Étiquette : research data

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Open Source Archaeology: Ethics and Practice

‘Open Source Archaeology: Ethics and Practice’ brings together authors and researchers in the field of open-source archaeology, defined as encompassing the ethical imperative for open public access to the results of publicly-funded research; practical solutions to open-data projects; open-source software applications in archaeology; public information sharing projects in archaeology; open-GIS; and the open-context system of data management and sharing.

This edited volume is designed to discuss important issues around open access to data and software in academic and commercial archaeology, as well as to summarise both the current state of theoretical engagement, and technological development in the field of open-archaeology.

URL : http://www.degruyter.com/view/product/460080

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Research data explored: an extended analysis of citations and altmetrics

In this study, we explore the citedness of research data, its distribution over time and its relation to the availability of a digital object identifier (DOI) in the Thomson Reuters database Data Citation Index (DCI).

We investigate if cited research data “impacts” the (social) web, reflected by altmetrics scores, and if there is any relationship between the number of citations and the sum of altmetrics scores from various social media platforms.

Three tools are used to collect altmetrics scores, namely PlumX, ImpactStory, and Altmetric.com, and the corresponding results are compared. We found that out of the three altmetrics tools, PlumX has the best coverage. Our experiments revealed that research data remain mostly uncited (about 85 %), although there has been an increase in citing data sets published since 2008.

The percentage of the number of cited research data with a DOI in DCI has decreased in the last years. Only nine repositories are responsible for research data with DOIs and two or more citations. The number of cited research data with altmetrics “foot-prints” is even lower (4–9 %) but shows a higher coverage of research data from the last decade. In our study, we also found no correlation between the number of citations and the total number of altmetrics scores.

Yet, certain data types (i.e. survey, aggregate data, and sequence data) are more often cited and also receive higher altmetrics scores. Additionally, we performed citation and altmetric analyses of all research data published between 2011 and 2013 in four different disciplines covered by the DCI.

In general, these results correspond very well with the ones obtained for research data cited at least twice and also show low numbers in citations and in altmetrics. Finally, we observed that there are disciplinary differences in the availability and extent of altmetrics scores.

URL : http://link.springer.com/article/10.1007/s11192-016-1887-4

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Open Data in Global Environmental Research: The Belmont Forum’s Open Data Survey

This paper presents the findings of the Belmont Forum’s survey on Open Data which targeted the global environmental research and data infrastructure community. It highlights users’ perceptions of the term “open data”, expectations of infrastructure functionalities, and barriers and enablers for the sharing of data. A wide range of good practice examples was pointed out by the respondents which demonstrates a substantial uptake of data sharing through e-infrastructures and a further need for enhancement and consolidation. Among all policy responses, funder policies seem to be the most important motivator. This supports the conclusion that stronger mandates will strengthen the case for data sharing.

URL : Open Data in Global Environmental Research: The Belmont Forum’s Open Data Survey

DOI :10.1371/journal.pone.0146695

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Enabling Open Science: Wikidata for Research

Wiki4R will create an innovative virtual research environment (VRE) for Open Science at scale, engaging both professional researchers and citizen data scientists in new and potentially transformative forms of collaboration. It is based on the realizations that (1) the structured parts of the Web itself can be regarded as a VRE, (2) such environments depend on communities, (3) closed environments are limited in their capacity to nurture thriving communities.

Wiki4R will therefore integrate Wikidata, the multilingual semantic backbone behind Wikipedia, into existing research processes to enable transdisciplinary research and reduce fragmentation of research in and outside Europe. By establishing a central shared information node, research data can be linked and annotated into knowledge. Despite occasional uses of Wikipedia or Wikidata in research, significant barriers to broader adoption in the sciences or digital humanities exist, including lack of integration into existing research processes and inadequate handling of provenances.

The proposed actions include providing best practices and tools for semantic mapping, adoption of citation and author identifiers, interoperability layers for integration with existing research environments, and the development of policies for information quality and interchange. The effectiveness of the actions will be tested in pilot use cases.

Unforeseen barriers will be investigated and documented. We will promote the adoption of Wiki4R by making it easy to use and integrate, demonstrate the applicability in selected research domains, and provide diverse training opportunities.

Wiki4R leverages the expertise gained in Europe through the Wikidata and DBpedia projects to further strengthen the established virtual community of 14000 people. As a result of increased interaction between professional science and citizens, it will provide an improved basis for Responsible Research and Innovation and Open Science in the European Research Area.

URL : Enabling Open Science: Wikidata for Research

Alternative location : http://rio.pensoft.net/articles.php?id=7573

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Assessing Research Data Management Practices of Faculty at Carnegie Mellon University

INTRODUCTION

Recent changes to requirements for research data management by federal granting agencies and by other funding institutions have resulted in the emergence of institutional support for these requirements. At CMU, we sought to formalize assessment of research data management practices of researchers at the institution by launching a faculty survey and conducting a number of interviews with researchers.

METHODS

We submitted a survey on research data management practices to a sample of faculty including questions about data production, documentation, management, and sharing practices. The survey was coupled with in-depth interviews with a subset of faculty. We also make estimates of the amount of research data produced by faculty.

RESULTS

Survey and interview results suggest moderate level of awareness of the regulatory environment around research data management. Results also present a clear picture of the types and quantities of data being produced at CMU and how these differ among research domains. Researchers identified a number of services that they would find valuable including assistance with data management planning and backup/storage services. We attempt to estimate the amount of data produced and shared by researchers at CMU.

DISCUSSION

Results suggest that researchers may need and are amenable to assistance with research data management. Our estimates of the amount of data produced and shared have implications for decisions about data storage and preservation.

CONCLUSION

Our survey and interview results have offered significant guidance for building a suite of services for our institution.

URL : Assessing Research Data Management Practices of Faculty at Carnegie Mellon University

DOI : http://doi.org/10.7710/2162-3309.1258

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Research Data Services in Academic Libraries: Data Intensive Roles for the Future?

Objectives

The primary objectives of this study are to gauge the various levels of Research Data Service academic libraries provide based on demographic factors, gauging RDS growth since 2011, and what obstacles may prevent expansion or growth of services.

Methods

Survey of academic institutions through stratified random sample of ACRL library directors across the U.S. and Canada. Frequencies and chi-square analysis were applied, with some responses grouped into broader categories for analysis.

Results

Minimal to no change for what services were offered between survey years, and interviews with library directors were conducted to help explain this lack of change.

Conclusion

Further analysis is forthcoming for a librarians study to help explain possible discrepancies in organizational objectives and librarian sentiments of RDS.

URL : Research Data Services in Academic Libraries: Data Intensive Roles for the Future?

DOI : http://dx.doi.org/10.7191/jeslib.2015.1085

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Research data management services in academic research libraries and perceptions of librarians

The emergence of data intensive science and the establishment of data management mandates have motivated academic libraries to develop research data services (RDS) for their faculty and students. Here the results of two studies are reported: librarians’ RDS practices in U.S. and Canadian academic research libraries, and the RDS-related library policies in those or similar libraries. Results show that RDS are currently not frequently employed in libraries, but many services are in the planning stages.

Technical RDS are less common than informational RDS, RDS are performed more often for faculty than for students, and more library directors believe they offer opportunities for staff to develop RDS-related skills than the percentage of librarians who perceive such opportunities to be available. Librarians need opportunities to learn more about these services either on campus or through attendance at workshops and professional conferences.

URL : Research data management services in academic research libraries and perceptions of librarians

DOI : http://dx.doi.org/10.1016/j.lisr.2013.11.003