- From: Julia Bosque Gil <jbosque@unizar.es>
- Date: Wed, 23 Sep 2020 13:33:20 +0200
- To: Julia Bosque Gil <jbosgil@gmail.com>
- Message-ID: <CA+B92MvUv5BZj6Sh0+G4+Tgp=K0oAYstU_9upn+z+RzDUbvnFQ@mail.gmail.com>
Apologies for cross-posting ====== 2nd Call for Papers: Special Issue on *Latest Advancements in Linguistic Linked Data* http://www.semantic-web-journal.net/blog/call-papers-special-issue-latest-advancements-linguistic-linked-data Contact email: swjadvancementslld@googlegroups.com *Deadline: 20th of November, 2020 * ====== In recent years, various efforts have arisen with regard to the representation and publication of linguistic resources such as lexicons, dictionaries, corpora, terminologies and linguistic ontologies. These efforts have exploited Semantic Web technologies and the Linguistic Linked Data (LLD) publication paradigm to facilitate and enhance the discovery, interoperability, integration and reusability of language resources. Initiatives such as the H2020 projects ELEXIS and Prêt-à-LLOD and the COST Action NexusLinguarum aim at developing robust ecosystems and networks of experts to address the LLD lifecycle, from identifying the requirements concerning the representation of linguistic resources to their exploitation by natural language processing (NLP) applications. With the rapid growth of the Linguistic Linked Open Data (LLOD) cloud and the increasing interest in the use of linked data for NLP, new challenges emerge concerning particular use cases and domain applications, language-specific features and quality dimensions, the evolution of LLD resources throughout time and the leverage of linguistic resources along LD technologies in NLP research, among other diverse aspects. This special issue on the latest advancements in LLD invites high-quality contributions, supported by a robust evaluation, which present an advancement in the state-of-the-art in the field of LLD methodologies and technologies and their use for NLP and provide insights into the new challenges ahead. The list of topics includes, but is not limited to, the following: - Knowledge Representation for Linguistic Data - Ontologies, vocabularies and linguistic category registries for linguistic data - Representation languages for linguistic data as LLD - Modelling challenges with state-of-the-art LLD models (e.g. OntoLex-Lemon) - Use case-based representation requirements for LLD - Ontology engineering for linguistic data representation: building, evaluation, evolution, alignment and reuse of ontologies for computational linguistics and NLP - LLD Generation and Evolution - Methodologies and workflows for LLD generation - Diachronic and sociolinguistic approaches to LLD generation and evolution - Innovative approaches to automatic LLD generation - Technically robust and systematically evaluated LLD resources - LLD for under-resourced and underrepresented languages and domains - Linking LLD sets across multiple dimensions and levels of linguistic description - LLD quality evaluation and resource curation - LLD extension, enrichment and evolution - LLD Publication, Querying and Visualization - Publication and metadata - IPR, licensing and privacy issues - LLD specific query techniques and languages - Supporting interfaces for different steps of the LLD lifecycle - Visualization of LLD - LLD and NLP research - LLD for NLP and NLP for LLD - Integration, exploitation and added value of LLD technologies and interoperable linguistic resources in NLP systems - LLD in Deep Learning-based NLP approaches - LLD in Big Data contexts - Applications and Use Cases - Automatic approaches for different steps of the LLD lifecycle - Knowledge extraction and representation from linguistic resources - LLD for research in specific domains (e.g. linguistics, digital humanities, life sciences, law, journalism, etc.) - LLD specific features and requirements from domain experts DeadlineSubmission deadline: 20th of November, 2020. Papers submitted before the deadline will be reviewed upon receipt. Guest editors The guest editors can be reached at swjadvancementslld@googlegroups.com . Julia Bosque-Gil, University of Zaragoza, Spain Milan Dojchinovski, Czech Technical University in Prague, Czech Republic Marieke van Erp, KNAW Humanities Cluster, Amsterdam, Netherlands Christian Chiarcos, Goethe Universität Frankfurt, Germany Philipp Cimiano, Bielefeld University, Germany -- Julia Bosque-Gil Aragon Institute of Engineering Research (I3A) University of Zaragoza Pronouns: she/her
Received on Wednesday, 23 September 2020 11:33:47 UTC