KDK 2017

About

The new biennial conference series on Language, Data and Knowledge (LDK) aims at bringing together researchers from across disciplines concerned with the acquisition, curation and use of language data in the context of data science and knowledge-based applications. With the advent of the Web and digital technologies, an ever increasing amount of language data is now available across application areas and industry sectors, including social media, digital archives, company records, etc. The efficient and meaningful exploitation of this data in scientific and commercial innovation is at the core of data science research, employing NLP and machine learning methods as well as semantic technologies based on knowledge graphs

Language data is of increasing importance to machine learning-based approaches in NLP, Linked Data and Semantic Web research and applications that depend on linguistic and semantic annotation with lexical, terminological and ontological resources, manual alignment across language or other human-assigned labels. The acquisition, provenance, representation, maintenance, usability, quality as well as legal, organizational and infrastructure aspects of language data are therefore rapidly becoming major areas of research that are at the focus of the conference.

Knowledge graphs is an active field of research concerned with the extraction, integration, maintenance and use of semantic representations of language data in combination with semantically or otherwise structured data, numerical data and multimodal data among others. Knowledge graph research builds on the exploitation and extension of lexical, terminological and ontological resources, information and knowledge extraction, entity linking, ontology learning, ontology alignment, semantic text similarity, Linked Data and other Semantic Web technologies. The construction and use of knowledge graphs from language data, possibly and ideally in the context of other types of data, is a further specific focus of the conference.

A further focus of the conference is the combined use and exploitation of language data and knowledge graphs in data science-based approaches to use cases in industry, including biomedical applications, as well as use cases in humanities and social sciences.

The LDK conference has been initiated by a consortium of researchers from the Insight Centre for Data Analytics, InfAI (University Leipzig) and Wolfgang Goethe University and a Scientific Committee of leading researchers in Natural Language Processing, Linked Data and Semantic Web, Language Resources and Digital Humanities. LDK is endorsed by several international organisations: DBpedia, ACL SIGANN, Global Wordnet Association, CLARIN and Big Data Value Association (BDVA). The first edition, LDK 2017, will be held in Galway (Ireland) with a second edition planned for 2019 in Leipzig (Germany).

Calls

Paper submission

We welcome submission of both long and short papers of relevance to the topics listed below. Submissions can be in the form of long or short research papers, scientific abstracts on use cases or position papers. Accepted submissions will be published in a conference proceedings and will be selected for presentation as oral or poster presentation based on recommendations of reviewers, this choice does not reflect the quality of the work.

Topics

Language Data

Language data portals Language data construction, acquisition and management Crowdsourcing of language data Metadata about language data Multilingual, multimedia and multimodal language data Evaluation, provenance and quality of language data Usability, validation and visualization of language data Organizational and infrastructural management of language data Standards and interoperability of language data Legal aspects of publishing language data Typological databases Under-resourced languages Knowledge Graphs

Ontologies, terminology, wordnets and lexical resources Information and knowledge extraction (taxonomy extraction, ontology learning) Data, information and knowledge integration across languages (Cross-lingual) Ontology Alignment Semantic text similarity Entity linking and relatedness Linked Data profiling Linguistic Linked Data Multilingual Linked Data and multilingual Web of Data Knowledge representation and reasoning on the Multilingual Semantic Web Applications in NLP

Semantic search Semantic content management Question answering Computer-aided Language Learning Text analytics for Internet of Things Multilingual Internet of Things Applying big data to text analytics Natural language interfaces to (big) data Use Cases in Digital Humanities, Social Sciences, BioNLP

Applications in Digital Humanities such as distant reading Analysis, enrichment of text archives Text mining for Social Science research Text mining from biomedical literature

Organisation

Organising Committee

Paul Buitelaar (Insight Centre for Data Analytics, NUI Galway) Christian Chiarcos (Goethe Universität Frankfurt) Sebastian Hellmann (InfAI, Universität Leipzig) John P. McCrae (Insight Centre for Data Analytics, NUI Galway) Local organisers (Insight Centre for Data Analytics, NUI Galway)

Paul Buitelaar John P. McCrae Brian Davis Cécile Robin Mihael Arčan Housam Ziad (Webmaster) Scientific Advisory Committee

Pushpak Bhattacharyya (IITP, India) Francis Bond (Nanyang Technological University, Singapore) Key-Sun Choi (KAIST, South Korea) Philipp Cimiano (Bielefeld University, Germany) Edward Curry (Insight Centre for Data Analytics, NUI Galway, Ireland) Franciska de Jong (Utrecht University, The Netherlands) Thierry Declerck (DFKI GmbH, Saarland University, Germany) Tatjana Gornostaja (Tilde, Latvia) Jorge Gracia, (Universidad Politécnica de Madrid, Spain) Nancy Ide (Vassar College, USA) Eric Nyberg (Carnegie Mellon University, USA) Felix Sasaki (DFKI GmbH, W3C Fellow, Germany) Karin Verspoor (University of Melbourne, Australia)