<div dir="ltr">[Apologies for cross posting; please circulate among your colleagues]<div><br></div><div><br></div><div><h1 class="m_5821728405545145788gmail-title m_5821728405545145788gmail-gutter" style="margin:0px 10px 0.5em;padding:0px;font-size:20.8px;color:rgb(50,50,50);font-family:"Myriad Pro",Myriad,"Trebuchet MS",Arial,Helvetica,sans-serif;font-style:normal;font-variant-ligatures:normal;font-variant-caps:normal;letter-spacing:normal;text-align:start;text-indent:0px;text-transform:none;white-space:normal;word-spacing:0px;background-color:rgb(255,255,255);text-decoration-style:initial;text-decoration-color:initial">Call for Papers (Semantic Web Journal): Special Issue on Knowledge Graphs: Construction, Management and Querying</h1>URL: <a href="http://www.semantic-web-journal.net/blog/call-papers-special-issue-knowledge-graphs-construction-management-and-querying" target="_blank">http://www.semantic-web-<wbr>journal.net/blog/call-papers-<wbr>special-issue-knowledge-<wbr>graphs-construction-<wbr>management-and-querying </a></div><div><br></div><div><p style="margin:0.5em 0px;padding:0px;color:rgb(50,50,50);font-family:"Myriad Pro",Myriad,"Trebuchet MS",Arial,Helvetica,sans-serif;font-size:13px;font-style:normal;font-variant-ligatures:normal;font-variant-caps:normal;font-weight:400;letter-spacing:normal;text-align:start;text-indent:0px;text-transform:none;white-space:normal;word-spacing:0px;background-color:rgb(255,255,255);text-decoration-style:initial;text-decoration-color:initial">A Knowledge Graph (KG) is a graph-theoretic knowledge representation that (at its simplest) models entities and attribute values as nodes, and relationships and attributes as labeled, directed edges. Knowledge Graphs have emerged as a unifying technology in several areas of AI, including Natural Language Processing and Semantic Web, and for this reason, the scope of what constitutes a KG has continued to broaden. In industry, widespread adoption of <a href="http://schema.org" target="_blank">schema.org</a>, as well as the Google Knowledge Graph, is changing the way information is being produced and consumed by both humans and machine agents on the Web. Even before the term ‘Knowledge Graph’ was coined and was in use, the Semantic Web community was a strong advocate of many of the core elements that make KGs so powerful, including graph-theoretic data models (and more generally, semi-structured representations of both data and schema), powerful pattern-matching querying languages, graph data management and the emergence and utilization of large publicly available KGs like DBpedia, GeoNames and Wikidata for such varied tasks as knowledge acquisition, information retrieval and knowledge alignment. With the renaissance of, and deep interest in, such technologies in the broader computer science community, we believe that the time is ripe for the Semantic Web to revisit Knowledge Graphs from the lens of construction, management and querying.</p><p style="margin:0.5em 0px;padding:0px;color:rgb(50,50,50);font-family:"Myriad Pro",Myriad,"Trebuchet MS",Arial,Helvetica,sans-serif;font-size:13px;font-style:normal;font-variant-ligatures:normal;font-variant-caps:normal;font-weight:400;letter-spacing:normal;text-align:start;text-indent:0px;text-transform:none;white-space:normal;word-spacing:0px;background-color:rgb(255,255,255);text-decoration-style:initial;text-decoration-color:initial">We welcome four main types of submissions: (i) full research papers, (ii) reports on tools and systems, (iii) application reports, and (iv) survey articles. The description of the submission types is posted at<span> </span><a href="http://www.semantic-web-journal.net/authors#types" style="margin:0px;padding:0px;text-decoration:none;color:rgb(191,29,32)" target="_blank">http://www.semantic-web-<wbr>journal.net/authors#types</a>. While there is no upper limit, paper length must be justified by content. For guidance, we provide a list of possible topics below. Note that these topics are non-exhaustive and are not meant to be mutually exclusive. We especially welcome interdisciplinary research that spans multiple topics. Our guest editorial board includes members from both academia and industry.</p><p style="margin:0.5em 0px;padding:0px;color:rgb(50,50,50);font-family:"Myriad Pro",Myriad,"Trebuchet MS",Arial,Helvetica,sans-serif;font-size:13px;font-style:normal;font-variant-ligatures:normal;font-variant-caps:normal;font-weight:400;letter-spacing:normal;text-align:start;text-indent:0px;text-transform:none;white-space:normal;word-spacing:0px;background-color:rgb(255,255,255);text-decoration-style:initial;text-decoration-color:initial">Knowledge Graph Construction:</p><ul style="margin:0px 0px 1.5em 2em;padding:0px;list-style-type:disc;color:rgb(50,50,50);font-family:"Myriad Pro",Myriad,"Trebuchet MS",Arial,Helvetica,sans-serif;font-size:13px;font-style:normal;font-variant-ligatures:normal;font-variant-caps:normal;font-weight:400;letter-spacing:normal;text-align:start;text-indent:0px;text-transform:none;white-space:normal;word-spacing:0px;background-color:rgb(255,255,255);text-decoration-style:initial;text-decoration-color:initial"><li style="margin:0px;padding:0px;line-height:19.5px">Novel techniques and algorithms for information extraction, especially algorithms that adapt quickly to novel domains and can be applied to Web data</li><li style="margin:0px;padding:0px;line-height:19.5px">Modeling structured sources in terms of a target KG ontology</li><li style="margin:0px;padding:0px;line-height:19.5px">Instance-based or hybrid ontology mapping between the ontologies of two KGs</li><li style="margin:0px;padding:0px;line-height:19.5px">Techniques for constructing multi-modal Knowledge Graphs from non-textual sources like video, images and other multimedia</li><li style="margin:0px;padding:0px;line-height:19.5px">Crowdsourced techniques for constructing high-quality Knowledge Graphs</li><li style="margin:0px;padding:0px;line-height:19.5px">Interactive techniques such as active learning, question answering and dialogs for rapid, high-quality human-in-the-loop KG construction</li><li style="margin:0px;padding:0px;line-height:19.5px">Entity resolution techniques for Knowledge Graphs</li><li style="margin:0px;padding:0px;line-height:19.5px">Machine Learning (including Probabilistic Logic) techniques for ‘completing’ Knowledge Graphs by reasoning and doing link prediction over information extraction, entity resolution or ontology mapping outputs</li></ul><p style="margin:0.5em 0px;padding:0px;color:rgb(50,50,50);font-family:"Myriad Pro",Myriad,"Trebuchet MS",Arial,Helvetica,sans-serif;font-size:13px;font-style:normal;font-variant-ligatures:normal;font-variant-caps:normal;font-weight:400;letter-spacing:normal;text-align:start;text-indent:0px;text-transform:none;white-space:normal;word-spacing:0px;background-color:rgb(255,255,255);text-decoration-style:initial;text-decoration-color:initial">Knowledge Graph Querying:</p><ul style="margin:0px 0px 1.5em 2em;padding:0px;list-style-type:disc;color:rgb(50,50,50);font-family:"Myriad Pro",Myriad,"Trebuchet MS",Arial,Helvetica,sans-serif;font-size:13px;font-style:normal;font-variant-ligatures:normal;font-variant-caps:normal;font-weight:400;letter-spacing:normal;text-align:start;text-indent:0px;text-transform:none;white-space:normal;word-spacing:0px;background-color:rgb(255,255,255);text-decoration-style:initial;text-decoration-color:initial"><li style="margin:0px;padding:0px;line-height:19.5px">Domain-specific search models over Knowledge Graphs, including for specialized applications like vertical search and enterprise search</li><li style="margin:0px;padding:0px;line-height:19.5px">Information Retrieval models (including learning to rank models) for querying Knowledge Graphs</li><li style="margin:0px;padding:0px;line-height:19.5px">Semantic query reformulation techniques to robustly query noisily constructed, or incomplete, Knowledge Graphs</li><li style="margin:0px;padding:0px;line-height:19.5px">Question Answering over Knowledge Graphs Knowledge Graph Management:</li><li style="margin:0px;padding:0px;line-height:19.5px">Entity alignment and linking between diverse Knowledge Graphs</li><li style="margin:0px;padding:0px;line-height:19.5px">Publishing, consumption, maintenance and evolution</li><li style="margin:0px;padding:0px;line-height:19.5px">Personalised learning based on Knowledge Graphs</li><li style="margin:0px;padding:0px;line-height:19.5px">Managing real time and historical data using Knowledge Graphs</li><li style="margin:0px;padding:0px;line-height:19.5px">Security and privacy issues surrounding Knowledge Graph use and management</li></ul><p style="margin:0.5em 0px;padding:0px;color:rgb(50,50,50);font-family:"Myriad Pro",Myriad,"Trebuchet MS",Arial,Helvetica,sans-serif;font-size:13px;font-style:normal;font-variant-ligatures:normal;font-variant-caps:normal;font-weight:400;letter-spacing:normal;text-align:start;text-indent:0px;text-transform:none;white-space:normal;word-spacing:0px;background-color:rgb(255,255,255);text-decoration-style:initial;text-decoration-color:initial">Applications:</p><ul style="margin:0px 0px 1.5em 2em;padding:0px;list-style-type:disc;color:rgb(50,50,50);font-family:"Myriad Pro",Myriad,"Trebuchet MS",Arial,Helvetica,sans-serif;font-size:13px;font-style:normal;font-variant-ligatures:normal;font-variant-caps:normal;font-weight:400;letter-spacing:normal;text-align:start;text-indent:0px;text-transform:none;white-space:normal;word-spacing:0px;background-color:rgb(255,255,255);text-decoration-style:initial;text-decoration-color:initial"><li style="margin:0px;padding:0px;line-height:19.5px">Applications that showcase the successful adoption of Knowledge Graphs in both research and industrial settings, with clear description of the role, impact and motivations behind using Knowledge Graphs.</li><li style="margin:0px;padding:0px;line-height:19.5px">Development and utilization of Knowledge Graphs in specific industrial domains (e.g., media, government, financials, healthcare, life sciences, smart cities, cultural heritage, etc.) or as a horizontal technology, across application areas (e.g., business intelligence, analytics, search, content / knowledge management, information extraction, data integration, recommendation systems, etc.).</li><li style="margin:0px;padding:0px;line-height:19.5px">Discussion of experiences, scalability and the measurable impact (quantitative and / or qualitative) of the added value created by using Knowledge Graphs in the respective domain. Best practises and concrete lessons learned from these experiences.</li><li style="margin:0px;padding:0px;line-height:19.5px">Potential strategic applications, use cases and areas where further research and advances based on using Knowledge Graphs is required</li></ul><h2 style="margin:0px 0px 0.5em;padding:0px;font-size:18.5705px;color:rgb(50,50,50);font-family:"Myriad Pro",Myriad,"Trebuchet MS",Arial,Helvetica,sans-serif;font-style:normal;font-variant-ligatures:normal;font-variant-caps:normal;letter-spacing:normal;text-align:start;text-indent:0px;text-transform:none;white-space:normal;word-spacing:0px;background-color:rgb(255,255,255);text-decoration-style:initial;text-decoration-color:initial">Deadline</h2><ul style="margin:0px 0px 1.5em 2em;padding:0px;list-style-type:disc;color:rgb(50,50,50);font-family:"Myriad Pro",Myriad,"Trebuchet MS",Arial,Helvetica,sans-serif;font-size:13px;font-style:normal;font-variant-ligatures:normal;font-variant-caps:normal;font-weight:400;letter-spacing:normal;text-align:start;text-indent:0px;text-transform:none;white-space:normal;word-spacing:0px;background-color:rgb(255,255,255);text-decoration-style:initial;text-decoration-color:initial"><li style="margin:0px;padding:0px;line-height:19.5px">Submission deadline: 15 June 2018. Papers submitted before the deadline will be reviewed upon receipt.</li></ul><h2 style="margin:0px 0px 0.5em;padding:0px;font-size:18.5705px;color:rgb(50,50,50);font-family:"Myriad Pro",Myriad,"Trebuchet MS",Arial,Helvetica,sans-serif;font-style:normal;font-variant-ligatures:normal;font-variant-caps:normal;letter-spacing:normal;text-align:start;text-indent:0px;text-transform:none;white-space:normal;word-spacing:0px;background-color:rgb(255,255,255);text-decoration-style:initial;text-decoration-color:initial">Submission Instructions</h2><p style="margin:0.5em 0px;padding:0px;color:rgb(50,50,50);font-family:"Myriad Pro",Myriad,"Trebuchet MS",Arial,Helvetica,sans-serif;font-size:13px;font-style:normal;font-variant-ligatures:normal;font-variant-caps:normal;font-weight:400;letter-spacing:normal;text-align:start;text-indent:0px;text-transform:none;white-space:normal;word-spacing:0px;background-color:rgb(255,255,255);text-decoration-style:initial;text-decoration-color:initial">Submissions shall be made through the Semantic Web journal website at<span> </span><a href="http://www.semantic-web-journal.net/" style="margin:0px;padding:0px;text-decoration:none;color:rgb(191,29,32)" target="_blank">http://www.semantic-web-<wbr>journal.net</a>. Prospective authors must take notice of the submission guidelines posted at<span> </span><a href="http://www.semantic-web-journal.net/authors" style="margin:0px;padding:0px;text-decoration:none;color:rgb(191,29,32)" target="_blank">http://www.semantic-web-<wbr>journal.net/authors</a>.</p><p style="margin:0.5em 0px;padding:0px;color:rgb(50,50,50);font-family:"Myriad Pro",Myriad,"Trebuchet MS",Arial,Helvetica,sans-serif;font-size:13px;font-style:normal;font-variant-ligatures:normal;font-variant-caps:normal;font-weight:400;letter-spacing:normal;text-align:start;text-indent:0px;text-transform:none;white-space:normal;word-spacing:0px;background-color:rgb(255,255,255);text-decoration-style:initial;text-decoration-color:initial">Note that you need to request an account on the website for submitting a paper. When submitting, please indicate in the cover letter that it is for the Special Issue on Knowledge Graphs and the chosen submission type. All manuscripts will be reviewed based on the SWJ open and transparent review policy and will be made available online during the review process.</p><h2 style="margin:0px 0px 0.5em;padding:0px;font-size:18.5705px;color:rgb(50,50,50);font-family:"Myriad Pro",Myriad,"Trebuchet MS",Arial,Helvetica,sans-serif;font-style:normal;font-variant-ligatures:normal;font-variant-caps:normal;letter-spacing:normal;text-align:start;text-indent:0px;text-transform:none;white-space:normal;word-spacing:0px;background-color:rgb(255,255,255);text-decoration-style:initial;text-decoration-color:initial">Guest editors</h2><p style="margin:0.5em 0px;padding:0px;color:rgb(50,50,50);font-family:"Myriad Pro",Myriad,"Trebuchet MS",Arial,Helvetica,sans-serif;font-size:13px;font-style:normal;font-variant-ligatures:normal;font-variant-caps:normal;font-weight:400;letter-spacing:normal;text-align:start;text-indent:0px;text-transform:none;white-space:normal;word-spacing:0px;background-color:rgb(255,255,255);text-decoration-style:initial;text-decoration-color:initial">The guest editors can be reached at<span> </span><a href="mailto:swj-knowledge-graphs@googlegroups.com" style="margin:0px;padding:0px;text-decoration:none;color:rgb(191,29,32)" target="_blank">swj-knowledge-graphs@<wbr>googlegroups.com</a>.</p><p style="margin:0.5em 0px;padding:0px;color:rgb(50,50,50);font-family:"Myriad Pro",Myriad,"Trebuchet MS",Arial,Helvetica,sans-serif;font-size:13px;font-style:normal;font-variant-ligatures:normal;font-variant-caps:normal;font-weight:400;letter-spacing:normal;text-align:start;text-indent:0px;text-transform:none;white-space:normal;word-spacing:0px;background-color:rgb(255,255,255);text-decoration-style:initial;text-decoration-color:initial"><a href="http://usc-isi-i2.github.io/kejriwal/" style="margin:0px;padding:0px;text-decoration:none;color:rgb(191,29,32)" target="_blank">Mayank Kejriwal</a><span> </span>(USC Information Sciences Institute; Los Angeles, CA, United States)<br><a href="https://researcher.watson.ibm.com/researcher/view.php?person=ie-VANLOPEZ" style="margin:0px;padding:0px;text-decoration:none;color:rgb(191,29,32)" target="_blank">Vanessa Lopez</a><span> </span>(IBM Research; Dublin, Ireland)<br><a href="http://juansequeda.com/" style="margin:0px;padding:0px;text-decoration:none;color:rgb(191,29,32)" target="_blank">Juan F. Sequeda</a><span> </span>(Capsenta; Austin, TX, United States)</p><h2 style="margin:0px 0px 0.5em;padding:0px;font-size:18.5705px;color:rgb(50,50,50);font-family:"Myriad Pro",Myriad,"Trebuchet MS",Arial,Helvetica,sans-serif;font-style:normal;font-variant-ligatures:normal;font-variant-caps:normal;letter-spacing:normal;text-align:start;text-indent:0px;text-transform:none;white-space:normal;word-spacing:0px;background-color:rgb(255,255,255);text-decoration-style:initial;text-decoration-color:initial">Guest editorial board</h2><p style="margin:0.5em 0px;padding:0px;color:rgb(50,50,50);font-family:"Myriad Pro",Myriad,"Trebuchet MS",Arial,Helvetica,sans-serif;font-size:13px;font-style:normal;font-variant-ligatures:normal;font-variant-caps:normal;font-weight:400;letter-spacing:normal;text-align:start;text-indent:0px;text-transform:none;white-space:normal;word-spacing:0px;background-color:rgb(255,255,255);text-decoration-style:initial;text-decoration-color:initial">Elena Cabrio, University of Nice Sophia Antipolis, France<br>Mari Carmen Suarez Figueroa, Universidad Politécnica de Madrid, Spain<br>Stamatia Dasiopoulou, Pompeu Fabra University, Spain<br>Dennis Diefenbach, St Etienne university, France<br>Derek Doran, Wright State University, United States<br>Mauro Dragoni, Fondazione Bruno Kessler, Italy<br>Sumit Bhatia, IBM Research, India<br>Jorge Gracia Del Río, Universidad Politécnica de Madrid, Spain<br>Dagmar Gromann, Technical University Dresden, Germany<br>Aidan Hogan, Universidad de Chile, Chile<br>Freddy Lecue, Accenture Technology Labs, Ireland<br>Antonio Lieto, University of Turin, Italy<br>Alessandra Mileo, INSIGHT Center for Data Analytics , Ireland<br>Andriy Nikolov, metaphacts GmbH, Germany<br>Sergio Oramas, Pompeu Fabra University, Spain<br>Petya Osenova, Bulgarian Academy of Sciences, Bulgaria<br>Raul Palma, Poznan Supercomputing and Networking Center, Poland<br>Simone Paolo Ponzetto, University of Mannheim, Germany<br>Hector Perez-Urbina, Google, United States<br>Silvio Peroni, University of Bologna, Italy<br>Mariano Rodriguez Muro, IBM Research, United States<br>Enrico Santus, Singapore University of Technology and Design, Singapore<br>Kiril Simov, Bulgarian Academy of Sciences, Bulgaria<br>Michael Spranger, Sony Computer Science Laboratories, Japan<br>Marta Sabou, Modul University, Austria<br>Piek Vossen, VU University Amsterdam, The Netherlands<br>Arkaitz Zubiaga, University of Warwick, United Kingdom<br>Balaji Ganesa, IBM Research, India</p><br></div></div>