Archives des mots-clés : research data

If We Share Data, Will Anyone Use Them? Data Sharing and Reuse in the Long Tail of Science and Technology

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Research on practices to share and reuse data will inform the design of infrastructure to support data collection, management, and discovery in the long tail of science and technology. These are research domains in which data tend to be local in character, minimally structured, and minimally documented. We report on a ten-year study of the Center for Embedded Network Sensing (CENS), a National Science Foundation Science and Technology Center.

We found that CENS researchers are willing to share their data, but few are asked to do so, and in only a few domain areas do their funders or journals require them to deposit data. Few repositories exist to accept data in CENS research areas.. Data sharing tends to occur only through interpersonal exchanges. CENS researchers obtain data from repositories, and occasionally from registries and individuals, to provide context, calibration, or other forms of background for their studies. Neither CENS researchers nor those who request access to CENS data appear to use external data for primary research questions or for replication of studies.

CENS researchers are willing to share data if they receive credit and retain first rights to publish their results. Practices of releasing, sharing, and reusing of data in CENS reaffirm the gift culture of scholarship, in which goods are bartered between trusted colleagues rather than treated as commodities.

URL : If We Share Data, Will Anyone Use Them?

DOI : 10.1371/journal.pone.0067332

Toward Reproducible Computational Research: An Empirical Analysis of Data and Code Policy Adoption by Journals

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Journal policy on research data and code availability is an important part of the ongoing shift toward publishing reproducible computational science. This article extends the literature by studying journal data sharing policies by year (for both 2011 and 2012) for a referent set of 170 journals.

We make a further contribution by evaluating code sharing policies, supplemental materials policies, and open access status for these 170 journals for each of 2011 and 2012.

We build a predictive model of open data and code policy adoption as a function of impact factor and publisher and find higher impact journals more likely to have open data and code policies and scientific societies more likely to have open data and code policies than commercial publishers.

We also find open data policies tend to lead open code policies, and we find no relationship between open data and code policies and either supplemental material policies or open access journal status.

Of the journals in this study, 38% had a data policy, 22% had a code policy, and 66% had a supplemental materials policy as of June 2012. This reflects a striking one year increase of 16% in the number of data policies, a 30% increase in code policies, and a 7% increase in the number of supplemental materials policies.

We introduce a new dataset to the community that categorizes data and code sharing, supplemental materials, and open access policies in 2011 and 2012 for these 170 journals.

URL : http://www.plosone.org/article/info%3Adoi%2F10.1371%2Fjournal.pone.0067111

Making research data repositories visible the re3data org…

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Making research data repositories visible: the re3data.org registry :

“Researchers require infrastructures that ensure a maximum of accessibility, stability and reliability to facilitate working with and sharing of research data. Such infrastructures are being increasingly summarized under the term Research Data Repositories (RDR). The project re3data.org – Registry of Research Rata Repositories has begun to index research data repositories in 2012 and offers researchers, funding organizations, libraries and publishers an overview of the heterogeneous research data repository landscape. Information icons help researchers to easily identify an adequate repository for the storage and reuse of their data. This article describes the RDR landscape, outlines the practicality of re3data.org as a service, and shows how this service helps to find research data.”

URL : https://peerj.com/preprints/21v1/

The Role of the Library in the Research Enterprise

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Libraries have provided services to researchers for many years. Changes in technology and new publishing models provide opportunities for libraries to be more involved in the research enterprise.

Within this article, the author reviews traditional library services, briefly describes the eScience and publishing landscape as it relates to libraries, and explores possible library programs in support of research. Many of the new opportunities require new partnerships, both within the institution and externally.

URL : http://dx.doi.org/10.7191/jeslib.2013.1043

Common Errors in Ecological Data Sharing Objectives…

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Common Errors in Ecological Data Sharing :

“Objectives: (1) to identify common errors in data organization and metadata completeness that would preclude a “reader” from being able to interpret and re-use the data for a new purpose; and (2) to develop a set of best practices derived from these common errors that would guide researchers in creating more usable data products that could be readily shared, interpreted, and used.
Methods: We used directed qualitative content analysis to assess and categorize data and metadata errors identified by peer reviewers of data papers published in the Ecological Society of America’s (ESA) Ecological Archives. Descriptive statistics provided the relative frequency of the errors identified during the peer review process.
Results: There were seven overarching error categories: Collection & Organization, Assure, Description, Preserve, Discover, Integrate, and Analyze/Visualize. These categories represent errors researchers regularly make at each stage of the Data Life Cycle. Collection & Organization and Description errors were some of the most common errors, both of which occurred in over 90% of the papers.
Conclusions: Publishing data for sharing and reuse is error prone, and each stage of the Data Life Cycle presents opportunities for mistakes. The most common errors occurred when the researcher did not provide adequate metadata to enable others to interpret and potentially re-use the data. Fortunately, there are ways to minimize these mistakes through carefully recording all details about study context, data collection, QA/ QC, and analytical procedures from the beginning of a research project and then including this descriptive information in the metadata.”

URL : http://escholarship.umassmed.edu/jeslib/vol2/iss2/1/

Open access to scientific literature and research data…

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Open access to scientific literature and research data: a window of opportunity for latin america :

“The advance that the international open access movement has had in the last decade may seem to suggest that we are witnessing an important change in the model of scientific communication. This paper introduces the fundamental concepts of this movement, and in turn tries to measure the impact it has had in Latin America based on the development of different strategies.”

URL : http://sedici.unlp.edu.ar/handle/10915/23865