著者

CODATA-ICSTI Task Group on Data Citation Standards and Practices

出版者

CODATA

雑誌

Data Science Journal (ISSN:16831470)

巻号頁・発行日

vol.12, pp.CIDCR1-CIDCR75, 2013 (Released:2013-09-13)

参考文献数

185

被引用文献数

56

---

The use of published digital data, like the use of digitally published literature, depends upon the ability to identify, authenticate, locate, access, and interpret them. Data citations provide necessary support for these functions, as well as other functions such as attribution of credit and establishment of provenance. References to data, however, present challenges not encountered in references to literature. For example, how can one specify a particular subset of data in the absence of familiar conventions such as page numbers or chapters? The traditions and good practices for maintaining the scholarly record by proper references to a work are well established and understood in regard to journal articles and other literature, but attributing credit by bibliographic references to data are not yet so broadly implemented. This report discusses the current state of data citation practices, its supporting infrastructure, a set of guiding principles for implementing data citation, challenges to implementation of good data citation practices, and open research questions.

著者

M A Parsons P A Fox

出版者

CODATA

雑誌

Data Science Journal (ISSN:16831470)

巻号頁・発行日

vol.12, pp.WDS32-WDS46, 2013 (Released:2013-02-10)

参考文献数

58

被引用文献数

50

---

International attention to scientific data continues to grow. Opportunities emerge to re-visit long-standing approaches to managing data and to critically examine new capabilities. We describe the cognitive importance of metaphor. We describe several metaphors for managing, sharing, and stewarding data and examine their strengths and weaknesses. We particularly question the applicability of a “publication” approach to making data broadly available. Our preliminary conclusions are that no one metaphor satisfies enough key data system attributes and that multiple metaphors need to co-exist in support of a healthy data ecosystem. We close with proposed research questions and a call for continued discussion.

著者

CODATA-ICSTI Task Group on Data Citation Standards and Practices

出版者

CODATA

雑誌

Data Science Journal (ISSN:16831470)

巻号頁・発行日

pp.OSOM13-043, (Released:2013-09-08)

参考文献数

185

被引用文献数

56

---

The use of published digital data, like the use of digitally published literature, depends upon the ability to identify, authenticate, locate, access, and interpret them. Data citations provide necessary support for these functions, as well as other functions such as attribution of credit and establishment of provenance. References to data, however, present challenges not encountered in references to literature. For example, how can one specify a particular subset of data in the absence of familiar conventions such as page numbers or chapters? The traditions and good practices for maintaining the scholarly record by proper references to a work are well established and understood in regard to journal articles and other literature, but attributing credit by bibliographic references to data are not yet so broadly implemented. This report discusses the current state of data citation practices, its supporting infrastructure, challenges to implementation of good data citation practices, and open research questions.

著者

James Campbell

出版者

CODATA

雑誌

Data Science Journal (ISSN:16831470)

巻号頁・発行日

pp.14-043, (Released:2015-01-19)

参考文献数

42

被引用文献数

10

---

Making scientific data openly accessible and available for re-use is desirable to encourage validation of research results and/or economic development. Understanding what users may, or may not, do with data in online data repositories is key to maximizing the benefits of scientific data re-use. Many online repositories that allow access to scientific data indicate that data is “open,” yet specific usage conditions reviewed on 40 “open” sites suggest that there is no agreed upon understanding of what “open” means with respect to data. This inconsistency can be an impediment to data re-use by researchers and the public.

著者

Peter Fox Ray Harris

出版者

CODATA

雑誌

Data Science Journal (ISSN:16831470)

巻号頁・発行日

vol.12, pp.WDS1-WDS12, 2013 (Released:2013-02-10)

参考文献数

20

被引用文献数

1

---

The International Council for Science (ICSU) vision explicitly recognises the value of data and information to science and particularly emphasises the urgent requirement for universal and equitable access to high quality scientific data and information. A universal public domain for scientific data and information will be transformative for both science and society. Over the last several years, two ad-hoc ICSU committees, the Strategic Committee on Information and Data (SCID) and the Strategic Coordinating Committee on Information and Data (SCCID), produced key reports that make 5 and 14 recommendations respectively aimed at improving universal and equitable access to data and information for science and providing direction for key international scientific bodies, such as the Committee on Data for Science and Technology (CODATA) as well as a newly ratified (by ICSU in 2008) formation of the World Data System. This contribution outlines the framing context for both committees based on the changed world scene for scientific data conduct in the 21st century. We include details on the relevant recommendations and important consequences for the worldwide community of data providers and consumers, ultimately leading to a conclusion, and avenues for advancement that must be carried to the many thousands of data scientists world-wide.

著者

Paul F. Uhlir

出版者

CODATA

雑誌

Data Science Journal (ISSN:16831470)

巻号頁・発行日

vol.9, pp.ES1-ES5, 2010-10-07 (Released:2010-10-07)

参考文献数

1

被引用文献数

3

著者

P Arzberger P Schroeder A Beaulieu G Bowker K Casey L Laaksonen D Moorman P Uhlir P Wouters

出版者

CODATA

雑誌

Data Science Journal (ISSN:16831470)

巻号頁・発行日

vol.3, pp.135-152, 2004 (Released:2006-01-05)

参考文献数

36

被引用文献数

167 142

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Access to and sharing of data are essential for the conduct and advancement of science. This article argues that publicly funded research data should be openly available to the maximum extent possible. To seize upon advancements of cyberinfrastructure and the explosion of data in a range of scientific disciplines, this access to and sharing of publicly funded data must be advanced within an international framework, beyond technological solutions. The authors, members of an OECD Follow-up Group, present their research findings, based closely on their report to OECD, on key issues in data access, as well as operating principles and management aspects necessary to successful data access regimes.

著者

Christian Bizer

出版者

CODATA

雑誌

Data Science Journal (ISSN:16831470)

巻号頁・発行日

vol.12, pp.GRDI6-GRDI12, 2013 (Released:2013-07-23)

参考文献数

17

被引用文献数

19

著者

R. de la Sablonnière E. Auger M. Sabourin G. Newton

出版者

CODATA

雑誌

Data Science Journal (ISSN:16831470)

巻号頁・発行日

vol.11, pp.DS29-DS43, 2012 (Released:2012-03-23)

参考文献数

57

被引用文献数

2

---

In most scientific fields, significant improvements have been made in terms of data sharing among scientists and researchers. Although there are clear benefits to data sharing, there is at least one field where this norm has yet to be developed: the behavioural sciences. In this paper, we propose an innovative methodology as a means to change existing norms within the behavioural sciences and move towards increased data sharing. Based on recent advances in social psychology, we theorize that a Survey Research Instrument that takes into account basic psychological processes can be effective in promoting data sharing norms.

著者

Kevin Ashley

出版者

CODATA

雑誌

Data Science Journal (ISSN:16831470)

巻号頁・発行日

vol.12, pp.GRDI65-GRDI68, 2013 (Released:2013-08-10)

参考文献数

5

被引用文献数

2

著者

F. Jack Smith

出版者

CODATA

雑誌

Data Science Journal (ISSN:16831470)

巻号頁・発行日

vol.5, pp.163-164, 2006 (Released:2006-11-28)

被引用文献数

14 9

著者

Shuichi Iwata

出版者

CODATA

雑誌

Data Science Journal (ISSN:16831470)

巻号頁・発行日

vol.7, pp.54-56, 2008 (Released:2008-05-27)

被引用文献数

9 11

著者

Paul F. Uhlir Robert S. Chen Joanne Irene Gabrynowicz Katleen Janssen

出版者

CODATA

雑誌

Data Science Journal (ISSN:16831470)

巻号頁・発行日

vol.8, pp.GEO1-GEO91, 2009-10-07 (Released:2009-10-07)

参考文献数

52

被引用文献数

7 4

著者

Tobias Weigel Michael Lautenschlager Frank Toussaint Stephan Kindermann

出版者

CODATA

雑誌

Data Science Journal (ISSN:16831470)

巻号頁・発行日

vol.12, pp.10-22, 2013 (Released:2013-03-07)

参考文献数

13

被引用文献数

3

---

Several scientific communities relying on e-science infrastructures are in need of persistent identifiers for data and contextual information. In this article, we present a framework for persistent identification that fundamentally supports context information. It is installed as a number of low-level requirements and abstract data type descriptions, flexible enough to envelope context information while remaining compatible with existing definitions and infrastructures. The abstract data type definitions we draw from the requirements and exemplary use cases can act as an evaluation tool for existing implementations or as a blueprint for future persistent identification infrastructures. A prototypic implementation based on the Handle System is briefly introduced. We also lay the groundwork for establishing a graph of persistent entities that can act as a base layer for more sophisticated information schemas to preserve context information.

著者

Costantino Thanos

出版者

CODATA

雑誌

Data Science Journal (ISSN:16831470)

巻号頁・発行日

vol.12, pp.71-90, 2013 (Released:2013-09-13)

参考文献数

30

被引用文献数

8

---

New high-throughput scientific instruments, telescopes, satellites, accelerators, supercomputers, sensor networks, and running simulations are generating massive amounts of data. In order to be able to exploit these huge volumes of data, a new type of e-infrastructure, the Global Research Data Infrastructure (GRDI), must be developed for harnessing the accumulating data and knowledge produced by the communities of research. This paper identifies the main challenges faced by the future GRDIs, defines a conceptual framework for GRDIs based on the ecosystem metaphor, describes a core set of functionality that these GRDIs must provide, and gives a set of recommendations for building the future GRDIs.

著者

Florian Quadt André Düsterhus Heinke Höck Michael Lautenschlager Andreas V. Hense Andreas N. Hense Martin Dames

出版者

CODATA

雑誌

Data Science Journal (ISSN:16831470)

巻号頁・発行日

vol.11, pp.89-109, 2012 (Released:2012-11-09)

参考文献数

26

被引用文献数

4

---

In a research project funded by the German Research Foundation, meteorologists, data publication experts, and computer scientists optimised the publication process of meteorological data and developed software that supports metadata review. The project group placed particular emphasis on scientific and technical quality assurance of primary data and metadata. At the end, the software automatically registers a Digital Object Identifier at DataCite. The software has been successfully integrated into the infrastructure of the World Data Center for Climate, but a key objective was to make the results applicable to data publication processes in other sciences as well.

著者

Mehedi Masud Gopal Chandra Das Anisur Rahman Arunashis Ghose

出版者

CODATA

雑誌

Data Science Journal (ISSN:16831470)

巻号頁・発行日

vol.5, pp.143-161, 2006 (Released:2006-11-28)

参考文献数

11

---

It is always a major demand to provide efficient retrieving and storing of data and information in a large database system. For this purpose, many file organization techniques have already been developed, and much additional research is still going on. Hashing is one developed technique. In this paper we propose an enhanced hashing technique that uses a hash table combined with a binary tree, searching on the binary representation of a portion the primary key of records that is associated with each index of the hash table. The paper contains numerous examples to describe the technique. The technique shows significant improvements in searching, insertion, and deletion for systems with huge amounts of data. The paper also presents the mathematical analysis of the proposed technique and comparative results.

著者

Sugam Sharma Udoyara S Tim Johnny Wong Shashi Gadia Subhash Sharma

出版者

CODATA

雑誌

Data Science Journal (ISSN:16831470)

巻号頁・発行日

vol.13, pp.138-157, 2014 (Released:2014-12-04)

参考文献数

40

被引用文献数

45

---

Today, science is passing through an era of transformation, where the inundation of data, dubbed data deluge is influencing the decision making process. The science is driven by the data and is being termed as data science. In this internet age, the volume of the data has grown up to petabytes, and this large, complex, structured or unstructured, and heterogeneous data in the form of “Big Data” has gained significant attention. The rapid pace of data growth through various disparate sources, especially social media such as Facebook, has seriously challenged the data analytic capabilities of traditional relational databases. The velocity of the expansion of the amount of data gives rise to a complete paradigm shift in how new age data is processed. Confidence in the data engineering of the existing data processing systems is gradually fading whereas the capabilities of the new techniques for capturing, storing, visualizing, and analyzing data are evolving. In this review paper, we discuss some of the modern Big Data models that are leading contributors in the NoSQL era and claim to address Big Data challenges in reliable and efficient ways. Also, we take the potential of Big Data into consideration and try to reshape the original operationaloriented definition of “Big Science” (Furner, 2003) into a new data-driven definition and rephrase it as “The science that deals with Big Data is Big Science.”

著者

James Campbell

出版者

CODATA

雑誌

Data Science Journal (ISSN:16831470)

巻号頁・発行日

vol.13, pp.203-230, 2015 (Released:2015-01-27)

参考文献数

42

被引用文献数

10

---

Making scientific data openly accessible and available for re-use is desirable to encourage validation of research results and/or economic development. Understanding what users may, or may not, do with data in online data repositories is key to maximizing the benefits of scientific data re-use. Many online repositories that allow access to scientific data indicate that data is “open,” yet specific usage conditions reviewed on 40 “open” sites suggest that there is no agreed upon understanding of what “open” means with respect to data. This inconsistency can be an impediment to data re-use by researchers and the public.

著者

Daniel Liwei Wang Jacek Becla Kian-Tat Lim

出版者

CODATA

雑誌

Data Science Journal (ISSN:16831470)

巻号頁・発行日

vol.12, pp.23-32, 2013 (Released:2013-05-13)

被引用文献数

1

---

Petascale data management and analysis remain one of the main unresolved challenges in today's computing. The 6th Extremely Large Databases workshop was convened alongside the XLDB conference to discuss the challenges in the health care, biology, and natural resources communities. The role of cloud computing, the dominance of file-based solutions in science applications, in-situ and predictive analysis, and commercial software use in academic environments were discussed in depth as well. This paper summarizes the discussions of this workshop.