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Changes in the digital scholarly environment and issues of trust: An exploratory, qualitative analysis

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Authors : Anthony Watkinson, David Nicholas, Clare Thornley, Eti Herman, Hamid R. Jamali, Rachel Volentine, Suzie Allard, Kenneth Levine, Carol Tenopir

The paper reports on some of the results of a research project into how changes in digital behaviour and services impacts on concepts of trust and authority held by researchers in the sciences and social sciences in the UK and the USA.

Interviews were used in conjunction with a group of focus groups to establish the form and topic of questions put to a larger international sample in an online questionnaire. The results of these 87 interviews were analysed to determine whether or not attitudes have indeed changed in terms of sources of information used, citation behaviour in choosing references, and in dissemination practices.

It was found that there was marked continuity in attitudes though an increased emphasis on personal judgement over established and new metrics. Journals (or books in some disciplines) were more highly respected than other sources and still the vehicle for formal scholarly communication.

The interviews confirmed that though an open access model did not in most cases lead to mistrust of a journal, a substantial number of researchers were worried about the approaches from what are called predatory OA journals. Established researchers did not on the whole use social media in their professional lives but a question about outreach revealed that it was recognised as effective in reaching a wider audience.

There was a remarkable similarity in practice across research attitudes in all the disciplines covered andin both the countries where interviews were held.

URL : http://ciber-research.eu/download/20151110-Watkinson-Changes_and_Trust.pdf

Undercounting File Downloads from Institutional Repositories

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Authors : Patrick Obrien, Kenning Arlitsch, Leila Sterman, Jeff Mixter, Jonathan Wheeler, Susan Borda

A primary impact metric for institutional repositories (IR) is the number of file downloads, which are commonly measured through third-party Web analytics software. Google Analytics, a free service used by most academic libraries, relies on HTML page tagging to log visitor activity on Google’s servers.

However, Web aggregators such as Google Scholar link directly to high value content (usually PDF files), bypassing the HTML page and failing to register these direct access events.

This article presents evidence of a study of four institutions demonstrating that the majority of IR activity is not counted by page tagging Web analytics software, and proposes a practical solution for significantly improving the reporting relevancy and accuracy of IR performance metrics using Google Analytics.

URL : Undercounting File Downloads from Institutional Repositories

DOI : http://dx.doi.org/10.1080/01930826.2016.1216224

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

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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

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

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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

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

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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/

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

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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

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

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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