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CHALLENGES OF SCHOLARLY COMMUNICATION: BIBLIOMETRIC TRANSPARENCY AND IMPACT
Analysing self-citations in a large bibliometric database
By Philipp Mayr-Schlegel
Citation metrics have value because they aim to make scientific assessment a level playing field, but urgent transparency-based adjustments are necessary to ensure that measurements yield the most accurate picture of impact and excellence. One problematic area is the handling of self-citations, which are either excluded or inappropriately accounted for when using bibliometric indicators for research evaluation. In this talk, in favour of openly tracking self-citations, I report on a study of self-referencing behaviour among various academic disciplines as captured by the curated bibliometric database Web of Science. Specifically, I examine the behaviour of thousands of authors grouped into 15 subject areas like Biology, Chemistry, Science and Technology, Engineering, and Physics. In this talk, I focus on the methodological set-up of the study and discuss data science related problems like author name disambiguation and bibliometric indicator modelling. This talk bases on the following publication: Kacem, A., Flatt, J. W., & Mayr, P. (2020). Tracking self-citations in academic publishing. Scientometrics, 123(2), 1157–1165. https://doi.org/10.1007/s11192-020-03413-9
Research impact beyond scholarly communication: the big challenge of Scientometrics 2.0
By Pei-Shan Chi & Wolfgang Glänzel
The last two decades in the evolution of bibliometrics mark a significant turn towards the quantification and measurement of scientific communication beyond the scholarly one and towards a broader assessment of its various impacts on science and society. We summarize the background and the main characteristics of this evolution, refer to latest results in our related studies, and focus on the latent and real challenges in the use of the new metrics designed for the measurement of the broader impact of research. In addition to the critical review several examples are given to illustrate the large potential and added value of the new metrics when used judiciously and correctly. In conclusion we will address and elaborate the framework of preconditions that are essential for improving coverage and reliability of both data sources and the metrics derived from those.
Why would a taxonomist interrogate the limitations of hierarchical thinking and information organization? Graphs offer more specific and flexible structures to model relationships between objects. This basic change of frame reflects more accurately the way humans understand information, provides flexible and extensible modelling options, and usurps existing (tree-based, or arboreal) power and information structures in favour of a decentralized, democratized information environment with no beginning and no end.
Bob is a taxonomist and ontologist at Factor, an information architecture consultancy, interested in knowledge graphs and Linked Data.
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BIBLIOMETRIC EXPERIMENT WITH THE FULL TEXT OF RESEARCH PAPERS
Are self-citations a normal feature of knowledge accumulation?
By Vincent Larivière
Science is a cumulative activity, in which past knowledge serves as a foundation for new knowledge. One of the mechanisms through which the cumulative nature of science manifests itself is the act of citing. However, citations are also central to research evaluation, thus creating incentive for researchers to cite their own work. Therefore, such self-citations have been one of the most constant criticism against the use of citation indicators for the measurement of research impact. Using a dataset containing millions of papers and disambiguated authors, this talk will examine the relative importance of self-citations and self-references in the scholarly communication landscape, their relationship with age and gender of authors, as well as their effects on various research evaluation indicators. It will also present the results of a comparison of the content of cited and citing papers, thus making it possible to test whether researchers cite their own work in order to inflate their impact indicators. The talk with conclude with a discussion of the role of self-citations in the research ecosystem.
Understanding scientific disagreement
By Dakota Murray
Healthy disagreement among scientists drives the creation of new knowledge and is a necessary precursor to consensus upon which technologies, policies, and new knowledge can be built. Yet, in spite of its prominence in popular and theoretical models of scientific progress, disagreement has received little empirical attention, with progress stymied by a lack of appropriate data and widely-accepted quantitative indicators. In this talk, we outline progress in overcoming these challenges, illustrating how increasingly-available full-text data and new approaches to measuring disagreement are paving the way for a more comprehensives, empirical, and quantitative understanding of the salience and features of disagreement in science at multiple levels of analysis. Using a rigorously-validated cue-word based approach, instances of disagreement are identified from the citation sentences of millions of publications, and incorporated into a singular indicator of disagreement. Using this indicator, we simultaneously reveal the structure of disagreement between macro-level fields and the enormous heterogeneity across meso-level subfields. At the micro-level, we complement these data with published comments—the most unambiguous instance of criticism in science—in order to better understand the sociological drivers of disagreement, including author gender, seniority, prestige, and more. This project establishes a firm methodological and empirical foundation for a science of scientific disagreement, which will prove essential for validating theories of scientific progress, building tools for scholarly search and discovery, designing consensus-aware science policy, and for effectively communicating epistemic uncertainty and consensus to the public.
Two short talks showcasing developments in knowledge organization tooling.
Phil will talk about Vocabs Editor, a service to create, edit and export SKOS controlled vocabularies in an efficient and user-friendly manner.
Eugene will talk about Taxonomies for Confluence, a Confluence add-on that lets users to index pages and build tables of contents using SKOS controlled vocabularies and integrate Confluence content into knowledge graphs.
Phil Stacey works for Barratt Homes implementing document management and fire safety in the southern counties division. Phil has over 25 years of experience in the construction industry working in design and information management. He is passionate about realising the business benefit of structured data and the benefits BIM (Building Information Modelling) software can deliver through its implementation at scale, across the housing sector.
Eugene Morozov is building Taxonomies for Confluence add-on.
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