Call for Papers
2nd Workshop at ESWC 2024 on Semantic Technologies and Deep Learning Models for Scientific, Technical and Legal Data

Workshop: May 26th or 27th, 2024 - Hersonissos, Greece
https://semtech4stld.github.io/

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Important Dates
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Abstract Submissions: March 1st, 2024
Paper Submissions: March 7th, 2024
Notifications: April 4th, 2024
Camera-Ready Contributions: April 18th, 2024
Final papers zip archive: April 18th, 2024
Workshop: May 26th or 27th, 2024


All deadlines are 11:59 pm, AoE time (Anywhere on Earth).


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Workshop Aims and Scope
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The rapid growth of online available scientific, technical, and legal data such as patents, and technical reports has made the large-scale analysis and processing of such data a crucial task. To benefit from the scientific-technical knowledge present in such documents, e.g., for decision-making or professional search and analytics, there is an urgent need for analyzing, enriching, and linking such data by employing state-of-the-art Semantic Web technologies and AI methods. To address the challenges mentioned above, Semantic Web Technologies, Natural Language Processing (NLP) techniques, Deep Neural Networks (DNN), and Large Language Models (LLMs) must be leveraged in order to provide efficient and effective solutions for creating easily accessible and machine-understandable data. This workshop aims to bring together researchers and professionals from these domains and provide a platform to engage in discussions, share ideas, and foster collaborative research initiatives.

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Workshop Keywords
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Large Language Models - Semantic Technologies - Deep Learning - Legal Data - Scientific Data - Natural Language Processing - Knowledge Graphs


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Workshop Topics
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The workshop accepts contributions in all topics related to semantic web technologies and deep learning focused (but not limited) to:
Data Collection
Leveraging Large Language Models (LLMs) for generating scientific, technical, and legal data.
New tools and systems for capturing scientific, technical, and legal data such as scientific articles, patent publications, etc.
Procedures and tools for storing, sharing, and preserving data.
Collecting and sharing data sets such as benchmarks, etc.
Pipelines and protocols to capture peculiarities from data.
Employing Semantic Web Technologies to represent and preserve sensitive data in terms of ethics, privacy, security, trust, etc.
Novel Semantic Technologies for scientific, technical and legal data
Ontologies and annotation schema to model such data.
Annotation, linking, and disambiguation of the data.
Knowledge graph construction.
LLMs to generate metadata, vocabularies, ontologies, and semantic models for specific data.
Applications for patents, scientific, technical and legal data by exploiting semantic technologies
Applications based on Generative AI and LLMs.
Exploiting knowledge graphs to drive document similarity, question answering, search etc.
Recommender systems.
Semantic content-based retrieval.
Natural language processing techniques for classification, summarization, etc.
Exploratory search using semantic technologies on scientific, technical, and legal data.
Key enabling tools (also based on LLMs) for semantic technologies on specific data and domains.
Lessons learned or/and use cases both from academia and industry around semantic models and LLMs for data in specific domains.


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Submission Details
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The submissions must be in English and adhere to the CEUR-WS one-column template: https://ceur-ws.org/Vol-XXX/ (see Session 2: The New CEURART Style). The papers should be submitted as PDF files to EasyChair. The review process will be single-blind. Please be aware that at least one author per paper must be registered and attend the workshop to present the work and that ESWC is a 100% in-person conference.
Full research papers (8-12 pages) should be clearly placed with respect to the state of the art and state the proposal's contribution in the application domain, even if presenting preliminary results. In particular, research papers should describe the methodology in detail, experiments should be repeatable, and a comparison with the existing approaches in the literature is encouraged.
Short papers (5-7 pages) should describe significant novel work in progress. Compared to full papers, their contribution may be narrower in scope, be applied to a narrower set of application domains, or have weaker empirical support than that expected for a full paper. Submissions likely to generate discussions in new and emerging scientific, technical, and legal data areas are encouraged.
Position or industry papers (3-5 pages) should introduce a new point of view in the workshop topics or summarize the experience of a group in the field.
Extended abstracts (1-2 pages) should introduce an ongoing work that aligns with the main scope of the workshop.
Submissions should be at most the indicated number of pages, including any diagrams and references.
Each submission will be reviewed by three independent reviewers based on relevance for the workshop, novelty/originality, significance, technical quality and correctness, quality and clarity of presentation, quality of references and reproducibility.
The accepted papers will be available on the Workshop website. The proceedings will be published in a CEUR-WS volume and consequently indexed on Google Scholar, DBLP, and Scopus.


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Workshop Chairs
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Rima Dessi’
https://www.fiz-karlsruhe.de/en/forschung/lebenslauf-und-publikationen-dr-rima-tuerker
FIZ - Karlsruhe Leibniz Institute for Information Infrastructure
Email: rima.dessi@fiz-karlsruhe.de

Danilo Dessi’
https://www.gesis.org/en/institute/staff/person/Danilo.Dessi
GESIS - Leibniz Institute for the Social Sciences
Email: danilo.dessi@gesis.org

Hidir Aras
https://www.fiz-karlsruhe.de/en/forschung/patents4science
FIZ- Karlsruhe Leibniz Institute for Information Infrastructure
Email: hidir.aras@fiz-karlsruhe.de

Francesco Osborne
https://people.kmi.open.ac.uk/francesco/
Knowledge Media Institute, The Open University
Email: francesco.osborne@open.ac.uk


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Contacts
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For general inquiries on the workshop, please send an email to rima.dessi@fiz-karlsruhe.de