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This paper seeks to consider the collaborative efforts of developing a grid computing infrastructure within problem‐focused, distributed and multi‐disciplinary projects – which the authors term interventionist grid development projects – involving commercial, academic and public collaborators. Such projects present distinctive challenges which have been neglected by existing escience research and information systems (IS) literature. The paper aims to define a research framework for understanding and evaluating the social, political and collaborative challenges of such projects.

The paper develops a research framework which extends Orlikowski and Gash's concept of technological frames to consider two additional frames specific to such grid projects; bureaucratic frames and collaborator frames. These are used to analyse a case study of a grid development project within Healthcare which aimed to deploy a European data‐grid of medical images to facilitate collaboration and communication between clinicians across the European Union.

That grids are shaped to a significant degree by the collaborative practices involved in their construction, and that for projects involving commercial and public partners such collaboration is inhibited by the differing interpretive frames adopted by the different relevant groups.

The paper is limited by the nature of the grid development project studied, and the subsequent availability of research subjects.

The paper provides those involved in such projects, or in policy around such grid developments, with a practical framework by which to evaluate collaborations and their impact on the emergent grid. Further, the paper presents lessons for future such Interventionist grid projects.

This is a new area for research but one which is becoming increasingly important as data‐intensive computing begins to emerge as foundational to many collaborative sciences and enterprises. The work builds on significant literature in escience and IS drawing into this new domain. The research framework developed here, drawn from the IS literature, begins a new stream of systems development research with a distinct focus on bureaucracy, collaboration and technology within such interventionist grid development projects.

eScience workflows use orchestration for integrating and coordinating distributed and heterogeneous scientific resources, which are increasingly exposed as web services. The rate of growth of scientific data makes eScience workflows data‐intensive, challenging existing workflow solutions. Efficient methods of handling large data in scientific workflows based on web services are needed. The purpse of this paper is to address this issue.

In a previous paper the authors proposed Data‐Flow Delegation (DFD) as a means to optimize orchestrated workflow performance, focusing on SOAP web services. To improve the performance further, they propose pipelined data‐flow delegation (PDFD) for web service‐based eScience workflows in this paper, by leveraging from the domain of parallel programming. Briefly, PDFD allows partitioning of large datasets into independent subsets that can be communicated in a pipelined manner.

The results show that the PDFD improves the execution time of the workflow considerably and is capable of handling much larger data than the non‐pipelined approach.

Execution of a web service‐based workflow hampered by the size of data can be facilitated or improved by using services supporting Pipelined Data‐Flow Delegation.

Contributions of this work include the proposed concept of combining pipelining and Data‐Flow Delegation, an XML Schema supporting the PDFD communication between services, and the practical evaluation of the PDFD approach.

Print theses and dissertations have regularly been submitted together with complementary material, such as maps, tables, speech samples, photos or videos, in various formats and on different supports. In the digital environment of open repositories and open data, these research results could become a rich source of research results and data sets, for reuse and other exploitation. The paper aims to discuss these issues.

After introducing electronic theses and dissertations (ETD) into the context of eScience, the paper investigates some aspects that impact the availability and openness of data sets and other supplemental files related to ETD (system architecture, metadata and data retrieval, legal aspects).

These items are part of the so-called “small data” of eScience, with a wide range of contents and formats. Their heterogeneity and their link to ETD need specific approaches to data curation and management, with specific metadata and identifiers and with specific services, workflows and systems. One size may not fit for all but it seems appropriate to separate text and data files. Regarding copyright and licensing, data sets must be evaluated carefully but should not be processed and disseminated under the same conditions as the related PhD theses. Some examples are presented.

The paper concludes with recommendations for further investigation and development to foster open access to research results produced along with PhD theses.

ETDs are an important part of the content of open repositories. Yet, their potential as a gateway to underlying research results has not really been explored so far.

The purpose of this paper is to share with readers the issues of the 9th International Bielefeld Conference.

This is a descriptive report.

The conference discussed essential current and future developments towards enhanced libraries and information infrastructures meeting the emerging demands of eScience and eLearning.

Will be of interest to library and information professionals.

The aim of this paper is to reposition the research library in the context of the changing information and knowledge architecture at the end of the “Gutenberg Parenthesis” and as part of the rapidly emerging “semantic” environment of the Linked Open Data paradigm. Understanding this process requires a good understanding of the evolution of the “document” notion in the passage from print based culture to the distributed hypertextual and RDF based information architecture of the WWW.

These objectives are reached using literature study and a descriptive historical approach as well as text mining techniques using Google nGrams as a data source.

The paper presents a proposal for effectively repositioning research libraries in the context of eScience and eScholarship as well as clear indications of the proposed repositioning already taking place. Furthermore, a new perspective of the “document” notion is provided.

The evolution described in the contribution creates opportunities for libraries to reposition themselves as aggregators and selectors of content and as contextualising agents as part of future Linked Data based scholarly research environments provided they are able and ready to operate the related cultural changes.

The paper will be useful for practitioners in search of strategic guidance for repositioning their librarian institutions in a context of ever increasing competition for scarce funding resources.

This study aims to investigate the factors influencing the data sharing habits of psychologists with respect to academic reciprocity.

A research model was developed based on Ostrom’s (2003) theory of collective action to map psychologists’ underlying motivations for data sharing. The model was validated by data from a survey of 427 psychologists, primarily from the psychological sciences and related disciplines.

This study found that data sharing among psychologists is driven primarily by their perceptions of community benefits, academic reciprocity and the norms of data sharing. This study also found that academic reciprocity is significantly influenced by psychologists’ perceptions of community benefits, academic reputation and the norms of data sharing. Both academic reputation and academic reciprocity are affected by psychologists’ prior experiences with data reuse. Additionally, psychologists’ perceptions of community benefits and the norms of data sharing are significantly affected by the perception of their academic reputation.

This study suggests that Ostrom’s (2003) theory of collective action can provide a new theoretical lens in understanding psychologists’ data sharing behaviours.

This study suggests several practical implications for the design and promotion of data sharing in the research community of psychology.

To the best of the authors’ knowledge, this is one of the initial studies that applied the theory of collective action to the mechanisms of reputation, community benefits, norms and reciprocity in psychologists’ data sharing behaviour. This research demonstrates that perceived community benefits, academic reputation and the norms of data sharing can all encourage academic reciprocity, and psychologists’ perceptions of community benefits, academic reciprocity and data sharing norms all facilitate their data sharing intentions.

There are a variety of benefits associated with the use of YouTube for learning purposes, such as YouTube is a free open-access tool students can use to facilitate their learning. This study investigates whether an attitudinal factor (i.e. perceived usefulness) and the factor's antecedents, resource quality factors (i.e. credibility, currency, coverage and relevance), normative factor (i.e. subjective norm) and control factor (i.e. perceived ease of use) all affect college freshmen's behavioral intentions to use YouTube for academic learning purposes.

This research employs the theory of planned behavior (TPB) to explore the attitudinal, normative and control factors associated with college freshmen's behavioral intentions to use YouTube for academic learning. After developing a quantitative survey given to 182 college freshmen in a Southeastern institution in the United States of America, structural equation modeling (SEM) was used to examine the seven hypotheses and the research constructs.

The results indicate that attitudinal factor (i.e. perceived usefulness) and its antecedents, resource quality factors (i.e. currency, coverage and relevance) and normative factor (i.e. subjective norm) have a statistically significant effect on college freshmen's intentions to use YouTube for academic learning purposes.

This study suggests that individual motivations (i.e. perceived usefulness and subjective norm) and resource quality factors (i.e. currency, coverage and relevance) play into college freshmen's decisions to use YouTube for learning purposes, while other research indicates that the system or application itself factors into students' decisions to use technology for learning.

This study suggests that college freshmen are more likely to use YouTube for academic learning purposes when the freshmen hold favorable attitudes about the platform and when the freshmen believe the freshmen's peers are also using YouTube to supplement in-class learning.

This is an initial study that focuses on college freshmen's behavioral intentions to use YouTube for academic learning purposes. This research demonstrates the roles that peers as well as resource quality factors play in students' decisions to use specific technology to enhance the students' learning.

Today’s undergraduate students have spent a significant portion of their lives using YouTube for various reasons, whether for entertainment, personal development or academic learning purposes. This study aims to investigate how system factors (i.e. reliability, usability and searchability), interaction factors (i.e. provider and user interactions) and content factors (i.e. format, relevance and coverage) affect undergraduate students’ satisfaction with YouTube and their intentions to adopt YouTube for learning purposes.

This research uses the information systems success model as its theoretical framework to explore the system, interaction and content factors associated with undergraduate students’ satisfaction with YouTube and their intentions to use YouTube for learning. The proposed hypotheses were examined by the structural equation modelling technique based on a survey with 345 undergraduate students at a Southeastern institution in the USA.

The results indicate that both system factors (including reliability, usability and searchability) and content factors (including format, relevance and coverage) have a statistically significant effect on students’ satisfaction with YouTube. This study also demonstrates that students’ satisfaction with YouTube significantly influences their intentions to use the platform for learning purposes.

The proposed research model provides a novel perspective in understanding the complex nature of students’ adoption of YouTube for learning purposes, led by both system and content factors mediated by satisfaction with YouTube.

This study suggests that when YouTube is intuitive to use and relevant content is added to the platform regularly, students are more likely to adopt this platform for learning purposes. As a result, it is critical that librarians remain aware of information-seeking practices and platforms used by students to tailor approaches to teaching information literacy to help students understand how to use the platform effectively.

Using the information systems success model, this research sheds light on the roles of system and content factors in undergraduate students’ satisfaction with YouTube and their intentions to use it for learning.

The purpose of this research is to investigate the factors that influence engineering researchers’ data reuse behaviours.

The data reuse behaviour model of engineering researchers was investigated by using a survey method. A national survey was distributed to engineering researchers in the USA, and a total of 193 researchers responded.

The results showed that perceived usefulness, perceived concerns and norms of data reuse have significant relationships with attitudes toward data reuse. Also, attitudes toward data reuse and the availability of data repositories were found to have significant influences on engineering researchers’ intention to reuse data.

This research used a combined theoretical framework by integrating the theory of planned behaviour (TPB) and the technology acceptance model (TAM). The combination of the TPB and the TAM effectively explained engineering researchers’ data reuse behaviours by addressing individual motivations, norms and resource factors.

This research has practical implications for promoting more reliable and beneficial data reuse in the engineering community, including encouraging positive motivations toward data reuse, building community norms of data reuse and setting up more data repositories.

As prior research on data reuse mainly used interviews, this research used a quantitative approach based on a combined theoretical framework and included diverse research constructs which were not tested in the previous research models. As one of the initial studies investigating data reuse behaviours in the engineering community, the current research provided a better understanding of data reuse behaviours and suggested possible ways to facilitate engineering researchers’ data reuse behaviours.

The purpose of this paper is to examine how health scientists’ attitudinal, social, and resource factors affect their data reuse behaviors.

A survey method was utilized to investigate to what extent attitudinal, social, and resource factors influence health scientists’ data reuse behaviors. The health scientists’ data reuse research model was validated by using partial least squares (PLS) based structural equation modeling technique with a total of 161 health scientists in the USA.

The analysis results showed that health scientists’ data reuse intentions are driven by attitude toward data reuse, community norm of data reuse, disciplinary research climate, and organizational support factors. This research also found that both perceived usefulness of data reuse and perceived concern involved in data reuse have significant influences on health scientists’ attitude toward data reuse.

This research evaluated its newly proposed research model based on the theory of planned behavior using a sample from the community of scientists’ scholar database. This research showed an overall picture of how attitudinal, social, and resource factors influence health scientists’ data reuse behaviors. This research is limited due to its sample size and low response rate, so this study is considered as an exploratory study rather than a confirmatory study.

This research suggested for health science research communities, academic institutions, and libraries that diverse strategies need to be utilized to promote health scientists’ data reuse behaviors.

This research is one of initial studies in scientific data reuse which provided a holistic map about health scientists’ data sharing behaviors. The findings of this study provide the groundwork for strategies to facilitate data reuse practice in health science areas.