Thursday 27 March 2014

Citation analysis of oceanographic data sets (and its in PLoS ONE, so it's OA!)

BELTER, C. W. 2014. Measuring the Value of Research Data: A Citation Analysis of Oceanographic Data Sets. PLoS ONE, 9, e92590.
dx.plos.org/10.1371/journal.pone.0092590 


Related tweet: https://twitter.com/Impactstory/status/449281205276405760

Thanks to Sue Cook for this one!

Sunday 23 March 2014

Scalable data citation in dynamic, large databases

Proll, S. & Rauber, A. 2013. Scalable data citation in dynamic, large databases: Model and reference implementation. In:  2013 IEEE International Conference on Big Data, 6-9 Oct. 2013. 307-312.  10.1109/BigData.2013.6691588 

This makes for interesting reading, and poses one solution for citing data in dynamic databases.

 

Nature's Scientific Data Journal - first look

 
 
Scientific Data is the new data journal being published by the Nature Publishing Group.
 
 
The journals aims "to meet demands from science researchers and funders for innovative ways to make scientific data more available, citable, discoverable, interpretable, reusable and reproducible"
 
While Scientific Data is scheduled for formal release in May 2014, a couple of "pre-release" data statements (articles) have recently been published giving a flavour of what's to come.
 
Interestingly, the reference lists include a separate section for Data Citations (see below for an example).  A list of recommended data repositories is provided.
 
Worth a look ... we anticipate data journals will be increasingly important as a mechanism for publishing data.  Amongst other things, they will offer greater opportunity for data citation metrics.
 
Data Citations
  1. 1. Perkins, A. D., Lee, M. & Tanentzapf, G. GenomeRNAi GR00238-S (2014).
  2. 2. Perkins, A. D., Lee, M. & Tanentzapf, G. Figshare http://dx.doi.org/10.6084/m9.figshare.806269 (2014).

Tuesday 18 March 2014

Data Citers Catch Up - Thursday April 3 @ 12.30 AEDST


NO NEED TO REGISTER: Just come in at 12.30pm (AEDST) using this link:
https://www4.go​tomeeting.com/j​oin/176321199

Focus for the April meet up:

Research Data Alliance Data Citation Working Group
https://rd-alli​ance.org/workin​ggroup-list.htm​l

Cite My Data DOI minting service - exploring new options for minting DOIs.
http://ands.org.au/services/cite-my-data.html

Our chair this month is Amanda Steen from Geoscience Australia.

Draft agenda
--  Welcome and introductions

--  Research Data Alliance Data Citation Working Group
Amir Aryani, ANDS representative on the Data Citation Working Group, will provide insights into the activities of the Group. Fresh from his return from the 3rd Plenary for the Alliance in Dublin during March, Amir will give a brief presentation and stay on to answer your questions. 

-- Cite My Data DOI minting service
Joel Benn from ANDS will join us to hear your thoughts about some new service options ANDS is considering for the Cite My Data Service. Do you have records already in RDA that you'd like to assign DOIs to? Anyone interested in a service where ANDS would mint DOIs for your new RDA records? If so, please come along, hear more, provide input and perhaps express interest.
 
--  Open floor for your data citation questions, issues, updates.
 
--  Call for topics and speakers for future catch ups.

Connect with your data citer's community on the blog at: http://datacite​rs.blogspot.com​.au

Tuesday 4 March 2014

Interesting article: 10 Simple Rules for the Care and Feeding of Scientific Data

Data citation rates several mentions in this article.  Worth a read.

10 Simple Rules for the Care and Feeding of Scientific Data
This article offers a short guide to the steps scientists can take to ensure that their data and associated analyses continue to be of value and to be recognized. In just the past few years, hundreds of scholarly papers and reports have been written on questions of data sharing, data provenance, research reproducibility, licensing, attribution, privacy, and more, but our goal here is not to review that literature. Instead, we present a short guide intended for researchers who want to know why it is important to "care for and feed" data, with some practical advice on how to do that.

http://arxiv.org/abs/1401.2134

Joint Declaration of Data Citation Principles

Recently announced!  Completion of the “Joint Declaration of
Data Citation Principles”.  The Principles cover purpose, function and attributes of citations. They are reproduced briefly below.  More at: www.force11.org/datacitation


  1. Importance

    Data should be considered legitimate, citable products of research. Data citations should be accorded the same importance in the scholarly record as citations of other research objects, such as publications[1].
  2. Credit and Attribution

    Data citations should facilitate giving scholarly credit and normative and legal attribution to all contributors to the data, recognizing that a single style or mechanism of attribution may not be applicable to all data[2].
  3. Evidence

    In scholarly literature, whenever and wherever a claim relies upon data, the corresponding data should be cited[3].
  4. Unique Identification

    A data citation should include a persistent method for identification that is machine actionable, globally unique, and widely used by a community[4].
  5. Access

    Data citations should facilitate access to the data themselves and to such associated metadata, documentation, code, and other materials, as are necessary for both humans and machines to make informed use of the referenced data[5].
  6. Persistence

    Unique identifiers, and metadata describing the data, and its disposition, should persist --  even beyond the lifespan of the data they describe[6].
  7. Specificity and Verifiability 

    Data citations should facilitate identification of, access to, and verfication of the specific data that support a claim.  Citations or citation metadata should include information about provenance and fixity sufficient to facilitate verfiying that the specific timeslice, version and/or granular portion of data retrieved subsequently is the same as was originally cited[7].
  8. Interoperability and flexibility

    Data citation methods should be sufficiently flexible to accommodate the variant practices among communities, but should not differ so much that they compromise interoperability of data citation practices across communities[8].