere.

The scope, subject matter and application of this study contribute to its originality and novelty.

The purpose of this paper is to boost multidisciplinary research by the building of an integrated catalogue or research assets metadata. Such an integrated catalogue should enable researchers to solve problems or analyse phenomena that require a view across several scientific domains.

There are two main approaches for integrating metadata catalogues provided by different e-science research infrastructures (e-RIs): centralised and distributed. The authors decided to implement a central metadata catalogue that describes, provides access to and records actions on the assets of a number of e-RIs participating in the system. The authors chose the CERIF data model for description of assets available via the integrated catalogue. Analysis of popular metadata formats used in e-RIs has been conducted, and mappings between popular formats and the CERIF data model have been defined using an XML-based tool for description and automatic execution of mappings.

An integrated catalogue of research assets metadata has been created. Metadata from e-RIs supporting Dublin Core, ISO 19139, DCAT-AP, EPOS-DCAT-AP, OIL-E and CKAN formats can be integrated into the catalogue. Metadata are stored in CERIF RDF in the integrated catalogue. A web portal for searching this catalogue has been implemented.

Only five formats are supported at this moment. However, description of mappings between other source formats and the target CERIF format can be defined in the future using the 3M tool, an XML-based tool for describing X3ML mappings that can then be automatically executed on XML metadata records. The approach and best practices described in this paper can thus be applied in future mappings between other metadata formats.

The integrated catalogue is a part of the eVRE prototype, which is a result of the VRE4EIC H2020 project.

The integrated catalogue should boost the performance of multi-disciplinary research; thus it has the potential to enhance the practice of data science and so contribute to an increasingly knowledge-based society.

A novel approach for creation of the integrated catalogue has been defined and implemented. The approach includes definition of mappings between various formats. Defined mappings are effective and shareable.