EN

Research Articles about Open Access Indexed by Scopus: A Content Analysis

Posted on by Hans Dillaerts

Authors : Rosângela Schwarz Rodrigues, Vitor Taga, Mariana Faustino dos Passos

This study analyzes research articles about open access (OA) indexed by the Scopus database, published from 2001 to 2015, in order to: (a) propose a categorization scheme about OA; (b) categorize the scientific production about OA; and (c) identify research trends on OA through disciplines at international level over time.

The authors used descriptive statistical methods and deductive content analysis using an unconstrained matrix in 347 selected research articles. The most explored themes were found to be “overview, current state, and growth of OA” counting for 98 articles (28.2%), and “awareness, perceptions, and attitudes toward OA” for 75 articles (21.6%).

As a conclusion, this study reveals a continuous and growing research interest by the OA community in studies focused on case studies regarding the development or evolution of OA in relation to certain groups, institutions, regions, periods, and how different actors perceive and address the OA movement.

URL : Research Articles about Open Access Indexed by Scopus: A Content Analysis

Alternative location : http://www.mdpi.com/2304-6775/4/4/31

EN

How Do Scientists Define Openness? Exploring the Relationship Between Open Science Policies and Research Practice

Posted on by Hans Dillaerts

Authors : Nadine Levin, Sabina Leonelli, Dagmara Weckowska, David Castle, John Dupré

This article documents how biomedical researchers in the United Kingdom understand and enact the idea of “openness.”

This is of particular interest to researchers and science policy worldwide in view of the recent adoption of pioneering policies on Open Science and Open Access by the U.K. government—policies whose impact on and implications for research practice are in need of urgent evaluation, so as to decide on their eventual implementation elsewhere.

This study is based on 22 in-depth interviews with U.K. researchers in systems biology, synthetic biology, and bioinformatics, which were conducted between September 2013 and February 2014.

Through an analysis of the interview transcripts, we identify seven core themes that characterize researchers’ understanding of openness in science and nine factors that shape the practice of openness in research.

Our findings highlight the implications that Open Science policies can have for research processes and outcomes and provide recommendations for enhancing their content, effectiveness, and implementation.

URL : How Do Scientists Define Openness? Exploring the Relationship Between Open Science Policies and Research Practice

Alternative location : http://bst.sagepub.com/content/early/2016/09/30/0270467616668760.abstract

EN

What does ‘green’ open access mean? Tracking twelve years of changes to journal publisher selfarchiving policies

Posted on by Hans Dillaerts

Authors : Elizabeth Gadd, Denise Troll Covey

Traces the 12-year self-archiving policy journey of the original 107 publishers listed on the SHERPA/RoMEO Publisher Policy Database in 2004, through to 2015. Maps the RoMEO colour codes (‘green’, ‘blue’, ‘yellow’ and ‘white’) and related restrictions and conditions over time.

Finds that while the volume of publishers allowing some form of self-archiving (pre-print, post-print or both) has increased by 12% over the 12 years, the volume of restrictions around how, where and when self-archiving may take place has increased 119%, 190% and 1000% respectively.

A significant positive correlation was found between the increase in self-archiving restrictions and the introduction of Gold paid open access options. Suggests that by conveying only the version of a paper that authors may self-archive, the RoMEO colour codes do not address all the key elements of the Bethesda Definition of Open Access.

Compares the number of RoMEO ‘green’ publishers over time with those meeting the definition for ‘redefined green’ (allowing embargo-free deposit of the post-print in an institutional repository). Finds that RoMEO ‘green’ increased by 8% and ‘redefined green’ decreased by 35% over the 12 years.

Concludes that the RoMEO colour codes no longer convey a commitment to green open access as originally intended. Calls for open access advocates, funders, institutions and authors to redefine what ‘green’ means to better reflect a publisher’s commitment to self-archiving.

URL : https://works.bepress.com/denise_troll_covey/82/

EN

Data trajectories: tracking reuse of published data for transitive credit attribution

Posted on by Hans Dillaerts

Author : Paolo Missier

The ability to measure the use and impact of published data sets is key to the success of the open data/open science paradigm. A direct measure of impact would require tracking data (re)use in the wild, which is difficult to achieve.

This is therefore commonly replaced by simpler metrics based on data download and citation counts. In this paper we describe a scenario where it is possible to track the trajectory of a dataset after its publication, and show how this enables the design of accurate models for ascribing credit to data originators.

A Data Trajectory (DT) is a graph that encodes knowledge of how, by whom, and in which context data has been re-used, possibly after several generations. We provide a theoretical model of DTs that is grounded in the W3C PROV data model for provenance, and we show how DTs can be used to automatically propagate a fraction of the credit associated with transitively derived datasets, back to original data contributors.

We also show this model of transitive credit in action by means of a Data Reuse Simulator. In the longer term, our ultimate hope is that credit models based on direct measures of data reuse will provide further incentives to data publication.

We conclude by outlining a research agenda to address the hard questions of creating, collecting, and using DTs systematically across a large number of data reuse instances in the wild.

URL : Data trajectories: tracking reuse of published data for transitive credit attribution

URL : http://dx.doi.org/10.2218/ijdc.v11i1.425

EN

Recognizing the Diversity of Contributions: A Case Study for Framing Attribution and Acknowledgement for Scientific Data

Posted on by Hans Dillaerts

Authors : Chung-Yi Hou, Matthew Mayernik

As scientific data volumes, format types, and sources increase rapidly with the invention and improvement of scientific capabilities, the resulting datasets are becoming more complex to manage as well.

One of the significant management challenges is pulling apart the individual contributions of specific people and organizations within large, complex projects.

This is important for two aspects:1) assigning responsibility and accountability for scientific work, and 2) giving professional credit to individuals (e.g. hiring, promotion, and tenure) who work within such large projects.

This paper aims to review the extant practice of data attribution and how it may be improved. Through a case study of creating a detailed attribution record for a climate model dataset, the paper evaluates the strengths and weaknesses of the current data attribution method and proposes an alternative attribution framework accordingly.

The paper concludes by demonstrating that, analogous to acknowledging the different roles and responsibilities shown in movie credits, the methodology developed in the study could be used in general to identify and map out the relationships among the organizations and individuals who had contributed to a dataset.

As a result, the framework could be applied to create data attribution for other dataset types beyond climate model datasets.

URL : Recognizing the Diversity of Contributions: A Case Study for Framing Attribution and Acknowledgement for Scientific Data

DOI : http://dx.doi.org/10.2218/ijdc.v11i1.357

EN

Factors Influencing Research Data Reuse in the Social Sciences : An Exploratory Study

Posted on by Hans Dillaerts

Author : Renata Gonçalves Curty

The development of e-Research infrastructure has enabled data to be shared and accessed more openly. Policy mandates for data sharing have contributed to the increasing availability of research data through data repositories, which create favourable conditions for the re-use of data for purposes not always anticipated by original collectors.

Despite the current efforts to promote transparency and reproducibility in science, datare-use cannot be assumed, nor merely considered a ‘thrifting’ activity where scientists shop around in datarepositories considering only the ease of access to data.

The lack of an integrated view of individual, socialand technological influential factors to intentional and actual data re-use behaviour was the key motivatorfor this study. Interviews with 13 social scientists produced 25 factors that were found to influence theirperceptions and experiences, including both their unsuccessful and successful attempts to re-use data.

These factors were grouped into six theoretical variables: perceived benefits, perceived risks, perceived effort,social influence, facilitating conditions, and perceived re-usability.

These research findings provide an in-depth understanding about the re-use of research data in the context of open science, which can be valuablein terms of theory and practice to help leverage data re-use and make publicly available data moreactionable.

URL : Factors Influencing Research Data Reuse in the Social Sciences : An Exploratory Study

DOI : http://dx.doi.org/10.2218/ijdc.v11i1.401

FR

Impact de l’Open Access sur les citations : une étude de cas

Posted on by Hans Dillaerts

Auteurs/Authors : Frédérique Bordignon, Mathieu Andro

De multiples études, dans la littérature internationale, ont cherché à évaluer l’impact de l’Open Access sur le taux de citation des articles scientifiques. La présente étude, en langue française, reste limitée aux publications 2010 de l’Ecole des Ponts.

Elle offre néanmoins un état de l’art des précédentes études sur le sujet à un lectorat de professionnels francophones et a pour originalité de mesurer le nombre moyen de citations par mois, avant et après “libération” Open Access des articles et d’éviter ainsi la plupart des biais qui peuvent être rencontrés dans ce type de démarche.

En plus de confirmer, comme beaucoup d’autres l’ont fait auparavant, un avantage net de l’Open Access sur le taux de citation en informatique, sciences de la terre et de l’univers, ingénierie, sciences environnementales, mathématiques, physique et astronomie, elle montre aussi qu’une « libération » précoce peut avoir un impact plus favorable qu’une « libération » tardive dans certains champs disciplinaires, comme les mathématiques et physique/astronomie.

URL : Impact de l’Open Access sur les citations : une étude de cas