Knowledge Graphs: New Directions for Knowledge Representation on the Semantic Web (Dagstuhl Seminar 18371)

The increasingly pervasive nature of the Web, expanding to devices and things in everyday life, along with new trends in Artificial Intelligence call for new paradigms and a new look on Knowledge Representation and Processing at scale for the Semantic Web. The emerging, but still to be concretely shaped concept of "Knowledge Graphs" provides an excellent unifying metaphor for this current status of Semantic Web research. More than two decades of Semantic Web research provides a solid basis and a promising technology and standards stack to interlink data, ontologies and knowledge on the Web. However, neither are applications for Knowledge Graphs as such limited to Linked Open Data, nor are instantiations of Knowledge Graphs in enterprises – while often inspired by – limited to the core Semantic Web stack. This report documents the program and the outcomes of Dagstuhl Seminar 18371 "Knowledge Graphs: New Directions for Knowledge Representation on the Semantic Web", where a group of experts from academia and industry discussed fundamental questions around these topics for a week in early September 2018, including the following: what are knowledge graphs? Which applications do we see to emerge? Which open research questions still need be addressed and which technology gaps still need to be closed?

[1]  Michel C. A. Klein,et al.  Ontology Evolution: Not the Same as Schema Evolution , 2004, Knowledge and Information Systems.

[2]  Elena Cabrio,et al.  Question Answering over Linked Data (QALD-5) , 2014, CLEF.

[3]  Diego Reforgiato Recupero,et al.  Semantic Web Machine Reading with FRED , 2017, Semantic Web.

[4]  Gerard de Melo.  Inducing Conceptual Embedding Spaces from Wikipedia , 2017, WWW.

[5]  Heiko Paulheim,et al.  Evaluating Entity Linking: An Analysis of Current Benchmark Datasets and a Roadmap for Doing a Better Job , 2016, LREC.

[6]  Patrick Valduriez.  Principles of Distributed Data Management in 2020? , 2011, DEXA.

[7]  T. Landauer,et al.  A Solution to Plato's Problem: The Latent Semantic Analysis Theory of Acquisition, Induction, and Representation of Knowledge. , 1997 .

[8]  Kalina Bontcheva,et al.  Natural Language Processing for the Semantic Web , 2016, Synthesis Lectures on the Semantic Web: Theory and Technology.

[9]  Gerard de Melo,et al.  WebBrain: Joint Neural Learning of Large-Scale Commonsense Knowledge , 2016, International Semantic Web Conference.

[10]  Ian A. Mason,et al.  Metamathematics of Contexts , 1995, Fundam. Informaticae.

[11]  Xinlei Chen,et al.  Never-Ending Learning , 2012, ECAI.

[12]  Gerhard Weikum,et al.  YAGO: A Large Ontology from Wikipedia and WordNet , 2008, J. Web Semant..

[13]  Heiner Stuckenschmidt,et al.  Results of the Ontology Alignment Evaluation Initiative 2007 , 2006, OM.

[14]  Fabian M. Suchanek,et al.  Fast rule mining in ontological knowledge bases with AMIE+\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$+$$\end{docu , 2015, The VLDB Journal.

[15]  Jürgen Umbrich,et al.  Evaluating Query and Storage Strategies for RDF Archives , 2016, SEMANTICS.

[16]  Achim Rettinger,et al.  Linked data quality of DBpedia, Freebase, OpenCyc, Wikidata, and YAGO , 2017, Semantic Web.

[17]  Jürgen Umbrich,et al.  The ACE theorem for querying the web of data , 2013, WWW '13 Companion.

[18]  E. Mannens,et al.  XML to RDF Conversion: A Generic Approach , 2008, 2008 International Conference on Automated Solutions for Cross Media Content and Multi-Channel Distribution.

[19]  Patrick Valduriez,et al.  Distributed and parallel database systems , 1996, CSUR.

[20]  Samantha Bail,et al.  OWL Reasoner Evaluation (ORE) Workshop 2013 Results: Short Report , 2013, ORE.

[21]  Piero A. Bonatti,et al.  Optimized Construction of Secure Knowledge-Base Views , 2015, Description Logics.

[22]  Fausto Giunchiglia,et al.  Local Models Semantics, or Contextual Reasoning = Locality + Compatibility , 1998, KR.

[23]  John F. Sowa,et al.  Principles of semantic networks , 1991 .

[24]  Rolf Nossum.  A decidable multi-modal logic of context , 2003, J. Appl. Log..

[25]  Tim Kraska,et al.  CrowdQ: Crowdsourced Query Understanding , 2013, CIDR.

[26]  Martin Gaedke,et al.  Silk - A Link Discovery Framework for the Web of Data , 2009, LDOW.

[27]  R. Pick.  Shepherd Or Servant: Centralization And Decentralization In Information Technology Governance , 2015 .

[28]  R. Guha.  Contexts: a formalization and some applications , 1992 .

[29]  Markus Krötzsch,et al.  Wikidata , 2014, Commun. ACM.

[30]  Frank van Harmelen,et al.  Detecting Erroneous Identity Links on the Web Using Network Metrics , 2018, SEMWEB.

[31]  Aart J. C. Bik,et al.  Pregel: a system for large-scale graph processing , 2010, SIGMOD Conference.

[32]  Siani Pearson,et al.  Towards accountable management of identity and privacy: sticky policies and enforceable tracing services , 2003, 14th International Workshop on Database and Expert Systems Applications, 2003. Proceedings..

[33]  Maria Simi,et al.  A Formalization of Viewpoints , 1995, Fundam. Informaticae.

[34]  Georg Struth,et al.  Relation Algebra , 2014, Arch. Formal Proofs.

[35]  Piero A. Bonatti,et al.  A Confidentiality Model for Ontologies , 2013, International Semantic Web Conference.

[36]  Wolfram Wöß,et al.  Towards a Definition of Knowledge Graphs , 2016, SEMANTiCS.

[37]  John McCarthy,et al.  Notes on Formalizing Context , 1993, IJCAI.

[38]  Michael Waidner,et al.  Platform for Enterprise Privacy Practices: Privacy-Enabled Management of Customer Data , 2002, Privacy Enhancing Technologies.

[39]  Ganggao Zhu,et al.  Computing Semantic Similarity of Concepts in Knowledge Graphs , 2017, IEEE Transactions on Knowledge and Data Engineering.

[40]  Susan T. Dumais,et al.  How come you know so much? From practical problem to theory , 1996 .

[41]  Stefan Decker,et al.  Mapping between RDF and XML with XSPARQL , 2012, Journal on Data Semantics.

[42]  Robert Dale,et al.  Building applied natural language generation systems , 1997, Natural Language Engineering.

[43]  Verena Rieser,et al.  The E2E Dataset: New Challenges For End-to-End Generation , 2017, SIGDIAL Conference.

[44]  Kostas Stefanidis,et al.  Versioning for Linked Data: Archiving Systems and Benchmarks , 2016, BLINK@ISWC.

[45]  Asunción Gómez-Pérez,et al.  OOPS!: A Pitfall-Based System for Ontology Diagnosis , 2018 .

[46]  Thomas Pellissier Tanon,et al.  From Freebase to Wikidata: The Great Migration , 2016, WWW.

[47]  Gerard de Melo.  Lexvo.org: Language-related information for the Linguistic Linked Data cloud , 2015, Semantic Web.

[48]  Jens Lehmann,et al.  Survey on challenges of Question Answering in the Semantic Web , 2017, Semantic Web.

[49]  Frank van Harmelen,et al.  Are Names Meaningful? Quantifying Social Meaning on the Semantic Web , 2016, SEMWEB.

[50]  Reynold Xin,et al.  GraphX: a resilient distributed graph system on Spark , 2013, GRADES.

[51]  Robert Isele,et al.  LDIF - Linked Data Integration Framework , 2011, COLD.

[52]  Gerard de Melo,et al.  FrameBase: Enabling integration of heterogeneous knowledge , 2017, Semantic Web.

[53]  Simone Paolo Ponzetto,et al.  BabelNet: The automatic construction, evaluation and application of a wide-coverage multilingual semantic network , 2012, Artif. Intell..

[54]  Tim Berners-Lee,et al.  A Demonstration of the Solid Platform for Social Web Applications , 2016, WWW.

[55]  Serena Villata,et al.  LIVE: a Tool for Checking Licenses Compatibility between Vocabularies and Data , 2014, International Semantic Web Conference.

[56]  Serena Villata,et al.  Heuristics for Licenses Composition , 2013, JURIX.

[57]  Xabier Artola,et al.  Big data for Natural Language Processing: A streaming approach , 2015, Knowl. Based Syst..

[58]  Jeff Heflin,et al.  LUBM: A benchmark for OWL knowledge base systems , 2005, J. Web Semant..

[59]  Frank van Harmelen,et al.  Is my:sameAs the same as your:sameAs?: Lenticular Lenses for Context-Specific Identity , 2017, K-CAP.

[60]  Freddy Priyatna,et al.  Formalisation and experiences of R2RML-based SPARQL to SQL query translation using morph , 2014, WWW.

[61]  E. Prud hommeaux,et al.  SPARQL query language for RDF , 2011 .

[62]  Jens Lehmann,et al.  Quality assessment for Linked Data: A Survey , 2015, Semantic Web.

[63]  Felix Naumann,et al.  Profiling linked open data with ProLOD , 2010, 2010 IEEE 26th International Conference on Data Engineering Workshops (ICDEW 2010).

[64]  Frank Schilder,et al.  The E2E NLG Challenge: A Tale of Two Systems , 2018, INLG.

[65]  Wei Hu,et al.  Bootstrapping Entity Alignment with Knowledge Graph Embedding , 2018, IJCAI.

[66]  Jeffrey Dean,et al.  Efficient Estimation of Word Representations in Vector Space , 2013, ICLR.

[67]  Helen Nissenbaum,et al.  A Critical Look at Decentralized Personal Data Architectures , 2012, ArXiv.

[68]  Stefan Decker,et al.  Access control and the Resource Description Framework: A survey , 2016, Semantic Web.

[69]  Martin Hepp,et al.  Games with a Purpose for the Semantic Web , 2008, IEEE Intelligent Systems.

[70]  Maribel Acosta,et al.  Crowdsourcing Linked Data Quality Assessment , 2013, SEMWEB.

[71]  Antoine Zimmermann,et al.  Contextualizing DL Axioms: Formalization, a New Approach, and Its Properties , 2017, WSP/WOMoCoE@ISWC.

[72]  Pascal Hitzler,et al.  OWLAx: A Protege Plugin to Support Ontology Axiomatization through Diagramming , 2016, International Semantic Web Conference.

[73]  P. Geurts,et al.  Forces and functions in scientific communication: an analysis of their interplay , 1997 .

[74]  Rafael Peñaloza,et al.  Correcting Access Restrictions to a Consequence More Flexibly , 2011, Description Logics.

[75]  Sören Auer,et al.  LIMES - A Time-Efficient Approach for Large-Scale Link Discovery on the Web of Data , 2011, IJCAI.

[76]  Serena Villata,et al.  Licenses Compatibility and Composition in the Web of Data , 2012, COLD.

[77]  Carlos Buil Aranda.  Federated query processing for the semantic web , 2014, Studies on the Semantic Web.

[78]  Andreas Dengel,et al.  BetterRelations: Using a Game to Rate Linked Data Triples , 2011, KI.

[79]  Mayank Kejriwal.  What Is a Knowledge Graph , 2019 .

[80]  Juan Sequeda,et al.  G-CORE: A Core for Future Graph Query Languages , 2017, SIGMOD Conference.

[81]  Ramanathan V. Guha,et al.  Contexts for the Semantic Web , 2004, SEMWEB.

[82]  Heiko Paulheim,et al.  One Knowledge Graph to Rule Them All? Analyzing the Differences Between DBpedia, YAGO, Wikidata & co , 2017, KI.

[83]  Jürgen Umbrich,et al.  Eight Fallacies when querying the Web of Data , 2013, 2013 IEEE 29th International Conference on Data Engineering Workshops (ICDEW).

[84]  Harmen van den Berg,et al.  First-Order Logic in Knowledge Graphs , 1993, ICML 1994.

[85]  Axel-Cyrille Ngonga Ngomo,et al.  Machine Translation Using Semantic Web Technologies: A Survey , 2017, J. Web Semant..

[86]  John Leslie King,et al.  Centralized versus decentralized computing: organizational considerations and management options , 1983, CSUR.

[87]  Dean Allemang.  Linked Data: Storing, Querying, and Reasoning. Sakr, Sherif, Wylot, Marcin, Mutharaju, Raghava, Le Phuoc, Danh, and Fundulaki, Irini. Cham, Switzerland: Springer International Publishing, 2018. 233 pp. $129.00 (hardcover). (ISBN 9783319735146) , 2019, J. Assoc. Inf. Sci. Technol..

[88]  Huiying Li,et al.  Data Profiling for Semantic Web Data , 2012, WISM.

[89]  Heiko Paulheim,et al.  Mining the Web of Linked Data with RapidMiner , 2015, J. Web Semant..

[90]  Wei Zhang,et al.  Knowledge vault: a web-scale approach to probabilistic knowledge fusion , 2014, KDD.

[91]  Rafael Peñaloza,et al.  A Generic Approach for Large-Scale Ontological Reasoning in the Presence of Access Restrictions to the Ontology's Axioms , 2009, International Semantic Web Conference.

[92]  Roberto Navigli,et al.  Natural Language Understanding: Instructions for (Present and Future) Use , 2018, IJCAI.

[93]  Felix Naumann,et al.  Data profiling revisited , 2014, SGMD.

[94]  Andrew Chou,et al.  Semantic Parsing on Freebase from Question-Answer Pairs , 2013, EMNLP.

[95]  Yufei Tao,et al.  Transparent anonymization: Thwarting adversaries who know the algorithm , 2010, TODS.

[96]  Stefan Schlobach,et al.  LOD Laundromat: A Uniform Way of Publishing Other People's Dirty Data , 2014, SEMWEB.

[97]  Olaf Hartig,et al.  Reconciliation of RDF* and Property Graphs , 2014, ArXiv.

[98]  Praveen Paritosh,et al.  Freebase: a collaboratively created graph database for structuring human knowledge , 2008, SIGMOD Conference.

[99]  Heiko Paulheim,et al.  Improving the Quality of Linked Data Using Statistical Distributions , 2014, Int. J. Semantic Web Inf. Syst..

[100]  Maria-Esther Vidal,et al.  BOUNCER: Privacy-Aware Query Processing over Federations of RDF Datasets , 2018, DEXA.

[101]  Nikolas Mitrou,et al.  Bringing relational databases into the Semantic Web: A survey , 2012, Semantic Web.

[102]  Chen Chen,et al.  BigGorilla: An Open-Source Ecosystem for Data Preparation and Integration , 2018, IEEE Data Eng. Bull..

[103]  Mirella Lapata,et al.  An Experimental Study of Graph Connectivity for Unsupervised Word Sense Disambiguation , 2010, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[104]  Joachim Biskup,et al.  Inference-proof Data Filtering for a Probabilistic Setting , 2017, PrivOn@ISWC.

[105]  Ajay Chakravarthy,et al.  Mining the Semantic Web , 2005 .

[106]  Yolanda Gil,et al.  A survey of trust in computer science and the Semantic Web , 2007, J. Web Semant..

[107]  Oren Etzioni,et al.  Machine Reading , 2006, AAAI.

[108]  Heiner Stuckenschmidt,et al.  Query-Based Access Control for Ontologies , 2010, RR.

[109]  Chris Clifton,et al.  On syntactic anonymity and differential privacy , 2013, 2013 IEEE 29th International Conference on Data Engineering Workshops (ICDEW).

[110]  Prateek Mittal,et al.  Dependence Makes You Vulnberable: Differential Privacy Under Dependent Tuples , 2016, NDSS.

[111]  Iryna Gurevych,et al.  E2E NLG Challenge: Neural Models vs. Templates , 2018, INLG.

[112]  Markus Krötzsch,et al.  Attributed Description Logics: Reasoning on Knowledge Graphs , 2018, IJCAI.

[113]  Aldo Gangemi,et al.  Serving DBpedia with DOLCE - More than Just Adding a Cherry on Top , 2015, International Semantic Web Conference.

[114]  Pierre Maret,et al.  NdFluents: An Ontology for Annotated Statements with Inference Preservation , 2017, ESWC.

[115]  V. S. Subrahmanian,et al.  Theory of Generalized Annotated Logic Programming and its Applications , 1992, J. Log. Program..

[116]  Jeffrey Pennington,et al.  GloVe: Global Vectors for Word Representation , 2014, EMNLP.

[117]  Jens Lehmann,et al.  TripleCheckMate: A Tool for Crowdsourcing the Quality Assessment of Linked Data , 2013, KESW.

[118]  E. Marchi,et al.  On the structure of the teaching-learning interactive process , 1974 .

[119]  Roberto Navigli,et al.  Entity Linking meets Word Sense Disambiguation: a Unified Approach , 2014, TACL.

[120]  Frank van Harmelen,et al.  A Contextualised Semantics for owl: sameAs , 2016, ESWC.

[121]  Ashwin Machanavajjhala,et al.  No free lunch in data privacy , 2011, SIGMOD '11.

[122]  Aldo Gangemi,et al.  Modelling Ontology Evaluation and Validation , 2006, ESWC.

[123]  Daniel P. Miranker,et al.  Mapping Relational Databases to Linked Data , 2014, Linked Data Management.

[124]  Herbert Van de Sompel,et al.  A Perspective on Archiving the Scholarly Web , 2014, iPRES.

[125]  Gerard de Melo,et al.  Multimodal Question Answering over Structured Data with Ambiguous Entities , 2017, WWW.

[126]  Reynold Xin,et al.  GraphFrames: an integrated API for mixing graph and relational queries , 2016, GRADES '16.

[127]  Richard Socher,et al.  The Natural Language Decathlon: Multitask Learning as Question Answering , 2018, ArXiv.

[128]  Paolo Ciancarini,et al.  Empirical Analysis of Foundational Distinctions in Linked Open Data , 2018, IJCAI.

[129]  Frank van Harmelen,et al.  Stream reasoning: A survey and outlook , 2017, Data Sci..

[130]  R. Peng.  Reproducible Research in Computational Science , 2011, Science.

[131]  Erhard Rahm,et al.  Recent Advances in Schema and Ontology Evolution , 2011, Schema Matching and Mapping.

[132]  Amit P. Sheth,et al.  Knowledge Representation on the Semantic Web , 2007 .

[133]  Daniele Braga,et al.  Stream Reasoning : Where We Got So Far , 2010 .

[134]  Jens Lehmann,et al.  DBpedia - A large-scale, multilingual knowledge base extracted from Wikipedia , 2015, Semantic Web.

[135]  Qiang Yang,et al.  A Machine Learning Approach for Instance Matching Based on Similarity Metrics , 2012, SEMWEB.

[136]  Agnieszka Lawrynowicz.  Semantic Data Mining - An Ontology-Based Approach , 2017, Studies on the Semantic Web.

[137]  Marco Rospocher,et al.  Frame-Based Ontology Population with PIKES , 2016, IEEE Transactions on Knowledge and Data Engineering.

[138]  Hema Swetha Koppula,et al.  RoboBrain: Large-Scale Knowledge Engine for Robots , 2014, ArXiv.

[139]  Steffen Staab,et al.  Ontology enrichment by discovering multi-relational association rules from ontological knowledge bases , 2016, SAC.

[140]  Marcelo Arenas,et al.  Foundations of Modern Query Languages for Graph Databases , 2016, ACM Comput. Surv..

[141]  Gerhard Weikum,et al.  On the Utility of Automatically Generated Wordnets , 2007 .

[142]  Diego Reforgiato Recupero,et al.  Framester: A Wide Coverage Linguistic Linked Data Hub , 2016, EKAW.

[143]  Heiko Paulheim,et al.  Knowledge graph refinement: A survey of approaches and evaluation methods , 2016, Semantic Web.

[144]  Umberto Straccia,et al.  A General Framework for Representing, Reasoning and Querying with Annotated Semantic Web Data , 2011, J. Web Semant..

[145]  Georg Lausen,et al.  SP2Bench: A SPARQL Performance Benchmark , 2008, Semantic Web Information Management.

[146]  Evgeniy Gabrilovich,et al.  A Review of Relational Machine Learning for Knowledge Graphs , 2015, Proceedings of the IEEE.

[147]  Eneko Agirre,et al.  Random Walks for Knowledge-Based Word Sense Disambiguation , 2014, CL.

[148]  Vasant Honavar,et al.  Secrecy-Preserving Query Answering for Instance Checking in EL\mathcal{EL} , 2010, RR.

[149]  Marta Sabou,et al.  Ontology (Network) Evaluation , 2012, Ontology Engineering in a Networked World.

[150]  Enrico Motta,et al.  Ontology evolution: a process-centric survey , 2013, The Knowledge Engineering Review.

[151]  Roberto Navigli,et al.  Word sense disambiguation: A survey , 2009, CSUR.

[152]  Dieter Fensel,et al.  It's a Streaming World! Reasoning upon Rapidly Changing Information , 2009, IEEE Intelligent Systems.

[153]  Heiko Paulheim,et al.  Synthesizing Knowledge Graphs for Link and Type Prediction Benchmarking , 2017, ESWC.

[154]  Ruben Verborgh,et al.  Decentralised Authoring, Annotations and Notifications for a Read-Write Web with dokieli , 2017, ICWE.

[155]  Scott Shenker,et al.  Shark: SQL and rich analytics at scale , 2012, SIGMOD '13.

[156]  Chris Brew,et al.  TR Discover: A Natural Language Interface for Querying and Analyzing Interlinked Datasets , 2015, International Semantic Web Conference.

[157]  Roberto Navigli,et al.  Train-O-Matic: Large-Scale Supervised Word Sense Disambiguation in Multiple Languages without Manual Training Data , 2017, EMNLP.

[158]  Maria-Esther Vidal,et al.  MINTE: semantically integrating RDF graphs , 2017, WIMS.