<div dir="ltr"><div dir="ltr"><div dir="ltr"><div dir="ltr" class="gmail_signature"><div dir="ltr"><div>Dear colleague,</div><div>We have extended the submissions deadline of the 2nd International Workshop on Scientific Knowledge Representation, Discovery, and Assessment, to be held April 25-26, 2022 at The Web Conference (WWW) 2022.</div><div><br></div><div>-----------------------------------------------------------------------------------------------------------------------------</div><div>CALL FOR PAPERS</div><div>Sci-K – 2nd International Workshop on Scientific Knowledge Representation, Discovery, and Assessment in conjunction with The Web Conference (WWW) 2022</div><div> </div><div>April 25-29, 2022, Lyon, France (held virtually)</div><div>web: <a href="https://sci-k.github.io">https://sci-k.github.io</a>, twitter: @scik_workshop</div><div>Submission deadline: February 1st, 2022 <b style="background-color:rgb(255,153,0)">(extended to February 7th, 2022)</b></div><div>-----------------------------------------------------------------------------------------------------------------------------</div><div> </div><div> </div><div>Aim and Scope:</div><div> </div><div>In the last decades, we have experienced a substantial increase in the volume of published scientific articles and related research objects (e.g., data sets, software packages); a trend that is expected to continue. This opens up fundamental challenges including generating large-scale machine-readable representations of scientific knowledge, making scholarly data discoverable and accessible, and designing reliable and comprehensive metrics to assess scientific impact. The main objective of Sci-K is to provide a forum for researchers and practitioners from different disciplines to present, educate from, and guide research related to scientific knowledge. Specifically, we foresee three main themes that cover the most important challenges in the field: representation, discoverability, and assessment.</div><div> </div><div>Representation. There is an 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: Scientific Knowledge Graphs (SKGs). These resources can power several data-driven services for navigating, analysing, and making sense of research dynamics. Current challenges are related to the design of ontologies able to conceptualise scholarly knowledge, model its representation, and enable its exchange across different SKGs.</div><div> </div><div>Discoverability. It is important that scholarly information is easily findable, discoverable, and visible, so that it can be mined and organised within SKGs. Hence, we need discovery tools able to crawl the Web and identify scholarly data, whether on a publisher’s website or elsewhere – institutional repositories, preprint servers, open-access repositories, and others. This is a particularly challenging endeavour as it requires a deep understanding of both the scholarly communication landscape and the needs of a variety of stakeholders: researchers, publishers, funders, and the general public. Other challenges are related to the discovery and extraction of entities and concepts, integration of information from heterogeneous sources, identification of duplicates, finding connections between entities, and identifying conceptual inconsistencies.</div><div> </div><div>Assessment. Due to the continuous growth in the volume of research output, rigorous approaches for the assessment of research impact are now more valuable than ever. In this context, we urge reliable and comprehensive metrics and indicators of the scientific impact and merit of publications, datasets, research institutions, individual researchers, and other relevant entities. </div><div>-----------------------------------------------------------------------------------------------------------------------------</div><div> </div><div><div>Topics of Interest:</div><div> </div><div>•<span style="white-space:pre"> </span>Representation</div><div><span style="white-space:pre"> </span>-<span style="white-space:pre"> </span>Data models for the description of scholarly data and their relationships.</div><div><span style="white-space:pre"> </span>-<span style="white-space:pre"> </span>Description and use of provenance information of scientific data.</div><div><span style="white-space:pre"> </span>-<span style="white-space:pre"> </span>Integration and interoperability models of different data sources.</div><div>•<span style="white-space:pre"> </span>Discoverability</div><div><span style="white-space:pre"> </span>-<span style="white-space:pre"> </span>Methods for extracting metadata, entities and relationships from scientific data.</div><div><span style="white-space:pre"> </span>-<span style="white-space:pre"> </span>Methods for the (semi-)automatic annotation and enhancement of scientific data.</div><div><span style="white-space:pre"> </span>-<span style="white-space:pre"> </span>Methods and interfaces for the exploration, retrieval, and visualisation of scholarly data.</div><div>•<span style="white-space:pre"> </span>Assessment</div><div><span style="white-space:pre"> </span>-<span style="white-space:pre"> </span>Novel methods, indicators, and metrics for quality and impact assessment of scientific publications, datasets, software, and other relevant entities based on scholarly data.</div><div><span style="white-space:pre"> </span>-<span style="white-space:pre"> </span>Uses of scientific knowledge graphs and citation networks for the facilitation of research assessment.</div><div><span style="white-space:pre"> </span>-<span style="white-space:pre"> </span>Studies regarding the characteristics or the evolution of scientific impact or merit.</div></div><div> </div><div>-----------------------------------------------------------------------------------------------------------------------------</div><div> </div><div>Submission Guidelines:</div><div>•<span style="white-space:pre"> </span>Full research papers (up to 8 pages for main content)</div><div>•<span style="white-space:pre"> </span>Short research papers (up to 4 pages for main content)</div><div>•<span style="white-space:pre"> </span>Vision/Position papers (up to 4 pages for main content)</div><div> </div><div>The workshop calls for full research papers (up to 8 pages + 2 pages of appendices + 2 pages of references), describing original work on the listed topics, and short papers (up to 4 pages + 2 pages of appendices + 2 pages of references), on early research results, new results on previously published works, demos, and projects. In accordance with Open Science principles, research papers may also be in the form of data papers and software papers (short or long papers). The former present the motivation and methodology behind the creation of data sets that are of value to the community; e.g., annotated corpora, benchmark collections, training sets. The latter presents software functionality, its value for the community, and its application to a non-specialist reader. To enable reproducibility and peer-review, authors will be requested to share the DOIs of the data sets and the software products described in the articles and thoroughly describe their construction and reuse.</div><div> </div><div>The workshop will also call for vision/position papers (up to 4 pages + 2 pages of appendices + 2 pages of references) providing insights towards new or emerging areas, innovative or risky approaches, or emerging applications that will require extensions to the state of the art. These do not have to include results already, but should carefully elaborate about the motivation and the ongoing challenges of the described area.</div><div> </div><div> </div><div>Submissions for review must be in PDF format and must adhere to the ACM template and format. Submissions that do not follow these guidelines, or do not view or print properly, may be rejected without review. </div><div> </div><div>The proceedings of the workshops will be published jointly with The Web Conference 2022 proceedings.</div><div> </div><div>Submit your contributions following the link: <a href="https://sci-k.github.io/2022/#submission">https://sci-k.github.io/2022/#submission</a> </div><div> </div><div>-----------------------------------------------------------------------------------------------------------------------------</div><div> </div><div>Important Dates:</div><div>•<span style="white-space:pre"> </span>Paper submission: February 7th, 2022 (23:59, AoE timezone)</div><div>•<span style="white-space:pre"> </span>Notification of acceptance: March 3rd, 2022</div><div>•<span style="white-space:pre"> </span>Camera-ready due: March 10th, 2022 (SHARP)</div><div>•<span style="white-space:pre"> </span>Workshop day: April 25th or 26th, 2022</div><div> </div><div> </div><div>-----------------------------------------------------------------------------------------------------------------------------</div><div> </div><div>Organizing Committee (alphabetical order):</div><div> </div><div>Paolo Manghi, ISTI-CNR, Italy</div><div>Andrea Mannocci, ISTI-CNR, Italy</div><div>Francesco Osborne, The Open University, UK</div><div>Dimitris Sacharidis, Université Libre De Bruxelles, Belgium</div><div>Angelo Salatino, The Open University, UK</div><div>Thanasis Vergoulis, “Athena” RC, Greece</div><div><br></div>
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