[Special issue] Quantitative Science Studies (QSS) on "Scientific Knowledge Graphs and Research Impact Assessment"

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Angelo Salatino

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Sep 29, 2020, 4:48:02 AM9/29/20
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Dear colleagues,


Please find attached below the details of the call for papers for the Quantitative Science Studies (QSS) special issue on “Scientific Knowledge Graphs and Research Impact Assessment”.


Aim and Scope

In the last decades, there has been a huge increase in the volume of published scientific articles and related research objects (e.g., data sets, software packages). This trend gives rise to important challenges.

On the one hand, we have challenges related to the representation and organisation of such data. We urge for flexible, context-sensitive, fine-grained, and machine-actionable representations of scholarly knowledge that at the same time are structured, interlinked, and semantically rich, such as Scientific Knowledge Graphs (SKGs).

On the other hand, we have challenges related to research impact assessment. Due to the aforementioned growth in the volume of research outputs, rigorous approaches to research assessment are now more valuable than ever. In this context, we urge for reliable and comprehensive metrics and indicators of the scientific impact and merit of publications, data sets, research institutions, individual researchers, and other relevant entities. 

More details available here: https://www.mitpressjournals.org/pb-assets/pdfs/Calls%20for%20Papers/QSS_CFP_2020.pdf.


Topics of interest

  • Models:

    • Data models for the description of scholarly data and their relationships

    • Description and use of provenance information of scientific data

  • Methods:

    • Methods for extracting metadata, entities and relationships from scientific data

    • Methods for the (semi-)automatic annotation and enhancement of scientific data

    • Novel methods, indicators, and metrics for quality and impact assessment of scientific publications, datasets, software, and other relevant entities based on scholarly data

    • Methods and interfaces for the exploration, retrieval, and visualisation of scholarly data focussing on facilitating impact assessment

    • Studies of scientific knowledge graphs and citation networks for scholarly articles, data and software


Important Dates

  • Full paper submission: 31 January 2021

  • Review reports and invitation to submit revised paper: 31 March 2021 

  • Revised paper submission: 31 May 2021

  • Expected publication: September 2021


Best regards,

Paolo Manghi, ISTI-CNR, Italy

Andrea Mannocci, ISTI-CNR, Italy

Francesco Osborne, The Open University, UK

Dimitris Sacharidis, TU Wien, Austria

Angelo Salatino, The Open University, UK

Thanasis Vergoulis, “Athena” RC, Greece

-- Guest editors


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