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This paper aims at understanding the current situation of research support services offered by academic libraries in world-leading universities and providing useful implications and insights for other academic libraries.

Of the top 100 universities listed in the QS World University Rankings in 2017, 76 libraries were selected as samples and a website investigation was conducted to explore the research support services. The statistical method and visualization software was used to generalize the key services, and the text analysis and case analysis were applied to reveal the corresponding implementation.

Research support service has become one of the significant services of academic libraries in the context of e-research and data-intensive research. The research support services can be generally divided into seven aspects, as follows: research data management (62, 81.58 per cent), open access (64, 84.21 per cent), scholarly publishing (59, 77.63 per cent), research impact measurement (32, 42.11 per cent), research guides (47, 61.84 per cent), research consultation (59, 77.63 per cent) and research tools recommendation (38, 50.00 per cent).

This paper makes a comprehensive investigation of research support services in academic libraries of top-ranking universities worldwide. The findings will help academic libraries improve research support services; thus, advancing the work of researchers and promoting scientific discovery.

This paper aims to analyse a set of converging trends underpinning a larger phenomenon called science 2.0 and to assess what are the most important implications for scientific method and research institutions.

It is based on a triangulation of exploratory methods which include a wide-ranging literature review, Web-based mapping and in-depth interviews with stakeholders.

The main implications of science 2.0 are enhanced efficiency, transparency and reliability; raise of data-driven science; microcontributions on a macroscale; multidimensional, immediate and multiform evaluation of science; disaggregation of the value chain of service providers for scientists; influx of multiple actors and the democratisation of science.

The paper rejects the notion of science 2.0 as the mere adoption of Web 2.0 technologies in science and puts forward an original integrated definition covering three trends that have not yet been analysed together: open science, citizens science and data-intensive science. It argues that these trends are mutually reinforcing and puts forward their main implications. It concludes with the identification of three enablers of science 2.0 – policy measures, individual practice of scientists and new infrastructure and services and sees the main bottleneck in lack of incentives on the individual level.

The purpose of this paper is to direct academic librarians to free data resources that support international relations research. This paper provides technical information so readers can download data from referenced sites for analysis. Proper citation of data sources is emphasized.

The resources were compiled from teaching information and statistical literacy to diplomacy undergraduate and graduate students. Data and data sets described are relevant to country research and sustainable development.

Academic librarians will help students identify if they are looking for data specific to an agency, indicator, initiative, or general topic. Statistical literacy is also an underlying goal for academic librarians. Key word searching is important for finding sources that may not surface through a simple Google search.

The free services described may not answer all research queries. Librarians may need to use services such as Political Risk Service’s CountryData Online.

This is an excellent resource list of secondary data sources for academic librarians in areas that may not be their area of expertise or for those not at Tier 1 research institutions.

Students internationally will have access to this data. This has implications for US college students who are competing with students overseas for jobs and will use data to help future employers make strategic decisions.

There has not been anything published recently in library literature about United Nations data resources. This article features commentary from two Seton Hall University Diplomacy faculty plus EDUCAUSE and UK researchers.

The purpose of this study was to establish the current skills base of librarians working in research data management services in academic and research libraries in South Africa. The purpose was also to determine the relevance of courses and programmes that are currently being offered by library and information studies programmes in response to the needs of research data management services and make recommendations on curriculum improvement.

About 13 institutions which were considered early adopters of research data management services were identified as participants in an online survey. In addition, a review of Web pages of existing library and information studies schools was carried to establish courses that would support research data management services. Data collected through the two approaches were analysed and presented quantitatively and qualitatively.

The findings reveal an environment in a developmental stage, with limited skilled personnel to run research data management services. The findings also show an absence of specific data librarianship courses within existing library and information studies programmes and a very limited scope for the full range of data management courses within professional development programmes.

The paper provides information on approaches to further develop existing curriculum and contribute to the data management needs and support governments, funders and publishers' requirements for the discoverability and re-use of research data across research domains.

The purpose of this paper is to examine the role of Research Data Services (RDSs), consisting of research data management, data curation and data stewardship, and data literacy education in supporting Research 2.0. Besides this, theory and principles, as well as selected examples of best practices in the relevant fields are presented.

A literature-based overview of actual insights on tasks and roles that academic and research libraries have to fulfil in order to react to the developments generated by the appearance and growing importance of Research 2.0 is provided. Taking the wide spectre of related issues into account, the discussion is limited to RDSs.

Even though Research 2.0 is evolving in different countries and some local environments in dissimilar ways, its data-intensive nature requires the helping presence of academic libraries and librarians. Being an emerging phenomenon, it will undoubtedly take several different shapes as it works itself out in time, but librarians should try to discover service niches, which may not be covered by other academic organisations, or their coverage is only partial or even unsatisfactory.

Taking the wide spectre of issues into account, the review of literature is limited to the period between 2014 and 2016.

The paper intends to add to the body of knowledge about the relationship between RDSs and Research 2.0, as well as about the association between the components of the former.

In recent years, a large number of data repositories have been built and used. However, the extent to which scientific data are re-used in academic publications is still unknown. The purpose of this paper is to explore the functions of re-used scientific data in scholarly publication in different fields.

To address these questions, the authors identified 827 publications citing resources in the Dryad Digital Repository indexed by Scopus from 2010 to 2015.

The results show that: the number of citations to scientific data increases sharply over the years, but mainly from data-intensive disciplines, such as agricultural, biology science, environment science and medicine; the majority of citations are from the originating articles; and researchers tend to reuse data produced by their own research groups.

Dryad data may be re-used without being formally cited.

The conservatism in data sharing suggests that more should be done to encourage researchers to re-use other’s data.

Library and information science (LIS) and the digital humanities are both interested in studying recorded information and often share institutional frameworks. The purpose of this paper is to go beyond outlining these similarities by examining the perceived and real strengths and weaknesses of both disciplines.

Epistemologies and methods of both disciplines are analysed, principally in the light of the growing importance of data-intensive research, taking into consideration that there is a tension about the academic status of these disciplines.

Epistemologies and methods of both disciplines are analysed, principally in the light of the growing importance of data-intensive research, taking into consideration that there is a tension about the academic status of these disciplines.

The paper intends to be an add-on to the recent discussions and the evolving body of knowledge about the relationship of these disciplines with the hope of indicating a possible new direction in the development of LIS.

The purpose of this study is twofold: to investigate the role of big data in firms’ co-knowledge and value creation and to understand the underlying drivers behind value creation through big data in the oil and gas industry by underscoring the role of firms’ capabilities, trends and challenges.

Following an inductive approach, semi-structured interviews were conducted with senior managers and analysts working in oil and gas companies across eight countries. The data collected from these key informants were then analysed using the qualitative data analysis software ATLAS.ti.

Value creation through big data is an important factor for enhancing performance. It has a positive impact on both tangible (organisational performance) and intangible (societal) aspects depending on the context. Oil and gas companies understand the importance of big data to creating value in their operations. However, implementing and using big data has been problematic. In this study, a framework was developed to show that factors such as the shortage of data experts, poor data quality, the risk of cyber-attacks and unsupportive organisational cultures impede its implementation and utilisation.

The findings from this study have implications for managers and executives implementing big data and creating value across various data-intensive industries. The research findings, are contextual, however, and should be applied cautiously.

This study contributes to the value creation literature in the big data context. The findings identify the key areas to be considered for the effective implementation and utilisation of big data in the oil and gas sector. This study addresses a broad but under-explored issue (i.e. knowledge creation from big data and its implementation) and strengthens the academic debate within this research stream.

Currently, in the education data use literature, there is a lack of research and examples that consider the early steps of filtering, organizing and visualizing data to inform decision-making. The purpose of this study is to describe how school leaders and researchers visualized and jointly made sense of data from a common learning management system (LMS) used by students across multiple schools and grades in a charter management organization operating in the USA. To make sense of LMS data, researchers and practitioners formed a partnership to organize complex data sets, create data visualizations and engage in joint sensemaking around data visualizations to begin to launch continuous improvement cycles.

The authors analyzed LMS data for n = 476 students in Algebra I using hierarchical cluster analysis heatmaps. The authors also engaged in a qualitative case study that examined the ways in which school leaders made sense of the data visualization to inform improvement efforts.

The outcome of this study is a framework for informing evidence-based improvement cycles using large, complex data sets. Central to moving through the various steps in the proposed framework are collaborations between researchers and practitioners who each bring expertise that is necessary for organizing, filtering and visualizing data from digital learning environments and administrative data systems.

The authors propose an integrated cycle of data use in schools that builds on collaborations between researchers and school leaders to inform evidence-based improvement cycles.

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.