CfP: International Workshop on Semantic Big Data @ ACM SIGMOD 2016
** CALL FOR PAPERS International Workshop on Semantic Big Data (SBD 2016) In conjunction with ACM SIGMOD 2016 1 July 2016, San Francisco, USA Submission: 15 February 2016 Web: http://www.ifis.uni-luebeck.de/~groppe/sbd ** ** Aims of the Workshop ** The current World-Wide Web enables an easy, instant access to a vast amount of online information. However, the content in the Web is typically for human consumption, and is not tailored for machine processing. The Semantic Web is hence intended to establish a machine-understandable Web, and is currently also used in many other domains and not only in the Web. The World Wide Web Consortium (W3C) has developed a number of standards around this vision. Among them is the Resource Description Framework (RDF), which is used as the data model of the Semantic Web. The W3C has also defined SPARQL as RDF query language, RIF as rule language, and the ontology languages RDFS and OWL to describe schemas of RDF. The usage of common ontologies increases interoperability between heterogeneous data sets, and the proprietary ontologies with the additional abstraction layer facilitate the integration of these data sets. Therefore, we can argue that the Semantic Web is ideally designed to work in heterogeneous Big Data environments. We define Semantic Big Data as the intersection of Semantic Web data and Big Data. There are masses of Semantic Web data freely available to the public - thanks to the efforts of the linked data initiative. According to http://stats.lod2.eu/ the current freely available Semantic Web data is approximately 90 billion triples in over 3,300 datasets, many of which are accessible via SPARQL query servers called SPARQL endpoints. Everyone can submit SPARQL queries to SPARQL endpoints via a standardized protocol, where the queries are processed on the datasets of the SPARQL endpoints and the query results are sent back in a standardized format. Hence not only Semantic Big Data is freely available, but also distributed execution environments for Semantic Big Data are freely accessible. This makes the Semantic Web an ideal playground for Big Data research. The goal of this workshop is to bring together academic researchers and industry practitioners to address the challenges and report and exchange the research findings in Semantic Big Data, including new approaches, techniques and applications, make substantial theoretical and empirical contributions to, and significantly advance the state of the art of Semantic Big Data. ** Types of Papers ** The workshop solicits papers of different type: - Research Papers propose new approaches, theories or techniques related to Semantic Big Data including new data structures, algorithms and whole systems. They should make substantial theoretical and empirical contributions to the research field. - Experiments and Analysis Papers focus on the experimental evaluation of existing approaches including data structures and algorithms for Semantic Big data and bring new insights through the analysis of these experiments. Results of Experiments and Analysis Papers can be e.g. showing benefits of well-known approaches in new settings and environments, open new research problems by demonstrating unexpected behavior or phenomena, or compare a set of traditional approaches in an experimental survey. - Application Papers report practical experiences on applications of Semantic Big Data. Application Papers might describe how to apply Semantic Web technologies to specific application domains with big data demands like social networks, web search, e-business, collaborative environments, e-learning, medical informatics, bioinformatics and geographic information system. Application Papers might describe applications using linked data in a new way. - Vision Papers identify emerging new or future research issues and directions, and describe new research visions having demands for Semantic Big Data. The new visions will potentially have great impacts on society. ** Topics of Interest ** We welcome papers on the following topics: - Semantic Data Management, Query Processing and Optimization in - Big Data - Cloud Computing - Internet of Things - Graph Databases - Federations - Spatial and Spatio-Temporal Data - Evaluation strategies for Semantic Big Data of Rule-based Languages like RIF and SWRL - Ontology-based Approaches for Modeling, Mapping, Evolution and Real-world ontologies in the context of Semantic Big Data - Reasoning Approaches (Real-World Applications, Efficient Algorithms) especially designed for Semantic Big Data environments - Linked Data - Integration of Heterogeneous Linked Data - Real-World Applications - Statistics and Visualizations - Quality - Ranking Techniques - Provenance - Mining and
Senior Researcher / PostDoc / PhD Positions at the University of Bonn
There are several positions available as 1. Akademischer Rat (comparable to Assistant Professor), 2. PostDoc and 3. PhD Student at the University of Bonn. Please refer to the details for the three types of positions below. === 1. Akademischer Rat Position at the University of Bonn === We are looking for a senior researcher (Akademischer Rat on payment scale 100% A13 [1] comparable to Assistant Professor) for 3 years with a possible extension to 6 years. Requirements: * A completed PhD and Master degree in a relevant field (Computer Science or related). Research and Teaching Areas: The candidate should have experience in *one of* the following areas (it is not required to cover more than one area): * Big Data, Machine Learning, Data Mining * Semantic Technologies and Linked Data * Geospatial data modelling and analysis * Natural language processing, in particular Question Answering Depending on previous qualification, the candidate will be responsible for courses on Machine Learning, Data Science or Data Engineerung. We expect: * Keen interest in top level conference and journal publications * Responsibility for courses at the Computer Science Institute for 3 hours per week (4 SWS) * Experience in acquiring and running research and industry projects * Co-supervision of PhD, Master- and Bachelor thesis * Experience in software development and project management * Interest in transferring research results into practise * Fluent command of German and English language We offer: * You will work at one of the leading [2] German Universities and have the opportunity to build your own research team. The goal is to perform internationally leading research which can be applied in high impact use cases. * The candidate will be supported with personal resources to the extent possible as well as an integration into an international collaboration network. * You will enjoy a close collaboration with Fraunhofer IAIS [3] as a leading research institute for large scale machine learning and data mining. * The payment will be 100% A13 for 3 years with a possible extension for further 3 years. * You will get financial support to attend related conferences. To apply, please send a mail to Martina Doelp (mart...@iai.uni-bonn.de) including a CV, two recommendation letters, a PhD certificate and a one page motivation letter including a short overview of previous research and acquisition activities. Applications are possible until all positions have been filled. Please do not send mails larger than 10MB. Please direct administrative questions to Martina Doelp (mart...@iai.uni-bonn.de) and all other questions to Prof. Jens Lehmann (jens.lehm...@cs.uni-bonn.de). The University of Bonn is an equal opportunities employer. [1] example calculation: http://oeffentlicher-dienst.info/c/t/rechner/beamte/nw?id=beamte-nrw=A_13=0=3=100==2015b=1=0=2 [2] https://en.wikipedia.org/wiki/University_of_Bonn#Ranking [3] http://www.iais.fraunhofer.de === 2. PostDoc Positions at the University of Bonn === We are looking for Postdoctoral Researchers (German: Wissenschaftliche(r) Mitarbeiter(in)) at the Computer Science Institute at the University of Bonn. Requirements: * A completed PhD and Master degree in a relevant field (Computer Science or related). * Proficiency in spoken and written English. Proficiency in German is desired. * Experience in *one of* (not necessarily more) the following areas: * Big Data, Machine Learning, Data Mining * Semantic Technologies and Linked Data * Geospatial data modelling and analysis * Natural language processing, in particular Question Answering We expect: * Keen interest in top level conference and journal publications * Co-supervision of PhD, Master- and Bachelor thesis * Interest in acquiring and running research and industry projects * Experience in software development and project management * Interest in transferring research results into practise and commercialising them We offer: * You will work at one of the leading [1] German Universities and have the opportunity to build your own research team. The goal is to perform internationally leading research which can be applied in high impact use cases. * You will enjoy a close collaboration with Fraunhofer IAIS [2] as a leading research institute for large scale machine learning and data mining. * The payment will be between 50% and 100% TV-L 13 and the contract duration between 2 and 4 years depending on previous experience and involvement in projects. * You will get financial support to attend related conferences and the possibility to obtain a discounted public transport ticket. To apply, please
Join us for the next Protege Short Course at Stanford University, March 21 - 23, 2016!
*** Apologies for cross-posting! Dear all, We are very happy to announce the next Protege Short Course to be held at Stanford University, California between March 21 - 23, 2016. The Protege Short Course offers a 3-day intensive training in use of the Protege toolset, ontology development, and OWL. We cover best practices in ontology building and the latest Semantic Web technologies, including OWL 2, RDF, and SPARQL. We also cover topics such as real-world applications with ontologies, and data access and import from different data sources. The course is hands-on and is taught by the members of the Protege team. Read more about it at: http://protege.stanford.edu/shortcourse/201603/ If you have any questions about the Protege Short Course, please email: protege-shortcou...@lists.stanford.edu Please feel free to forward this announcement to anyone who might be interested in the course. Thank you! We look forward to seeing you next Spring! Best regards, The Protege Team
CfP: WWW2016 workshop on Linked Data on the Web (LDOW2016)
Hi all, In case you don't know yet what do in your X-Mas holidays, why not preparing a submission for the WWW2016 workshop on Linked Data on the Web (LDOW2016) in Montreal, Canada ;-) The paper submission deadline for the workshop is 24 January, 2016. Please find the call for papers below. BTW: LDOW now also accepts HTML5+RDFa submissions according to the Linked Research principles: https://github.com/csarven/linked-research with embedded semantic and interactive content. Looking forward seeing you at LDOW2016 in Montreal! Cheers, Sören Chris, Tim, and Tom Call for Papers: 9th Workshop on Linked Data on the Web (LDOW2016) Co-located with 25th International World Wide Web Conference April 11 to 15, 2016 in Montreal, Canada http://events.linkeddata.org/ldow2016/ The Web is developing from a medium for publishing textual documents into a medium for sharing structured data. This trend is fueled on the one hand by the adoption of the Linked Data principles by a growing number of data providers. On the other hand, large numbers of websites have started to semantically mark up the content of their HTML pages and thus also contribute to the wealth of structured data available on the Web. The 9th Workshop on Linked Data on the Web (LDOW2016) aims to stimulate discussion and further research into the challenges of publishing, consuming, and integrating structured data from the Web as well as mining knowledge from the global Web of Data. The special focus of this years LDOW workshop will be Web Data Quality Assessment and Web Data Cleansing. *Important Dates* * Submission deadline: 24 January, 2016 (23:59 Pacific Time) * Notification of acceptance: 10 February, 2016 * Camera-ready versions of accepted papers: 1 March, 2016 * Workshop date: 11-13 April, 2016 *Topics of Interest* Topics of interest for the workshop include, but are not limited to, the following: Web Data Quality Assessment * methods for evaluating the quality and trustworthiness of web data * tracking the provenance of web data * profiling and change tracking of web data sources * cost and benefits of web data quality assessment * web data quality assessment benchmarks Web Data Cleansing * methods for cleansing web data * data fusion and truth discovery * conflict resolution using semantic knowledge * human-in-the-loop and crowdsourcing for data cleansing * cost and benefits of web data cleansing * web data quality cleansing benchmarks Integrating Web Data from Large Numbers of Data Sources * linking algorithms and heuristics, identity resolution * schema matching and clustering * evaluation of linking and schema matching methods Mining the Web of Data * large-scale derivation of implicit knowledge from the Web of Data * using the Web of Data as background knowledge in data mining * techniques and methodologies for Linked Data mining and analytics Linked Data Applications * application showcases including Web data browsers and search engines * marketplaces, aggregators and indexes for Web Data * security, access control, and licensing issues of Linked Data * role of Linked Data within enterprise applications (e.g. ERP, SCM,CRM) * Linked Data applications for life-sciences, digital humanities, social sciences etc. *Submissions* We seek two kinds of submissions: 1. Full scientific papers: up to 10 pages in ACM format 2. Short scientific and position papers: up to 5 pages in ACM format Submissions must be formatted using the ACM SIG template available at http://www.acm.org/sigs/publications/proceedings-templates or in HTML5 e.g. according to the Linked Research (https://github.com/csarven/linked-research) principles. For authoring submission according to the Linked Research principles authors can use dokieli (https://github.com/linkeddata/dokieli) - a decentralized authoring and annotation tooling. HTML5 papers can be submitted by either providing an URL to their paper (in HTML+RDFa, CSS, JavaScript etc.) with supporting files, or an archived zip file including all the material. Accepted papers will be presented at the workshop and included in the CEUR workshop proceedings. At least one author of each paper has to register for the workshop and to present the paper. *Organizing Committee* Christian Bizer, University of Mannheim, Germany Tom Heath, Open Data Institute, UK Sören Auer, University of Bonn and Fraunhofer IAIS, Germany Tim Berners-Lee, W3C/MIT, USA *Contact Information* For further information about the workshop, please contact the workshops chairs at: ldow2...@events.linkeddata.org -- Enterprise Information Systems, Computer Science, University of Bonn http://eis.iai.uni-bonn.de/SoerenAuer Fraunhofer-Institute Intelligent Analysis & Information Systems (IAIS) Organized Knowledge -- http://www.iais.fraunhofer.de/Auer.html Skype: soerenauer, Mobile +4915784988949 http://linkedin.com/in/soerenauer https://twitter.com/SoerenAuer
