May 2021 - sem-grd - lists.ogf.org

CfP ISWC 2021 - Call for Research, In-Use, Resource, Doctoral Consortium papers
by International Semantic Web Conference 28 Jun '21

28 Jun '21

20th International Semantic Web Conference (ISWC 2021) Virtual, October 24-28, 2021 https://iswc2021.semanticweb.org In this announcement: 1. Call for Research papers 2. Call for In-Use papers 3. Call for Resource papers 4. Call for Doctoral Consortium papers 1. Call for Research papers ******************************************* In this track of ISWC 2021, we are looking for novel and significant research contributions addressing theoretical, analytical and empirical aspects of the Semantic Web. While we welcome work that relates to the W3C Semantic Web recommendations (e.g., RDF, OWL, SPARQL, etc.), we also encourage contributions to research at the intersection of the Semantic Web and other scientific disciplines. Submissions to the research track should describe original, significant, and replicable research on the Semantic Web. All papers must include method evaluations that are rigorous, repeatable and reproducible. This will be one of the key reviewing criteria. We also strongly encourage papers that provide links to the data sets, source code and queries used to evaluate their approach, and/or live deployments. Topics of interest and further details: https://iswc2021.semanticweb.org/research-track Track Chairs: - Eva Blomqvist (University of Linköping, Sweden) - Andreas Hotho (University of Würzburg, Germany) Contact: iswc2021-program(a)easychair.org 2. Call for In-Use papers ******************************************* The In-Use track at ISWC 2021 continues the tradition of demonstrating and sharing the increasing adoption of Semantic Web technologies by providing a forum for the community to explore the benefits and challenges of applying such technologies in concrete, practical use cases, beyond the research communities from which they originate, in contexts ranging from industry to government and society. The In-Use track thus seeks submissions describing applied and validated solutions such as software tools, systems or architectures that benefit from the use of Semantic Web technologies (including, but not limited to, technologies based on the Semantic Web standards). Topics of interest and further details: https://iswc2021.semanticweb.org/in-use-call Track Chairs: - Ying Ding (University of Texas at Austin, USA) - Payam Barnaghi (Imperial College London, UK) Contact: iswc2021-in-use(a)easychair.org 3. Call for Resource papers ******************************************* The ISWC 2021 Resources Track aims to promote the sharing of resources which support, enable or utilise semantic web research. Resources include, but not restricted to: datasets, ontologies/vocabularies, ontology design patterns, evaluation benchmarks or methods, software tools/services, APIs and software frameworks, workflows, crowdsourcing task designs, protocols, methodologies and metrics, that have contributed or may contribute to the generation of novel scientific work. In particular, we encourage the sharing of such resources following best and well-established practices within the Semantic Web community. As such, this track calls for contributions that provide a concise and clear description of a resource and its usage. Topics of interest and further details: https://iswc2021.semanticweb.org/resources-track Track Chairs: - Stefan Dietze (GESIS, Cologne & Heinrich-Heine-University Düsseldorf, Germany)_ - Achille Fokoue (IBM Research, Yorktown Heights, NY, USA) ***** Important Dates (common to all paper tracks above) ***** - Abstracts Due: 12 April 2021 - Full Papers Due: 19 April 2021 - Author Rebuttals: 2–6 June 2021 - Notifications: 23 June 2021 4. Call for Doctoral Consortium papers ******************************************* The ISWC 2021 Doctoral Consortium (DC) will provide PhD students with an opportunity to: ● present and discuss their research ideas in a supportive, formative and yet critical environment; ● receive feedback from mentors, typically senior members of the Semantic Web research community, and peers; ● explore career pathways available after completing their PhD degree, and finally ● network and build collaborations with other members of the community. The event is intended for students who are midway through their PhD, therefore at a stage where they have articulated a reasonably detailed research proposal, preferably supported by some preliminary results. The aim is to support the students in refining their proposal and suggest possible ways to improve their research plan and achieve results with prospective greater impact. While doctoral degrees can vary in format and conduct, we aim this Call for Papers to PhD candidates in their second, or early in their third year and who will have already partially investigated some specific problems. Students will be required to submit a paper to the doctoral consortium, structured like a research proposal. All proposals submitted to the Doctoral Consortium will undergo a rigorous review process by the International Programme Committee, who will provide detailed and constructive feedback and select those submissions to be presented at the Doctoral Consortium. If accepted, students will have to register and attend the event, which will include a range of interactive activities. Details: https://iswc2021.semanticweb.org/doctoral-consortium-call DC Chairs: - Miriam Fernandez (Open University, UK) - Valentina Tamma (University of Liverpool, UK) ***** Important Dates (DC track) ***** - Papers due: 3 May, 2021 - Notification to proposers: 31 May 2021 - DC Day: 25 October, 2021 *** All deadlines are AoE (Anywhere on Earth) *** Submission link for all papers: https://easychair.org/conferences/?conf=iswc2021 Follow ISWC on social media: - Twitter: @iswc_conf #iswc_conf (https://twitter.com/iswc_conf) - LinkedIn: https://www.linkedin.com/groups/13612370 - Facebook: https://www.facebook.com/ISWConf The ISWC 2021 Organising Team https://iswc2021.semanticweb.org/organizing-committee

1 2

[CFP] 1st International Workshop on Ontology Uses and Contribution to Artificial Intelligence
by Sarra Ben Abbès 27 May '21

27 May '21

Dear colleagues and researchers, Please consider submitting a paper for the 1st International workshop on "Ontology Uses and Contribution to Artificial Intelligence" which will be held online or in Hanoi, Vietnam - November 6-12, 2021. ***** OnUCAI - CALL FOR PAPERS **** * *Ontology Uses and Contribution to Artificial Intelligence* * 1st International Workshop, in conjunction with *KR 2021 <https://kr2021.kbsg.rwth-aachen.de/> * November 6-12, 2021 - Online or in Hanoi, Vietnam* https://sites.google.com/view/ onucai-kr2021 ** Important dates ** - *Workshop paper submission due: *July 02, 2021 - *Workshop paper notifications: *August 06, 2021 - *Workshop paper camera-ready versions due: *September 06, 2021 - *Workshop registration deadline: *TBA - *Workshop: *November 06-12, 2021 All deadlines are 23:59 anywhere on earth (UTC-12) ** Workshop description ** An ontology is well known to be the best way to represent knowledge in a domain of interest. It is defined by Gruber as “an explicit specification of a conceptualization”. It allows us to represent explicitly and formally existing entities, their relationships and their constraints in an application domain. This representation is the most suitable and beneficial way to solve many challenging problems related to the information domain (e.g., knowledge representation, knowledge sharing, knowledge reusing, automated reasoning, knowledge capitalizing and ensuring semantic interoperability among heterogeneous systems). Using ontology has many advantages, among them we can cite ontology reusing, reasoning and explanation, commitment and agreement on a domain of discourse, ontology evolution and mapping, etc. As a field of artificial intelligence (AI), ontology aims at representing knowledge based on declarative and symbolic formalization. Combining this symbolic field with computational fields of IA such as Machine Learning (ML), Deep Learning (DL), Probabilistic Graphical Models (PGMs), Computer Vision (CV) and Natural Languages Processing (NLP) is a promising association. Indeed, ontological modeling plays a vital role to help AI reducing the complexity of the studied domain and organizing information inside it. It broadens AI’s scope allowing it to include any data type as it supports unstructured, semi-structured, or structured data format which enables smoother data integration. The ontology also assists AI for interpretation process, learning, enrichment, prediction, semantic disambiguation and discovering of complex inferences. Finally, the ultimate goal of ontologies is the ability to be integrated in a software to make sense of all information. In the last decade, ontologies are increasingly being used to provide background knowledge for several AI domains in different sectors (e.g. energy, transport, health, banking and insurance, etc.). Some of these AI domains are: - Machine learning and deep learning: semantic data selection, semantic data pre-processing, semantic data transformation, semantic data prediction, semantic clustering correction of the outputs, semantic enrichment with ontological concepts, use the semantic structure for promoting distance measure, etc. - Probabilistic Graphical Models: learning PGM (structure or parameters) using ontologies, probabilistic semantic reasoning, semantic causality and probability, etc. - Computer Vision: semantic image processing, semantic image classification, semantic object recognition/classification, etc. - Blockchain: semantic transactions, interoperable blockchain systems, etc. - Natural Language Processing: semantic text mining, semantic text classification, semantic role labelling, semantic machine translation, semantic question answering, ontology based text summarizing, semantic recommendation systems, etc. - Robotics: semantic task composition, task assignment, communication, cooperation and coordination, etc. - Voice-video-speech: semantic voice recognition, semantic speech annotation, etc. - Game Theory: semantic definition of specific games, semantic rules and goals definition, etc. - etc. ** Objective ** This workshop aims at highlighting recent and future advances on the role of ontologies and knowledge graphs in different domains of AI and how it can be used in order to reduce the semantic gap between the data, applications, machine learning process, etc., in order to obtain a semantic-aware approaches. In addition, the goal of this workshop is to bring together an area for experts from industry, science and academia to exchange ideas and discuss results of on-going research in ontologies and AI approaches. We invite the submission of original works that is related -- but are not limited to -- the topics below. ** Topics of interests ** - Ontology for Machine Learning/Deep Learning - Ontology for Probabilistic Graphical Models - Ontology for Federated Machine Learning - Ontology for Smart Contracts - Ontology for Computer Vision - Ontology for Natural Language Processing - Ontology for Robotics and Multi-agent Systems - Ontology for Voice-video-speech - Ontology for Game Theory - and so on. ** Submission * * The workshop is open to submit unpublished work resulting from research that presents original scientific results, methodological aspects, concepts and approaches. All submissions are not anonymous and must be PDF documents written in English and formatted using the following style files: *KR2021_authors_kit <https://www.google.com/url?q=https%3A%2F%2Fkr2021.kbsg.rwth-aachen.de%2Fdow…>* Papers are to be submitted through the workshop's *EasyChair <https://www.google.com/url?q=https%3A%2F%2Feasychair.org%2F&sa=D&sntz=1&usg…>* submission page. We welcome the following types of contributions: - *Full papers* of up to 9 pages, including abstract, figures and appendices (if any), but excluding references and acknowledgements: Finished or consolidated R&D works, to be included in one of the Workshop topics. - *Short papers* of up to 4 pages, excluding references and acknowledgements: Ongoing works with relevant preliminary results, opened to discussion. At least one author of each accepted paper must register for the workshop, in order to present the paper. For further instructions, please refer to the *KR 2021 <https://www.google.com/url?q=https%3A%2F%2Fkr2021.kbsg.rwth-aachen.de%2F&sa…>* page. ** Workshop chairs ** - Sarra Ben Abbès, Engie, France - Lynda Temal, Engie, France - Nada Mimouni, CNAM, France - Ahmed Mabrouk, Engie, France - Philippe Calvez, Engie, France ** Program Committee ** - Shridhar Devamane, Physical Design Engineer, Tecsec Technologies, Bangalore, India **Publication* The best papers from this workshop may be included in the supplementary proceedings of KR 2021.

1 0

K-CAP 2021: First call for papers - deadline
by Marieke van Erp 18 May '21

18 May '21

*apologies for cross-posting* K-CAP 2021 The Eleventh International Conference on Knowledge December 2 - 3, 2021 A virtual conference https://www.k-cap.org/2021/ *Call for Papers* The massive quantity and increasing availability of information on the Web have catalyzed research in a wide range of fields. Today's data-driven world, however, needs more than an abundance of information, and there is a broadening focus on information quality and accuracy. Given the increasing demand for higher quality, accurate information that can be effectively and unambiguously used, the study of precise and scalable knowledge capture is of crucial importance. Knowledge capture involves the extraction of useful knowledge from multiple, potentially heterogeneous sources, as well as its acquisition directly from human experts. The International Conference on Knowledge Capture, K-CAP, is a forum that brings together members of disparate research communities who are interested in efficiently and precisely capturing knowledge from a variety of heterogeneous sources, and in creating representations that can be useful for automated reasoning, analysis, and other forms of machine processing, as well as to support users in knowledge-intensive collaborative tasks. To discuss and advance the goals of scalable and precise knowledge capture, K-CAP 2021 aims to attract researchers from diverse areas of artificial intelligence, including knowledge representation and reasoning, knowledge acquisition, semantic web, intelligent user interfaces for knowledge acquisition and retrieval, query processing and question answering over heterogeneous knowledge bases, novel evaluation paradigms, problem-solving and reasoning, agents, information extraction from structured or unstructured data, machine learning and representation learning, information enrichment and visualization, as well as researchers interested in cyber-infrastructures to foster the publication, retrieval, reuse, and integration of data. *Topics of interest* - Knowledge acquisition - Knowledge authoring - Knowledge extraction - Knowledge management - Knowledge publication - Knowledge capture from multimodal data, e.g., text, audio, visual - Knowledge capture for the Semantic Web and the Web of Linked Data - Knowledge capture and enrichment in specific domains such as earth and life sciences - Collaborative and social approaches to knowledge management and acquisition - Crowdsourcing for knowledge capture and refinement - Handling bias in knowledge capture - Knowledge capture from social environments and contexts - Problem-solving knowledge and methods - Knowledge-based markup techniques - Modeling methodologies for ontologies and knowledge graphs - Narrative intelligence - Knowledge capture through storytelling - Provenance and trust issues in knowledge intensive systems - Services and applications that enable or utilize data capture techniques - Semantic search and query enrichment - Knowledge engineering and knowledge governance - Ontology design patterns - Similarity measurement and analogy-based reasoning - Extracting knowledge graphs from unstructured/semi-structured and multimedia data - Summarization techniques for knowledge graphs - Visualization of knowledge graphs and visual query interfaces - Services and API for knowledge graphs - Addressing scalability issues for distributed knowledge graphs - Automated construction, enrichment and cleaning of knowledge graphs and alignment to existing graphs - Hybrid approaches for knowledge capture combining knowledge engineering and machine learning - Data dynamicity, heterogeneity, and decay in knowledge intensive systems *Submissions* The eleventh International Conference on Knowledge Capture, K-CAP 2021, features a full papers track for research papers, as well as tracks for short papers, for visionary ideas, and for demos. Full papers, which describe original research, can be up to 8 pages long including references. Full papers will appear in the conference proceedings and will be citable as K-CAP 2021 publications. Short papers, which may describe (possibly preliminary or open-ended) research, applications (academic, industrial or otherwise), and late breaking results, can be up to 4 pages long, including references. Short papers will also appear in the conference proceedings and will be citable as K-CAP 2021 publications. Visionary papers, which describe outrageous ideas or potentially preliminary, but highly innovative research, can be up to 2 pages long, including references. Visionary papers will be presented as short talks in the conference program. Demo,which exemplify applications or illustrate work presented in other submissions, can be up to 4 pages long, including references. Demos will be presented as short talks in the conference program. Authors of all paper types will present their work in plenary sessions during the conference. Presentation timing for the different types of papers will be announced once the program is crafted. K-CAP is not a double-blind conference, hence authors should list their names and affiliations on the submission. Please use the ACM 2 column SIG Conference Proceedings template for your submission. Submissions in HTML format are welcome, so long as authors of HTML submissions also provide a conversion of their submission to a PDF file that adheres to the required ACM template for proceedings. Papers submitted to the main conference track should not have been published before in an archival venue, or currently be under review in an archival venue. Authors are welcome to submit papers that have been published as a preprint on arXiv, or in a non-archival venue like a workshop. All submissions to K-CAP should be made through EasyChair: https://easychair.org/conferences/?conf=kcap21 This year we will embrace the FAIR principles by collecting structured metadata of the datasets, software, ontologies and methods generated by K-CAP submissions. Authors will be encouraged to add these resources in the EasyChair submission form (together with a brief description). Accepted papers with resources will be highlighted in the main K-CAP conference page. *Important Dates* - Paper submission: September 15, 2021 - Author notification: October 13, 2021 - Camera ready version due: October 25, 2021 - Conference dates: December 2-3, 2021 All deadlines are midnight AoE (Anywhere on Earth). -- https://www.mariekevanerp.com / @merpeltje Digital Humanities Lab / dhlab.nl KNAW Humanities Cluster / huc.knaw.nl https://odeuropa.eu - Sensory mining and olfactory heritage https://cultural-ai.nl - A lab for culturally valued AI

1 0

[CFP] 1st International Workshop on Ontology Uses and Contribution to Artificial Intelligence
by Sarra Ben Abbès 10 May '21

10 May '21

Dear colleagues and researchers, Please consider submitting a paper for the 1st International workshop on "Ontology Uses and Contribution to Artificial Intelligence" which will be held online or in Hanoi, Vietnam - November 6-12, 2021. ***** OnUCAI - CALL FOR PAPERS **** * *Ontology Uses and Contribution to Artificial Intelligence* * 1st International Workshop, in conjunction with *KR 2021 <https://kr2021.kbsg.rwth-aachen.de/> * November 6-12, 2021 - Online or in Hanoi, Vietnam* https://sites.google.com/view/onucai-kr2021 ** Important dates ** - *Workshop paper submission due: *July 02, 2021 - *Workshop paper notifications: *August 06, 2021 - *Workshop paper camera-ready versions due: *September 06, 2021 - *Workshop registration deadline: *TBA - *Workshop: *November 06-12, 2021 All deadlines are 23:59 anywhere on earth (UTC-12) ** Workshop description ** An ontology is well known to be the best way to represent knowledge in a domain of interest. It is defined by Gruber as “an explicit specification of a conceptualization”. It allows us to represent explicitly and formally existing entities, their relationships and their constraints in an application domain. This representation is the most suitable and beneficial way to solve many challenging problems related to the information domain (e.g., knowledge representation, knowledge sharing, knowledge reusing, automated reasoning, knowledge capitalizing and ensuring semantic interoperability among heterogeneous systems). Using ontology has many advantages, among them we can cite ontology reusing, reasoning and explanation, commitment and agreement on a domain of discourse, ontology evolution and mapping, etc. As a field of artificial intelligence (AI), ontology aims at representing knowledge based on declarative and symbolic formalization. Combining this symbolic field with computational fields of IA such as Machine Learning (ML), Deep Learning (DL), Probabilistic Graphical Models (PGMs), Computer Vision (CV) and Natural Languages Processing (NLP) is a promising association. Indeed, ontological modeling plays a vital role to help AI reducing the complexity of the studied domain and organizing information inside it. It broadens AI’s scope allowing it to include any data type as it supports unstructured, semi-structured, or structured data format which enables smoother data integration. The ontology also assists AI for interpretation process, learning, enrichment, prediction, semantic disambiguation and discovering of complex inferences. Finally, the ultimate goal of ontologies is the ability to be integrated in a software to make sense of all information. In the last decade, ontologies are increasingly being used to provide background knowledge for several AI domains in different sectors (e.g. energy, transport, health, banking and insurance, etc.). Some of these AI domains are: - Machine learning and deep learning: semantic data selection, semantic data pre-processing, semantic data transformation, semantic data prediction, semantic clustering correction of the outputs, semantic enrichment with ontological concepts, use the semantic structure for promoting distance measure, etc. - Probabilistic Graphical Models: learning PGM (structure or parameters) using ontologies, probabilistic semantic reasoning, semantic causality and probability, etc. - Computer Vision: semantic image processing, semantic image classification, semantic object recognition/classification, etc. - Blockchain: semantic transactions, interoperable blockchain systems, etc. - Natural Language Processing: semantic text mining, semantic text classification, semantic role labelling, semantic machine translation, semantic question answering, ontology based text summarizing, semantic recommendation systems, etc. - Robotics: semantic task composition, task assignment, communication, cooperation and coordination, etc. - Voice-video-speech: semantic voice recognition, semantic speech annotation, etc. - Game Theory: semantic definition of specific games, semantic rules and goals definition, etc. - etc. ** Objective ** This workshop aims at highlighting recent and future advances on the role of ontologies and knowledge graphs in different domains of AI and how it can be used in order to reduce the semantic gap between the data, applications, machine learning process, etc., in order to obtain a semantic-aware approaches. In addition, the goal of this workshop is to bring together an area for experts from industry, science and academia to exchange ideas and discuss results of on-going research in ontologies and AI approaches. We invite the submission of original works that is related -- but are not limited to -- the topics below. ** Topics of interests ** - Ontology for Machine Learning/Deep Learning - Ontology for Probabilistic Graphical Models - Ontology for Federated Machine Learning - Ontology for Smart Contracts - Ontology for Computer Vision - Ontology for Natural Language Processing - Ontology for Robotics and Multi-agent Systems - Ontology for Voice-video-speech - Ontology for Game Theory - and so on. ** Submission * * The workshop is open to submit unpublished work resulting from research that presents original scientific results, methodological aspects, concepts and approaches. All submissions are not anonymous and must be PDF documents written in English and formatted using the following style files: *KR2021_authors_kit <https://www.google.com/url?q=https%3A%2F%2Fkr2021.kbsg.rwth-aachen.de%2Fdow…>* Papers are to be submitted through the workshop's *EasyChair <https://www.google.com/url?q=https%3A%2F%2Feasychair.org%2F&sa=D&sntz=1&usg…>* submission page. We welcome the following types of contributions: - *Full papers* of up to 9 pages, including abstract, figures and appendices (if any), but excluding references and acknowledgements: Finished or consolidated R&D works, to be included in one of the Workshop topics. - *Short papers* of up to 4 pages, excluding references and acknowledgements: Ongoing works with relevant preliminary results, opened to discussion. At least one author of each accepted paper must register for the workshop, in order to present the paper. For further instructions, please refer to the *KR 2021 <https://www.google.com/url?q=https%3A%2F%2Fkr2021.kbsg.rwth-aachen.de%2F&sa…>* page. ** Workshop chairs ** - Sarra Ben Abbès, Engie, France - Lynda Temal, Engie, France - Nada Mimouni, CNAM, France - Ahmed Mabrouk, Engie, France - Philippe Calvez, Engie, France ** Program Committee ** - TBD **Publication* The best papers from this workshop may be included in the supplementary proceedings of KR 2021.

1 0

[CFP] Call for Abstracts and Call for the e-Business 2021 Doctoral Consortium (Submission Deadline :: 12th of May)
by calendarsites＠insticc.org 05 May '21

05 May '21

Dear Colleagues, ICE-B 2021 is welcoming abstract submissions and also contributions to the e-Business 2021 Doctoral Consortium, until the 12th of May. ABSTRACT TRACK: In order to ensure a proper and fair review of the abstracts, we encourage authors to submit abstracts with clear insights and background of the work, and to include complementing material that can help the panel understand its contribution and relevance to the conference. Complementing material could include, for example, previously published papers or videos related to the abstract, to enrich the abstract submission. Abstracts that bring an appropriate complementing material are eligible for oral or poster presentation; otherwise, they are eligible for poster presentation only. Oral presentations are given a 20' minutes time slot. Abstracts will be advertised in the conference program and in the conference book of abstracts (in the printed and digital version), but not published DOCTORAL CONSORTIUM: The ICE-B 2021 Doctoral Consortium aims to improve the research of PhD students and broaden their perspectives by giving them the opportunity to share and develop their research ideas in a supportive environment, get feedback from senior members, improve their communication skills, exchange ideas, and build relationships with other PhD students. Accepted contributions will be presented in a dedicated conference session where participants will discuss their research ideas and results, and receive constructive feedback from an audience consisting of their peers as well as more senior experts in the field. In addition to that, students will be invited to participate at poster sessions so that they also receive comments of other participants in the conference. IMPORTANT DATES: Submission deadline: May 12, 2021 Notification of acceptance: May 25, 2021 Camera Ready and Registration: June 3, 2021 For more information, you may send an email to: <mailto:%20ice-b.secretariat@insticc.org> ice-b.secretariat(a)insticc.org or visit the conference website: <http://www.ice-business.org/> http://www.ice-business.org/

1 0