DataCite as a novel bibliometric source: Coverage, strengths and limitations

Robinson-García, Nicolás; Mongeon, Philippe; Jeng, Wei; Costas, Rodrigo

doi:10.1016/j.joi.2017.07.003

Cited by 25 publications

(17 citation statements)

References 18 publications

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“…DataCite is a content registration service, and its Event Data API provides citation indicators for research outputs that link to DataCite records (DataCite Event Data, n.d.). DataCite has handled over 6 million DOI registrations to date, of which 42% were specifically for datasets (Robinson-Garcia et al, 2017). A sizable portion of DataCite-registered content comes from only a handful of repositories, and due to inconsistency in metadata, it is unclear whether there is disciplinary bias within the content registered via DataCite (Robinson-Garcia et al, 2017).…”

Section: Citation-based Indicatorsmentioning

confidence: 99%

Assessing the Impact and Quality of Research Data Using Altmetrics and Other Indicators

Konkiel

2020

SAR

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Research data in all its diversity-instrument readouts, observations, images, texts, video and audio files, and so on-is the basis for most advancement in the sciences. Yet the assessment of most research programmes happens at the publication level, and data has yet to be treated like a first-class research object. How can and should the research community use indicators to understand the quality and many potential impacts of research data? In this article, we discuss the research into research data metrics, these metrics' strengths and limitations with regard to formal evaluation practices, and the possible meanings of such indicators. We acknowledge the dearth of guidance for using altmetrics and other indicators when assessing the impact and quality of research data, and suggest heuristics for policymakers and evaluators interested in doing so, in the absence of formal governmental or disciplinary policies. Policy highlights • Research data is an important building block of scientific production, but efforts to develop a framework for assessing data's impacts have had limited success to date. • Indicators like citations, altmetrics, usage statistics, and reuse metrics highlight the influence of research data upon other researchers and the public, to varying degrees. • In the absence of a shared definition of "quality", varying metrics may be used to measure a dataset's accuracy, currency, completeness, and consistency. • Policymakers interested in setting standards for assessing research data using indicators should take into account indicator availability and disciplinary variations in the data when creating guidelines for explaining and interpreting research data's impact. • Quality metrics are context dependent: they may vary based upon discipline, data structure, and repository. For this reason, there is no agreed upon set of indicators that can be used to measure quality. • Citations are well-suited to showcase research impact and are the most widely understood indicator. However, efforts to standardize and promote data citation practices have seen limited success, leading to varying rates of citation data availability across disciplines. • Altmetrics can help illustrate public interest in research, but availability of altmetrics for research data is very limited. • Usage statistics are typically understood to showcase interest in research data, but infrastructure to standardize these measures have only recently been introduced, and not all repositories report their usage metrics to centralized data brokers like DataCite. • Reuse metrics vary widely in terms of what kinds of reuse they measure (e.g. educational, scholarly, etc). This category of indicator has the fewest heuristics for collection and use associated with it; think about explaining and interpreting reuse with qualitative data, wherever possible. • All research data impact indicators should be interpreted in line with the Leiden Manifesto's principles, including accounting for disciplinary variation and data availability. • Assessing research...

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Section: Citation-based Indicatorsmentioning

confidence: 99%

Assessing the Impact and Quality of Research Data Using Altmetrics and Other Indicators

Konkiel

2020

SAR

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“…However, it is found that there is lack of understanding of FAIR data and principles; need for investments in the development of data tools, services, and processes to support open research; adopting FAIR principles across the broad coordinating activities and policy development at cross-disciplinary, national, and international levels [59,60]. DataCite has been steering on persistent identifiers for research data citation, discovery, and accessibility, while also emphasizing the measurement of grants and the impact that is made by funding agencies [61,62]. Hypothesis has been experimenting with open annotation use cases on preprints and discussed the burden of moderating (editorial and site), identity, and versioning among the preprint repositories [63].…”

Section: Preprints For Building Scholarly Infrastructures and Metricsmentioning

confidence: 99%

Preprints in Scholarly Communication: Re-Imagining Metrics and Infrastructures

Balaji

Dhanamjaya

2019

Publications

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Digital scholarship and electronic publishing within scholarly communities change when metrics and open infrastructures take center stage for measuring research impact. In scholarly communication, the growth of preprint repositories as a new model of scholarly publishing over the last three decades has been one of the major developments. As it unfolds, the landscape of scholarly communication is transitioning—with much being privatized as it is made open—and turning towards alternative metrics, such as social media attention, author-level, and article-level metrics. Moreover, the granularity of evaluating research impact through new metrics and social media changes the objective standards of evaluating research performance. Using preprint repositories as a case study, this article situates them in a scholarly web, examining their salient features, benefits, and futures. Moves towards scholarly web development and publishing on the semantic and social web with open infrastructures, citations, and alternative metrics—how preprints advance building the web as data—is discussed. We determine that this will viably demonstrate new metrics and, by enhancing research publishing tools in the scholarly commons, facilitate various communities of practice. However, for preprint repositories to be sustainable, scholarly communities and funding agencies should support continued investment in open knowledge, alternative metrics development, and open infrastructures in scholarly publishing.

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“…Most rely on the use of DOIs, which assumes that these are widely used, but this does not yet appear to be the case in archaeology: for instance, Google searches for the DOIs of random ADS archives led back to the original archive rather than to references to the archive, even in cases where the archives were known to have been reused and cited. Event services such as those being developed by DataCite and Crossref are intended to capture the broader range of reuses but are dependent on the use of persistent identifiers (Dappert et al 2017; Robinson-Garcia et al 2017). Until archaeologists consistently use DOIs or other such persistent identifiers for their data, the capture of altmetrics for archaeological data citation seems equally problematic and equally unreliable as standard data citations, as indeed is the experience elsewhere (Peters et al 2016).…”

Section: Absence Of Evidence and Evidence Of Absencementioning

confidence: 99%

Reuse Remix Recycle

Huggett

2018

Adv. archaeol. pract.

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Preservation of digital data is predicated on the expectation of its reuse, yet that expectation has never been examined within archaeology. While we have extensive digital archives equipped to share data, evidence of reuse seems paradoxically limited. Most archaeological discussions have focused on data management and preservation, and on disciplinary practices surrounding archiving and sharing data. This paper addresses the reuse side of the data equation through a series of linked questions: what is the evidence for reuse, what constitutes reuse, what are the motivations for reuse, and what makes some data more suitable for reuse than others? It concludes by posing a series of questions aimed at better understanding our digital engagement with archaeological data.La conservación de los datos existentes en formato digital se basa en la expectativa de su posterior reutilización y aprovechamiento. Sin embargo, esta expectativa, como posibilidad razonable, nunca ha sido examinada dentro del campo de la arqueología. Aunque contamos con grandes repositorios digitales equipados para compartir datos, las evidencias de casos de una reutilización clara de los mismos parecen ser, paradójicamente, limitadas. La mayor parte de los análisis acerca de estas cuestiones desde la arqueología se han centrado en cómo gestionar y conservar los datos, y también en las prácticas de almacenamiento y acceso compartido a los datos llevadas a cabo dentro de la disciplina. Este artículo aborda el aspecto de la reutilización de los datos en este contexto a través de una serie de preguntas vinculadas entre sí: ¿Qué evidencias o casos de reutilización existen? ¿Qué constituye realmente una reutilización de datos?, ¿Cuáles son las motivaciones para su reutilización, y qué hace que algunos datos sean más adecuados para reutilizar que otros? Así mismo, el artículo concluye planteando una serie de preguntas enfocadas a comprender mejor nuestra relación entre el medio digital y los datos arqueológicos."The best thing to do with your data will be thought of by someone else" (Rufus Pollock, cited in Wentworth 2008) The Digital Data ParadoxIn 1995, Brian Fagan drew attention to what he called "archaeology's dirty secret" -the failure of archaeologists to publish definitive reports on their fieldwork, pointing to problems in scholarly culture including a focus on funding field research rather than analysis or publication (Fagan 1995:16). He identified the digital as a catalyst for change: "The demands of the electronic forum will make it harder to duck the responsibility of preparing one's data for scholarly use and scrutiny. In many cases, 'publication' will consist of meticulously organized databases, including graphics." (Fagan 1995:17). In the intervening years there has been a significant development of digital 2 repositories in the UK, USA and elsewhere facilitating this vision by providing for the preservation and distribution of archaeological data. However, rather than resolving archaeology's 'dirty secret', they have in fact u...

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DataCite as a novel bibliometric source: Coverage, strengths and limitations

Cited by 25 publications

References 18 publications

Assessing the Impact and Quality of Research Data Using Altmetrics and Other Indicators

Assessing the Impact and Quality of Research Data Using Altmetrics and Other Indicators

Preprints in Scholarly Communication: Re-Imagining Metrics and Infrastructures

Reuse Remix Recycle

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