Call for Papers |
|
Making Sense of Stream Data
------------------ Call for Papers ------------------ The Journal of Web Semantics (https://www.journals.elsevier.com/journal-of-web-semantics/) invites submissions for a special issue on Making Sense of Stream Data, to be edited by Albert Bifet, Emanuele Della Valle, Danh Le Phuoc, and Konstantin Schekotihin. Our growing ability to collect, integrate, store, and analyze massive data fuels scientific breakthroughs and technological innovations. However, in a world where volatility, uncertainty, complexity, and ambiguity are the new normal, making sense of historical data is no longer enough. First, in the 2020s’ the demand for storage will exceed the production capability by an order of magnitude. This exponential inflation will thus require analyzing almost 30% of global data in real-time. Second, when changes hit, those who employ historical data analytics discover that their models are no longer relevant. COVID-19 is one of those changes. In this special issue, we call researchers from the various areas such as Knowledge Representation, Semantic Web, Complex Event Processing, Streaming Machine Learning, or Stream Processing for theoretical contributions, novel algorithms, artifacts, and tools to realize successful systems. Moreover, we invite practitioners from any application domain that deals with data streams to report their experiences, best practices, and insights. ------------------ Important Dates ------------------ - Call for papers: 01 Oct 2021 - Submission deadline: **31 May 2022** - Author notification: 31 Jul 2022 - Second round: 31 Aug 2022 - Final notification: 31 Oct 2022 - Publication: appr. Q1 2023 ------------------ Topics of Interest ------------------ Topics of interest focused on data streams include, but are not limited to: - Continuous query answering - Complex event processing and recognition - Ontological query answering over data streams - Probabilistic reasoning for data streams - Rule- and logic-based knowledge representation and reasoning - Neural-symbolic and statistical relational learning approaches - Novelty, and concept drift detection - Learning to forget and resistance to catastrophic forgetting - Incremental, online, and continuous/lifelong machine learning - Trustworthy AI over streams - Reinforcement learning over streams - Handling incomplete and noisy data - Approximation approaches to data processing - Publishing and consuming data streams - Parallelization and distribution of data processing - Topologies for distributed processing - Implementation and evaluation experiences - Development concerns, including deployment, scalability, and complexity - Proposals for datasets and benchmarks The list of application domains includes, but is not limited to: - Internet and Web of Things - Industry 4.0 - Online/Real-Time Planning and Scheduling - Evolving textual, multimedia, social media data streams - Evolving graphs in social networks, biological networks, cybersecurity - Adaptive recommender and filtering systems - Autonomous driving and robotics - Anomaly detection and diagnosis ------------------ Preliminary Review Committee ------------------ - Alexander Artikis, University of Piraeus, Greece - Maroua Bahri, Télécom Paris - Institut Polytechnique de Paris, France - Albert Bifet, University of Waikato, New Zealand - Eva Blovmquist, Linköping University, Sweden - Jean-Paul Calbimonte, EPFL, Switzerland - José Campo Ávila, Universidad de Málaga, Spain - Oscar del Corcho, Universidad Politécnica de Madrid, Spain - Daniele Dell’Aglio, Aalborg University, Danmark - Heitor Murilo Gomes, University of Waikato, New Zealand - Mark Greaves, Pacific Northwest National Laboratory, USA - Fredrik Heintz, Linköping University, Sweden - Yun Sing Koch, University of Auckland, New Zealand - Nicolas Kourtellis, Telefonica, Spain - Alessandro Margara, Politecnico di Milano, Italy - Deborah McGuinness, Rensselaer Polytechnic Institute, USA - Boris Motik, University of Oxford, United Kingdom - Özgür Lütfü Özcep, University of Lübeck, Germany - Jeff Z. Pan, University of Aberdeen, United Kingdom - Josiane Xavier Parreira, Siemens AG, Austria - Patrik Schneider, TU Vienna and Siemens AG, Austria - Sabri Skhiri, Eura Nova, Belgium - Riccardo Tommasini, Tartu, Estonia - Trung Kien Tran, Bosch, Germany - Anni-Yasmin Turhan, TU Dresden, Germany - Jacopo Urbani, Vrije Universiteit Amsterdam, Netherlands - Michael Zakharyaschev, Birbeck College, UK ------------------ Submission Guidelines ------------------ For this special issue, we are seeking two types of papers: - _Research papers_ describing novel and significant scientific contributions. Those papers are typically 15-20 pages long. - _System papers_ that focus on the description of stream reasoning systems where the authors fully detail the design, construction, implementation, and usage as well as demonstrate its usefulness. Those papers are expected to be 6-8 pages long. The _Journal of Web Semantics_ solicits original scientific contributions of high quality. Following the overall mission of the journal, we emphasize the publication of papers that combine theories, methods, and experiments from different subject areas in order to deliver innovative semantic methods and applications. The publication of large-scale experiments and their analysis is also encouraged to clearly illustrate scenarios and methods that introduce semantics into existing Web interfaces, contents, and services. Submission of your manuscript is welcome provided that it, or any translation of it, has not been copyrighted or published and is not being submitted for publication elsewhere. Manuscripts should be prepared for publication in accordance with instructions given in the JWS guide for authors (http://www.elsevier.com/journals/journal-of-web-semantics/1570-8268/guide-for-authors) and use the two-column variant of the style. The submission and review process will be carried out using Elsevier's Web-based (https://www.editorialmanager.com/JOWS/default.aspx). Please state the name of the SI in your cover letter and, at the time of submission, please select “**VSI:SR**” when reaching the Article Type selection. Upon acceptance of an article, the author(s) will be asked to transfer the copyright of the article to the publisher. This transfer will ensure the widest possible dissemination of information. Elsevier's liberal preprint policy (https://www.elsevier.com/authors/journal-authors/submit-your-paper/sharing-and-promoting-your-article) permits authors and their institutions to host preprints on their websites. Preprints of the articles will be made freely accessible via JWS First Look (https://papers.ssrn.com/sol3/JELJOUR_Results.cfm?form_name=journalbrowse&journal_id=3169691). Final copies of accepted publications will appear in print and at Elsevier's archival online server. |
Credits and Sources |
| [1] MSSD 2022 : Making Sense of Stream Data - special issue of the Journal of Web Semantics |
