We must all accept that science is data and that data are science, and thus provide for, and justify the need for the support of, much-improved data curation. (Hanson, Sugden, & Alberts) 
 
Researchers are producing an unprecedented deluge of data by using new methods and instrumentation. Others may wish to mine these data for new discoveries and innovations. However, research data are not readily available as sharing is common in only a few fields such as astronomy and genomics. Data sharing practices in other fields vary widely. Moreover, research data take many forms, are handled in many ways, using many approaches, and often are difficult to interpret once removed from their initial context. Data sharing is thus a conundrum. Four rationales for sharing data are examined, drawing examples from the sciences, social sciences, and humanities: (1) to reproduce or to verify research, (2) to make results of publicly funded research available to the public, (3) to enable others to ask new questions of extant data, and (4) to advance the state of research and innovation. These rationales differ by the arguments for sharing, by beneficiaries, and by the motivations and incentives of the many stakeholders involved. The challenges are to understand which data might be shared, by whom, with whom, under what conditions, why, and to what effects. Answers will inform data policy and practice. © 2012 Wiley Periodicals, Inc.

科研数据共享的挑战 (The Conundrum of Sharing Research Data)

In this study, we investigate information retrieval (IR) on Turkish texts using a large-scale test collection that contains 408,305 documents and 72 ad hoc queries. We examine the effects of several stemming options and query-document matching functions on retrieval performance. We show that a simple word truncation approach, a word truncation approach that uses language-dependent corpus statistics, and an elaborate lemmatizer-based stemmer provide similar retrieval effectiveness in Turkish IR. We investigate the effects of a range of search conditions on the retrieval performance; these include scalability issues, query and document length effects, and the use of stopword list in indexing. © 2008 Wiley Periodicals, Inc.

Information retrieval on Turkish texts

Abstract The growing importance of data in society in general and scientific domains in particular, mirrored in the Open Data initiative and in the advent of eScience, requires public, school and academic libraries to contribute to both data and information literacy, as part of their mission to further knowledge and innovation in their respective fields of action. No specific library standards have been proposed to date, however, and most research studies conducted adopt a partial view of data literacy, stressing only the components needed in any given context. The present paper aims to contribute to the advancement of data literacy with the proposal of a set of core competencies and contents that can serve as a framework of reference for its inclusion in libraries’ information literacy programs. The various definitions of data literacy are discussed, the coverage of the competencies listed in information literacy standards is described, and the competencies considered in the experiments conducted to date in education and libraries are identified. The conclusion drawn is that the model proposed can favour the development of data literacy support resources and services. Topics for further research are also specified.

/pdf/incorporating-data-literacy-into-information-literacy-2holoxvfai.pdf

Incorporating Data Literacy into Information Literacy Programs: Core Competencies and Contents

Researchers increasingly need to integrate the disposition, management, and curation of their data into their current workflows. However, it is not yet clear to what extent faculty and students are sufficiently prepared to take on these responsibilities. This paper articulates the need for a data information literacy program (DIL) to prepare students to engage in such an "e-research" environment. Assessments of faculty interviews and student performance in a geoinformatics course provide complementary sources of information, which are then filtered through the perspective of ACRL's information literacy competency standards to produce a draft set of outcomes for a data information literacy program.

/pdf/determining-data-information-literacy-needs-a-study-of-3mcm13jgs7.pdf

Determining Data Information Literacy Needs: A Study of Students and Research Faculty

http://www.mikesmit.com/wp-content/papercite-data/pdf/data_literacy.pdf

Strategies and Best Practices for Data Literacy Education: Knowledge Synthesis Report

In spring 2008 and 2009, we offered a course “Scientific Data Management” to undergraduate and graduate students from science and technology majors with support from an NSF CCLI (award #0633447) grant. We actively advertised the course on campus and conducted outreach efforts to individual classes and faculty representing a wide range of science and technology disciplines. Each time the course was offered, we conducted preand post-course surveys to assess the instructional effectiveness and learning outcomes. This paper will describe our experience as well as lessons learned in three areas: science faculty perceptions on data management, effect of science curriculum structures on data literacy education, and changes of students’ perceptions and aptitudes, and discuss how the lessons learned will help shape our escience Librarianship curriculum development, which is being funded by IMLS.

/pdf/lessons-learned-from-a-two-year-experience-in-science-data-55was4mjkf.pdf

Lessons learned from a two-year experience in science data literacy education

https://asistdl.onlinelibrary.wiley.com/doi/pdf/10.1002/meet.2008.14504503139

Faculty data management practices: A campus-wide census of STEM departments†

La recherche d'information federee est une technologie qui permet de rechercher des materiaux en provenance de sources multiples a partir d'un seul point d'entree. Vendeurs de logiciels, concepteurs et fournisseurs de contenus se sont associes pour explorer le comportement et les attentes d'etudiants ayant eu a utiliser des ressources de bibliotheques pour rediger un devoir. Les resultats des entretiens devraient permettre d'ameliorer la technologie de recherche federee.

/pdf/federated-search-observed-in-the-context-of-student-writing-6r97o1l19x.pdf

Federated search observed in the context of student writing Taking steps towards improving user experience

Meta-analyses are studies that bring together data or results from multiple independent studies to produce new and over-arching findings. Current data curation systems only partially support meta-analytic research. Some important meta-analytic tasks, such as the selection of relevant studies for review and the integration of research datasets or findings, are not well supported in current data curation systems. To design tools and services that more fully support meta-analyses, we need a better understanding of meta-analytic research. This includes an understanding of both the practices of researchers who perform the analyses and the characteristics of the individual studies that are brought together. In this study, we make an initial contribution to filling this gap by developing a conceptual framework linking meta-analyses with data paths represented in published articles selected for the analysis. The framework focuses on key variables that represent primary/secondary datasets or derived socio-ecological data, contexts of use, and the data transformations that are applied. We introduce the notion of using variables and their relevant information (e.g., metadata and variable relationships) as a type of currency to facilitate synthesis of findings across individual studies and leverage larger bodies of relevant source data produced in small science research. Handling variables in this manner provides an equalizing factor between data from otherwise disparate data-producing communities. We conclude with implications for exploring data integration and synthesis issues as well as system development.

/pdf/variables-as-currency-linking-meta-analysis-research-and-s9qz1wr245.pdf

Variables As Currency: Linking Meta-Analysis Research and Data Paths in Sciences

Repurposing of data raises a number of issues for use across the disciplines of climate science and social science. The issues we present are results of the work we are currently carrying out as part of the Data Conservancy Project1 which aims to preserve data for long-term known and unanticipated use over time, across disciplines and over a variety of spatial, temporal and organizational scales.

/pdf/repurposing-data-across-disciplines-a-study-of-data-reuse-40o0ia4vpq.pdf

Repurposing data across disciplines: a study of data reuse issues between climate science and social science

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