The Third Wikidata Workshop

Call for Papers

Co-located with the 21st International Conference on Semantic Web (ISWC 2022).

Date: October 23 or 24, 2022

The workshop will be held online, afternoon European time.

Website: https://wikidataworkshop.github.io/2022/

== Important dates ==

Papers due: *Friday, *29 July 2022

Notification of accepted papers: Friday, September 23, 2022

Camera-ready papers due: Monday, October 3, 2022

Workshop date: October 23/24, 2022

== Overview ==

Wikidata is an openly available knowledge base, hosted by the Wikimedia Foundation. It can be accessed and edited by both humans and machines and acts as a common structured-data repository for several Wikimedia projects, including Wikipedia, Wiktionary, and Wikisource. It is used in a variety of applications by researchers and practitioners alike.

In recent years, we have seen an increase in the number of publications around Wikidata. While there are several dedicated venues for the broader Wikidata community to meet, none of them focuses on publishing original, peer-reviewed research. This workshop fills this gap - we hope to provide a forum to build this fledgling scientific community and promote novel work and resources that support it.

The workshop primarily seeks original contributions that address the opportunities and challenges of creating, contributing to, and using a global, collaborative, open-domain, multilingual knowledge graph such as Wikidata.

We encourage a range of submissions, including novel research, opinion pieces, and descriptions of systems and resources, which are naturally linked to Wikidata and its ecosystem or enabled by it. What we are less interested in are works that use Wikidata alongside or in lieu of other resources to carry out some computational task - unless the work feeds back into the Wikidata ecosystem, for instance by improving or commenting on some Wikidata aspect, or suggesting new design features, tools, and practices.

This year, we also added a track for already published work. To foster conversations around the topic of Wikidata, we invite authors of papers published at other conferences to submit their papers to present at the workshop. These will not be included in the proceedings but gives a chance for authors to interact with the community.

We welcome interdisciplinary work, as well as interesting applications that shed light on the benefits of Wikidata and discuss areas of improvement.

The workshop is planned as an interactive half-day event, in which most of the time will be dedicated to discussions and exchange rather than oral presentations. For this reason, all accepted papers will be presented in short talks and accompanied by a poster. All works will be presented online.

== Topics ==

Topics of submissions include, but are not limited to:

- Data quality and vandalism detection in Wikidata

- Referencing in Wikidata

- Anomaly, bias, or novelty detection in Wikidata

- Algorithms for aligning Wikidata with other knowledge graphs

- The Semantic Web and Wikidata

- Community interaction in Wikidata

- Multilingual aspects in Wikidata

- Machine learning approaches to improve data quality in Wikidata

- Tools, bots, and datasets for improving or evaluating Wikidata

- Participation, diversity, and inclusivity aspects in the Wikidata ecosystem

- Human-bot interaction

- Managing knowledge evolution in Wikidata

- Abstract Wikipedia

== Submission guidelines ==

We welcome the following types of contributions.

= Track 1: Novel Works =

The papers in this track will be peer-reviewed by at least three researchers. Accepted papers will be published as open access papers on CEUR (authors can also waive this). We invite the following types of papers:

- Full research paper: Novel research contributions (7-12 pages)

- Short research paper: Novel research contributions of smaller scope than full papers (3-6 pages)

- Position paper: Well-argued ideas and opinion pieces, not yet in the scope of a research contribution (6-8 pages)

- Resource paper: New dataset or other resources directly relevant to Wikidata, including the publication of that resource (8-12 pages)

- Demo paper: New system critically enabled by Wikidata (6-8 pages)

Submissions must be as PDF or HTML, formatted in the style of the Springer Publications format for Lecture Notes in Computer Science (LNCS). For details on the LNCS style, see Springer’s Author Instructions.

Papers have to be submitted through easychair (Please add “[NOVEL]” in the beginning of the title on the submission page so we know that you are submitting to this track): https://easychair.org/my/conference?conf=wikidataworkshop2022

= Track 2: Published works =

This track welcomes papers previously published at a peer-reviewed research venue, to be presented and discussed in the workshop. They do not have to follow the formatting and page limit instructions from Track 1, and can instead be submitted in the original format.

Previously published papers will be reviewed by the organising committee in terms of topical fit and prominence of the publication venue. They will not be published as part of the proceedings. We invite the following types of papers:

- Full research paper: Previously published research contributions

- Resource paper: Previously published datasets or other resources that are important or interesting to the community

- Demo paper: Presenting a previously published system critically enabled by Wikidata

Papers have to be submitted through easychair (please add “[PUBLISHED]” in the beginning of the title on the submission page so we know that you are submitting to this track): https://easychair.org/my/conference?conf=wikidataworkshop2022

== Proceedings ==

The complete set of papers from the Novel Works Track will be published with the CEUR Workshop Proceedings (CEUR-WS.org).

== Organizing committee ==

Lucie-Aimée Kaffee, University of Copenhagen, lucie.kaffee[[@]]gmail.com

Simon Razniewski, Max Planck Institute for Informatics, srazniew[[@]] mpi-inf.mpg.de

Kholoud Alghamdi, King's College London, kholoud.alghamdi[[@]]kcl.ac.uk

Gabriel Maia Rocha Amaral, King's College London, gabriel.amaral[[@]] kcl.ac.uk

== Programme committee ==

Seyed Amir Hosseini Beghaeiraveri, Heriot-Watt University Houcemeddine Turki, Data Engineering and Semantics Research Unit, University of Sfax, Tunisia

Filip Ilievski, Information Sciences Institute, University of Southern California, Marina del Rey, CA, USA

Mahir Morshed, University of Illinois at Urbana-Champaign

Daniel Garijo, Universidad Politécnica de Madrdid

Niel Chah, University of Toronto & Microsoft

Alasdair Gray, Heriot Watt University

Thomas Pellissier Tanon, Lexistems

John Samuel, CPE Lyon

Dennis Diefenbach, The QA Company

Heiko Paulheim, University of Mannheim

Cristina Sarasua, University of Zurich

Pavlos Vougiouklis, Huawei

Pierre-Henri Paris, Télécom Paris

Lydia Pintscher, Wikimedia Deutschland

Isaac Johnson, Wikimedia Foundation

Alessandro Piscopo, BCC

Luis Galárraga, Inria

Danai Symeonidou, INRAE

Andrew D. Gordon, Microsoft Research and University of Edinburgh

David Abián, King’s College London

Elisavet Koutsiana, King’s College London