Wikidata Workshop (WD-WS)
|
|
Date: 24 October 2021
|
|
Time: Half Day (times tbd)
|
|
Organizers: Lucie-Aimée Kaffee, Simon Razniewski, and Aidan Hogan
|
| Wikidata is an open knowledge base hosted by the Wikimedia Foundation that can be read and edited by both humans and machines. Wikidata is a central hub of the Semantic Web, and is used in a variety of academic and industrial applications. |
|
| In recent years, we have seen an increase in the number of scientific publications around Wikidata. While there are a number of venues for the Wikidata community to exchange, none of those publish original research. With the Wikidata Workshop 2020, we started to give the research-focused part of the Wikidata community a venue to meet and exchange information and knowledge. |
|
| The Wikidata Workshop 2021 will focus on the challenges and opportunities of working on a collaborative open-domain knowledge graph such as Wikidata, which is edited by an international and multilingual community. We encourage submissions that study the influence such a knowledge graph has on the web of data, as well as those working on improving this knowledge graph itself. This workshop brings together everyone working around Wikidata in both the scientific field and industry to discuss trends and topics around this collaborative knowledge graph. |
|
Website: https://wikidataworkshop.github.io/2021/
|
|
|
|
Workshop on data and research objects management for linked open science (DaMaLOS)
|
|
DStefan Bischof and Gottfried Schenneate: 24 October 2021
|
|
Time: Half Day (times tbd)
|
|
Organizers: Leyla Jael G. Castro, Markus Stocker, and Dietrich Rebholz-Schuhmann
|
| Research data is the mirror of experimental work. Data, together with the software used to produce and analyze it, complements scientific publications and is core input to data- and knowledge-driven research. Most research activities follow the research data cycle, where data is continuously produced , transformed and (re)used, transitioning from one research to another. For this cycle to prosper, we require Research Data and Research Objects Management (RDM and ROM) plans supporting the findable, accessible, interoperable and reusable (FAIR) principles. Despite playing an important role, data on its own is not sufficient to establish Open Science nor Linked Open Science, i.e., Open Science plus Linked Open Data (LOD) principles. LOD principles, aka LOD 5 stars, follow objectives that overlap with FAIR principles and Open Science (e.g., LOD 5 stars include “openness” and the use of “non-proprietary open formats”). In this workshop we will explore what is required for RDM to effectively instantiate Linked Open Science, including effective support for LOD, automation by, e.g.,machine/deep learning approaches, FAIR and Data Spaces/Ecosystems. Furthermore, we are interested in innovations to also support other Research Objects such as software and workflows, in order to get an integrated layer supporting all the edges of Linked Open Science. We welcome contributions on data and research objects management plans, FAIRification supporting Open Science, linking approaches on metadata + publications + data + software, and research supporting open and transparent digital research ecosystems.
|
|
Website: https://zbmed.github.io/damalos
|
|
|
|
12th Workshop on Ontology Design and Patterns
|
|
Date: 24 October 2021
|
|
Time: Full Day (times tbd)
|
|
Organizers: Karl Hammar, Cogan Shimizu, Hande McGinty, Luigi Asprino, and Valentina Anita Carriero
|
| The workshop series covers issues related to quality in ontology design and ontology design patterns (ODPs) for data and knowledge engineering in Semantic Web. The increased attention to ODPs in recent years through their interaction with emerging trends of Semantic Web such as knowledge graphs can be attributed to their benefit for knowledge engineers and Semantic Web developers. Such benefits come in the form of a direct link to requirements, reuse, guidance, and better communication. The workshop’s aim is thus not just: 1) providing an arena for discussing patterns, pattern-based ontologies, systems, datasets, but also 2) broadening the pattern community by developing its own "discourse" for discussing and describing relevant problems and their solutions.
|
|
Website: http://ontologydesignpatterns.org/wiki/WOP:2021
|
|
|
|
Fourth International Workshop on Semantic Web Meets Health Data Management (SWH)
|
|
Date: 24 October 2021
|
|
Time: Full Day (times tbd)
|
|
Organizers: Haridimos Kondylakis, Praveen Rao, and Kostas Stefanidis
|
| The advancements in health-care have brought to the foreground the need for flexible access to health-related information and created an ever-growing demand for efficient data management infrastructures. To this direction, many challenges must be first overcome, enabling seamless, effective and efficient access to several health data sets and novel methods for exploiting the existing information. This workshop aims at putting together an interdisciplinary audience that is interested in the fields of semantic web, data management and health informatics to discuss the challenges in health-care data management and to propose new solutions for the next generation data-driven health-care systems.
|
|
Website: https://sites.google.com/view/swh2021/
|
|
|
|
CANCELLED - Joint Workshop on Scalable Semantic Web Knowledge Base Systems and Storing, Querying and Benchmarking the Web of Data (SSWS+QuWeDa)
|
|
Date: 24 October 2021
|
|
Time: Half Day (times tbd)
|
|
Organizers: Muhammad Saleem, Axel-Cyrille Ngonga Ngomo, Thorsten Liebig, Achille Fokoue, and Zhe Wu
|
| SSWS 2021 is the 14th edition of the successful Scalable Semantic Web Knowledge Base Systems workshop series. This workshop provides a forum for discussing application-oriented issues of Semantic Technologies, with the focus on the development and deployment of systems that turn large volumes of real-world data into actionable knowledge at industry domains. This imposes significant scalability requirements on storage and processing systems and demands for reliable workflows to curate and validate data from various sources. SSWS furthermore invites contributions that integrate methods and results from research on Property Graphs found in graph databases for instance as well as approaches that combine Knowledge Graphs with machine learning. SSWS welcomes submissions that address relevant research results, report on real-world deployments as well as describe benchmarks and capable back ends or system architectures.
|
|
Website: https://sites.google.com/view/quweda2021
|
|
|
|
Workshop on Deep Learning for Knowledge Graphs (DL4KG)
|
|
Date: 25 October 2021
|
|
Time: Full Day (times tbd)
|
|
Organizers: Mehwish Alam, Davide Buscaldi, Michael Cochez, Francesco Osborne, Diego Reforgiato Recupero, and Harald Sack
|
| Over the past years there has been a rapid growth in the use and the importance of Knowledge Graphs (KGs) along with their application to many important tasks. KGs are large networks of real-world entities described in terms of their semantic types and their relationships to each other. On the other hand, Deep Learning methods have also become an important area of research, achieving some important breakthrough in various research fields, especially Natural Language Processing (NLP) and Image Recognition. In order to pursue more advanced methodologies, it has become critical that the communities related to Deep Learning, Knowledge Graphs, and NLP join their forces in order to develop more effective algorithms and applications. This workshop aims to reinforce the relationships between these communities and foster inter-disciplinary research in the areas of KG, Deep Learning, and Natural Language Processing.
|
|
Website: https://alammehwish.github.io/dl4kg2021/
|
|
|
|
CANCELLED - 5th (Online) International Workshop on Semantic Web solutions for large-scale biomedical data analytics (SeWeBmeDA)
|
|
Date: 25 October 2021
|
|
Time: Half Day (times tbd)
|
|
Organizers: Ali Hasnain, Michel Dumontier, Dietrich Rebholz-Schuhmann, Brian Kirby and Tracy Robson
|
| The life sciences domain has been an early adopter of linked data and, a considerable portion of the Linked Open Data cloud is composed of life sciences data sets. The deluge of in flowing biomedical data, partially driven by high-throughput gene sequencing technologies, is a key contributor and motor to these developments. The available data sets require integration according to international standards, large-scale distributed infrastructures, specific techniques for data access, and offer data analytics benefits for decision support. Especially in combination with Semantic Web and Linked Data technologies, these promises to enable the processing of large as well as semantically heterogeneous data sources and the capturing of new knowledge from those. This workshop invites papers for life sciences and biomedical data processing, as well as the amalgamation with Linked Data and Semantic Web technologies for better data analytics, knowledge discovery and user-targeted applications. This research contribution should provide useful information for the Knowledge Acquisition research community as well as the working Data Scientist.
|
|
Website: https://sites.google.com/view/sewebmeda-2021/home
|
|
|
|
7th Workshop on Managing the Evolution and Preservation of the Data Web (MEPDaW)
|
|
Date: 25 October 2021
|
|
Time: Half Day (times tbd)
|
|
Organizers: Fabrizio Orlandi, Damien Graux, Julio Cesar dos Reis, and Maria-Esther Vidal
|
| There is a vast and rapidly increasing quantity of scientific, corporate, government, and crowd-sourced data openly published on the Web. Open Data plays a catalyst role in the way structured information is exploited on a large scale. A traditional view of digitally preserving these datasets by "pickling and locking them away" for future use, like groceries, conflicts with their evolution. There are several approaches and frameworks (Linked Data Stack, PoolParty Suite, etc.) that manage a full life-cycle of the Data Web. More specifically, these solutions are expected to tackle major issues such as the synchronisation problem (monitoring changes), the curation problem (repairing data imperfections), the appraisal problem (assessing the quality of a dataset), the citation problem (how to cite a particular version of a dataset), the archiving problem (retrieving a specific version of a dataset), and the sustainability problem (preserving at scale, ensuring long-term access). During the past six years, the MEPDaW workshop series has been gathering researchers from the community around these challenges. So far the series successfully published more than 30 research efforts allowing more than 50 individual authors to present and share their ideas.
|
|
Website: https://mepdaw-ws.github.io/2021/
|
|
|
|
6th International Workshop on Visualization and Interaction for Ontologies and Linked Data (VOILA)
|
|
Date: 25 October 2021
|
|
Time: Half Day (times tbd)
|
|
Organizers: Patrick Lambrix, Catia Pesquita, and Vitalis Wiens
|
| "A picture is worth a thousand words", we often say, yet many areas are in demand of sophisticated visualization techniques, and the Semantic Web is not an exception. The size and complexity of ontologies and Linked Data in the Semantic Web constantly grows and the diverse backgrounds of the users and application areas multiply at the same time. Providing users with visual representations and sophisticated interaction techniques can significantly aid the exploration and understanding of the domains and knowledge represented by ontologies and Linked Data. There is no one-size-fits-all solution but different use cases demand different visualization and interaction techniques. Ultimately, providing better user interfaces, visual representations and interaction techniques will foster user engagement and likely lead to higher quality results in different applications employing ontologies and proliferate the consumption of Linked Data.
|
|
Website: http://voila2021.visualdataweb.org/
|
|
|
|
The Sixteenth International Workshop on Ontology Matching (OM)
|
|
Date: 25 October 2021
|
|
Time: Full Day (times tbd)
|
|
Organizers: Pavel Shvaiko, Jérôme Euzenat, Ernesto Jiménez-Ruiz, Oktie Hassanzadeh, and Cássia Trojahn
|
| Ontology matching is a key interoperability enabler for the Semantic Web, as well as a useful technique in some classical data integration tasks dealing with the semantic heterogeneity problem. It takes ontologies as input and determines as output an alignment, that is, a set of correspondences between the semantically related entities of those ontologies. These correspondences can be used for various tasks, such as ontology merging, data interlinking, query answering or navigation over knowledge graphs. Thus, matching ontologies enables the knowledge and data expressed with the matched ontologies to interoperate.
|
|
Website: http://om2021.ontologymatching.org/
|
|
|
|
