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Call for Papers

  • Program Chairs 

Claudia d’Amato (Department of Computer Science, University of Bari, IT)

Fabien Gandon (Wimmics, Inria, I3S, CNRS, Univ. Nice Sophia Antipolis, FR)

ESWC is a A rank conference according to CORE classificarion and a major venue for discussing the latest scientific results and technology innovations related to the Semantic Web. The 11th edition of ESWC will take place from May 25th, 2014 to May 29th, 2014 in Anissaras, Crete, Greece. Besides a main focus on advances in Semantic Web research and technologies, ESWC 2014 is seeking to broaden its attention to span other relevant research areas in which Web semantics plays an important role.

The goal of the Semantic Web is to create a Web of knowledge and services in which the semantics of content is made explicit and content is linked to both other content and services. This arrangement of knowledge-based functionalities is weaving together a large network of human knowledge, and making this knowledge machine-processable to support intelligent behaviour by machines. Additionally, it supports novel applications allowing content from heterogeneous sources to be combined in unforeseen ways and support enhanced matching between users needs, software functionalities and online content.

Creating such an interlinked Web of knowledge which bridges between heterogeneous content and services requires collaboration between several computer science domains. Also, within this hybrid space that the Web has become, where humans and software interact in a complex manner, fundamentally requires an inter-disciplinary approach to find novel solutions to the problems generated.  

ESWC 2014 will feature twelve thematic research tracks (see below) and an in-use and industrial track. Submissions of interdisciplinary research papers, covering more than one thematic track, are also encouraged. In addition, the in-use and industrial track will provide an opportunity for dialogue and discussion on industrial applications, tools, deployment experiences, case studies and usage analysis.

Submitted papers should describe original work, present significant results, and provide rigorous, principled, and repeatable evaluation. We strongly encourage and appreciate the submission of papers incorporating links to data sets and other material used for evaluation as well as to live demos and software source code.

We therefore encourage submissions addressing several conference research topics. However, each paper should be associated with at least one of the topics of the conference. The main research topics this year are:

  • Vocabularies, Schemas, Ontologies;
  • Reasoning;
  • Linked Open Data;
  • Social Web;
  • Web Science;
  • Data Management, Big data, Scalability;
  • Natural Language Processing;
  • Information Retrieval;
  • Machine Learning;
  • Mobile Web;
  • Sensors;
  • Streams;
  • Services, processes, and cloud computing.

Additional special research topics this year are:

  • Cognition and Semantic Web;
  • Policies, Rights, Governance;
  • Semantic multimedia web.

Important Dates

Abstract submission: Wednesday 8th of January, 2014 (sharp) - 23:59 Hawaii Time

Full paper submission: Monday 13th of January, 2014 (sharp) - 23:59 Hawaii Time

Authors rebuttal: Wednesday 19th-21st of February, 2014 - 23:59 Hawaii Time

Acceptance notification: Wednesday 26th of February, 2014 - 23:59 Hawaii Time

Camera ready: Monday 10th of March, 2014 - 23:59 Hawaii Time

Submission Information

ESWC2014 welcomes the submission of original research and application papers dealing with all aspects of representing and using semantics on the Web. We encourage theoretical, methodological, empirical, and applications papers. The proceedings of this conference will be published in Springer's Lecture Notes in Computer Science series.

This year three of the best papers presented at the conference will have the opportunity to submit an extended version to a special issue of the journal "Semantic Web - Interoperability, Usability, Applicability" (IOS Press).

Papers should not exceed fifteen (15) pages in length and must be formatted according to the information for LNCS authors. Papers must be submitted in PDF (Adobe's Portable Document Format) format. Papers that exceed 15 pages or do not follow the LNCS guidelines will be automatically rejected without a review. Authors of accepted papers will be required to provide semantic annotations for the abstract of their submission - details of this process will be given on the conference Web page at the time of acceptance. At least one author of each accepted paper must register for the conference. More information about the Springer's Lecture Notes in Computer Science (LNCS) are available on the Springer LNCS Web site.

Submissions and reviewing will be supported by the EasyChair system: https://www.easychair.org/account/signin.cgi?conf=eswc2014

ESWC 2014 Tracks

Vocabularies, Schemas, Ontologies

Chairs
Maria Keet - University of KwaZulu-Natal
Jérôme Euzenat - Inria & LIG, France
 

Reasoning

Chairs
Thomas Lukasiewicz - University of Oxford
Sebastian Rudolph - Technische Universität Dresden 
 

Linked Open Data

Chairs
Laura Hollink - Vrije Universiteit Amsterdam 
Vojtech Svatek - University of Economics, Prague
 

Social Web and Web Science

Chairs
Matthew Rowe - Lancaster University, UK
Pieter De Leenheer - Collibra
 

Semantic Data Management, Big data, Scalability

Chairs
Maria-Esthel Vidal - Universidad Simón Bolivar,Venezuela
Jacopo Urbani - Vrije Universiteit Amsterdam, NL
 

Natural Language Processing and Information Retrieval

Chairs
Elena Montiel-Ponsoda - Universidad Politécnica de Madrid, Spain
Diana Maynard, University of Sheffield, UK
 

Machine Learning

Chairs
Nicola Fanizzi - University of Bari
Agnieszka Lawrynowicz - Poznan University of Technology
 

Mobile Web, Sensors and Semantic Streams

Chairs
Payam Barnaghi, University of Surrey, UK
Kerry Taylor, CSIRO, Australia
 

Services, Processes and Cloud Computing

Chairs
Matthias Klusch - DFKI, Germany
Freddy Lecue - IBM Research, Smarter City Technology Centre, Dublin, Ireland
 

In-use & Industrial Track 

Chairs
Kingsley Idehen - OpenLink Software
Evelyne Viegas, Microsoft Research
 

Cognition and Semantic Web

Chairs
Aldo Gangemi - University of Paris 13/ISTC-CNR
Krzysztof Janowicz - University of California 
 

Semantic Web policies, rights and governance

Chairs
Renato Iannella - Semantic Identity, Australia
Pompeu Casanovas - Universitat Autònoma de Barcelona
 

Semantic Multimedia Web

Chairs
Massimo Romanelli, Attensity EUROPE GmbH
Stefan Rüger - Knowledge Media Institute, The Open University, UK
 

Research Track: Vocabularies, Schemas, Ontologies

Ontologies and related artifacts (such as schemas and vocabularies) play a central role in the Semantic Web by enabling the design of robust applications needing intensive reasoning and some intelligence, as well as enabling shallow querying and reasoning over large-scale linked data and documents. The Semantic Web has also established empirical perspectives on ontologies and their development; e.g., ontologies can be learned from text, extracted from legacy representations and the Web, and can be studied experimentally with experts and users, and against realistic tasks, making design patterns for ontologies emerge out of good practices. Finally, the management and dynamics of ontologies are addressed by matching, versioning, evolution, modularization, and other ontology engineering methods.

This track intends to address innovative top-down and/or bottom-up research on ontologies, vocabularies, and schemas for the Semantic Web, Web 3.0, Linked Data, and semantic technologies in general. Both theoretical and empirical research papers are welcome. Topics of interest include, but are not limited to, the following:

  • Languages, tools, and methodologies for (collaborative) ontology engineering
  • Ontology matching, alignment and merging
  • Evolution of vocabularies, schemas, and ontologies on the Web
  • Ontology repositories and ontology search
  • Ontology- and schema-based data integration
  • Knowledge acquisition (extraction, learning)
  • Ontology management, maintenance and reuse
  • Ontology and schema quality and evaluation
  • Ontology-driven applications and ontologies for semantic technologies
  • Ontologies and vocabularies for specific domains
  • Ontology-/schema-/vocabulary-based information retrieval
 

Research Track: Reasoning

The Reasoning track invites submissions on all topics related to reasoning with ontologies and rules, to reasoning for the World Wide Web, to reasoning using Semantic Web technologies, reasoning and learning, and reasoning on highly dynamic and noisy data streams. Contributions can range from theoretical advances to usage-driven developments. Particularly encouraged are future-oriented contributions concerning topics such as stream reasoning, reasoning on the Web of Data, reasoning in presence of noisy data, and the application-driven development of reasoning methods. Papers with a strong relation to other tracks, but a clear focus on reasoning are also welcome. The range of topics of interest includes, but is not limited to, the following:
 
  • RDF- and OWL-based reasoning
  • declarative rule-based reasoning techniques, rule languages, standards, and rule systems
  • mixing logical and statistical reasoning
  • approximate reasoning techniques
  • combining learning and reasoning
  • non-deductive approaches to reasoning, non-standard reasoning over ontologies
  • scalable reasoning, reasoning with large, expressive or distributed ontologies
  • distributed and parallel reasoning
  • ontology-based data access
  • stream reasoning
  • reasoning with context dependent knowledge
  • commonsense reasoning
  • reasoning with inconsistency, reasoning under uncertainty, reasoning about vagueness
  • reasoning about user preferences
  • reasoning on the Web of data
  • reasoning for knowledge engineering, for data integration, for data and knowledge extraction from the Web
  • applications of reasoning
  • implementation and evaluation of reasoners
 

Research Track: Linked Open Data

Linked Open Data, as a best practice of promoting the sharing and publication of structured data on the semantic Web, has gained significant momentum over the past years. As a newly emerged research area, there is much to be addressed from the extraction of Linked Data, visualization, query, storage, to the quality assessment, reasoning, and smart consumption.  Existing research and technologies must be further exploited and adapted to empower a continuous and rapid advance in Linked Data movement. Therefore, our topics of interest include the following, but not limited to:
 
  •  Linked Open Data extraction and publication
  • Storage, publication and validation of data, links, and embedded LOD
  • Linked data integration/fusion/consolidation
  • Database, IR, NLP and AI technologies for LOD
  • Creation and management of LOD vocabularies
  • Linked Open Data consumption
  • Linked data applications (e.g., eGovernment, eEnvironment, or eHealth)
  • Dataset description and discovery
  • Searching, querying, and reasoning in LOD
  • Analyzing, mining and visualization of LOD
  • Usage of LOD and social interactions with LOD
  • Dynamics of LOD
  • Architecture and infrastructure
  • Provenance, privacy, and rights management; relationship between LOD and linked closed data
  • Assessing data quality and data trustworthiness
  • Scalability issues of- Linked Open Data. 
 

Research Track: Social Web and Web Science

The tremendous increase in using Web technologies for establishing and maintaining diverse social interactions has transformed the Web into a socio-technological phenomenon. As a recognition of this status quo, the emerging Web Science discipline has taken a multidisciplinary approach towards understanding Web phenomena with a special focus on the people and communities who shape the Web and whose lives are influenced by Web technologies emerging in an increasingly ubiquitous way. In tandem with such studies, the rise in uptake of social platforms and the ubiquity of social functionalities across the Web has meant that the machine-readability of social data, and thus its automatic interpretation, from disparate Web platforms has become increasingly important. Therefore both Semantic Web and Social Web research have an important impact on one another:
 
  1. Semantic Web research offers important technologies for making sense of and dealing with the large amount of user generated content that is inherently dynamic, heterogeneous and contextual.
  2. Semantic Web research can greatly benefit from user generated content for extending its information basis and improving its technologies, for example its reasoning mechanisms.

 

This track invites contributions that explore synergies between the Semantic Web and its technology on the one hand, and social and ubiquitous Web phenomena on the other hand. Topics of interest include but are not limited to the following:
 
  • Bringing user-generated content into the Semantic Web
  • Mining semantics from social data and collective intelligence from community interactions
  • Semantically enabled social platforms and applications: wikis, forums, portals, blogs and microblogs, etc.
  • Web users as virtual and physical sensors, crawlers, etc. for a ubiquitous Social Semantic Web
  • Semantics for personalisation: recommendations, social navigation, collaborative search, social filtering, etc
  • Socio-semantic Web, the Internet of Things and reality augmented by the Socio-semantic Web
  • Social semantic networks, network effects, community analysis and user evolution
  • Semantics for Human-based computation and vice-versa
  • Querying, mining and analysis of social semantic data and dynamics
  • Representing and reasoning with uncertainty, provenance and trust in social data
  • Big social semantic data: scalable processing techniques, trust and compliance
  • Ethical issues related to the use of user generated content (e.g., privacy, consent, access control)
     

Research Track: Semantic Data Management, Big data, Scalability

In the last years, we witnessed the emergence of a new Web of data in the form of a dense network of linked datasets available on the Web. Currently, the Web of data contains billions of facts coming from different organizations (such as Life and Health science groups, Government agencies, Wikipedia, or entertainment organizations) and its ever-growing size poses crucial challenges to the development of technologies capable to manage such data on a Web-scale.
In this context, Semantic Data Management techniques rely on the meaning of the data for storing, managing, integrating and querying the Web of Data. The Semantic Data Management Track aims at bringing together researchers from the Database, Artificial Intelligence, and Semantic Web communities, to discuss research issues and experiences in developing, deploying and evaluating concepts, techniques and applications related to the Management of Semantic Web Data, especially on a large scale.
To this end, this track encourages paper submissions on the following topics:
 
  • Systems for (distributed) Semantic Data Management.
  • Semantic Data Management in Graph Databases.
  • Scalable Analysis of the Web of Data.
  • Query processing of Semantic Data.
  • Semantic access to Legacy Data.
  • Management of Spatial Data.
  • Management of Dynamic Data & Temporal Semantics.
  • Virtualized Semantic Stores.
  • Exploratory Semantic Searching and Browsing.
  • Security and privacy in large datasets.
  • Traceability and trustworthiness.
  • Ranking of Semantic Data.
  • Provenance in the Integration of Heterogeneous Semantic Data.
  • Performance and Evaluation of Semantic Data Management Techniques.
  • Benchmarking of Semantic Data Management Techniques.
  • Quality of Big Data.
  • Semantic Data Management technologies for Big Data (volume, velocity, variety).
  • Domain-Specific Semantic Data Management technologies: Life Science, eGovernment, eEnvironment, eMobility, eHealth, and within the enterprise.

Research Track: Natural Language Processing and Information Retrieval

The belief that the interaction between NLP and Semantic Web could boost the performances of semantic Web technologies has become an undeniable fact. NLP services have substantially contributed to the rapid development of the Semantic Web, in the same way as the Semantic Web has contributed to the enhancement of NLP systems by providing background knowledge. In the Big Data era, the Linked Open Data (LOD) initiative has opened up new perspectives for NLP research by making available a giant knowledge base that contains both general and very specific domain knowledge for use in language processing tasks. The NLP community in turn has provided lexical and linguistic resources that, in combination with this data, can help make sense of the structured knowledge on the Web.
Multilingualism and multiculturalism are also highly relevant: since more and more data and linguistic resources are published in the LOD cloud in languages other than English. Web technologies such as Semantic Search, Information Extraction, Question Answering and Social Network Analysis have to account for these languages. Finally, user- or community-generated data and annotations have become extremely relevant for businesses and market studies.
The main goal of the track is to foster a closer interaction between the NLP and Semantic Web communities, which could produce shared and better standards for knowledge and linguistic representation. This is necessary for maximizing data exploitation, as well as to increase the amount of linked data by exploiting knowledge acquisition techniques.
To this end, interdisciplinary papers addressing a clear interaction between Natural Language Processing and Semantic Web issues are solicited. Specific topics include, but are not limited to:
 
  • Semantic annotation exploiting linked data
  • Monolingual or cross-lingual semantic search and question answering
  • Standards for meaning and/or linguistic representation on the Semantic Web
  • Ontology learning and ontology population
  • Ontology-based information extraction
  • Ontology lexicalization and localization
  • Entity/event coreference and linking via the Semantic Web
  • Exploitation of lexical resources for the Semantic Web
  • Natural Language Search and Question Answering over linked data
  • Language processing of social networks
  • Opinion mining exploiting semantic information
  • Natural Language Processing services using LOD
  • Integrating ontologies/Linked Open Data with Language Resources
  • Information Extraction for Social Media Mining
 

Research Track: Machine Learning

In the perspective of the Semantic Web (SW) as a Web of Data, Machine Learning (ML) approaches are gaining an increasing relevance. ML can deal with the intrinsic uncertainty in Web data containing incomplete and/or contradictory information. ML is also very well suited to cope with a large scale of Web data and provides tools for big data analytics. The prospect is that innovative solutions based on specific application of ML techniques to information sources such as Linked Data, tagged data, social networks, and ontologies will increasingly support standard SW tasks and enable new ones.
We invite high quality contributions from all areas of research that address the emerging data challenges. Topics of interest include but are not limited to the following:
 
  • Data mining and knowledge discovery in the Web of data
    • Statistical relational learning
    • Discovery of associations, patterns and events
    • Data quality assessment: modeling and maintenance of provenance information
    • Feature extraction, pre-processing and transformation of SW data
    • Evaluation and benchmarking of ML models
  • Big Data analytics involving Linked Data
  • Inductive reasoning on uncertain knowledge
    • Combination of logic reasoning and ILP
    • Approaches adopting alternative theories of evidence
    • Inductive techniques based on semantic similarity
  • Ontology learning and enrichment
  • Ontology matching and instance matching
  • Knowledge base maintenance
    • Construction, refinement, interlinking, debugging, repair
    • Efficient indexing, search and retrieval
  • Mining the Social SW
    • Social network analysis, sentiment analysis, link prediction,
    • Usage mining, ranking methods, recommendation
  • Semantic data mining (data mining approaches that use ontologies as background knowledge)
  • Meta-learning
  • Cognitive-inspired approaches and exploratory search in the SW
  • Discovery science involving Linked Data and ontologies

Research Track: Mobile Web, Sensors and Semantic Streams

With the advent of the Semantic Web, Web Services, and social networks, the Web has become a global data sharing and processing platform. Social media and smart phones are driving citizen sensing where mobile people report observations of the real world (e.g. via social media such as Twitter). In parallel, the Internet of Things (IoT), that is, networks of devices with sensors and actuators, has matured to become a major scientific and economic driver, whose potential impact cannot be overestimated.
While the Web provides ease of use of distributed resources and a sophisticated development infrastructure, the IoT brings in real-time information from the physical world. The combination will foster the development of even more sophisticated systems. However, most of this dynamic information currently available is not easy to access and process, and requires human knowledge of concrete deployments to use effectively.
In this track we welcome new ideas and results that combine stream data - available on the Web or coming from sensors and/or mobile devices - and semantic technologies for effective data description, representation, interpretation, integration, and development of novel applications. We invite high-quality submissions related to (but not limited to) one or more of the following topics:
 
  • Architectures, middleware and data management for semantic streams and semantic sensor networks
  • Context- and location-aware applications based on semantic technologies
  • Intelligent data processing and large sensor and mobile Web data analytics
  • Real-time data and resource discovery with quality-aware information search and retrieval
  • Using semantic enrichment and large-scale data analytics for processing or interpreting dynamic IoT data
  • Linked data and mashups over stream data
  • Ontologies and rules for a dynamic Web
  • Provenance of semantic data on the sensor and mobile Web
  • Scalability and performance of semantic technologies on sensor and mobile Web
  • Semantic-based security, privacy and trust in mobile devices and applications
  • Semantic event detection and response
  • Semantics for the factory of the future

 

Research Track: Services, Processes and Cloud Computing

As the Internet of services is converging with the Internet of things, 3D Web and quantum internet, the variety and number of application services in different domains is continuously increasing. In fact, anything may become a service (XaaS) to be provided as, or accessible through, a Web service ranging from public services to multimedia content services, to business software (SaaS), platforms (PaaS), and infrastructures (IaaS) in public, private or federated clouds to appliances, sensors and machinery – plus the 50 billion other things which are expected to become connected to the Internet as data services (DaaS) by 2050. Linked data provided by (semantic) services in the Web, sensor Web, 3D Web are ready to be exploited following the Web principles.
This track is concerned with latest advances in semantic technologies that are suitable to address the challenges and opportunities raised. Topics of interest include but are not limited to:
 
  • Privacy-aware service description, representation, processing and reasoning
  • Context-aware elicitation of service semantics
  • Semantics of services in the sensor Web (IoT)
  • Service-based applications in the 3D Web, Sensor Web (IoT)
  • Services for semantic stream reasoning and applications
  • Personalized interaction with Web-accessible things, services and business processes
  • Semantic discovery and composition planning of services,
  • e.g. in REST, WSDL, OWL-S, USDL, WSML, Linked USDL, etc.
  • Lightweight services processing
  • Task-oriented data, service and business process mash-ups
  • Model-driven semantic service description, search and composition
  • Parallel and distributed execution of complex services
  • Service negotiation in practice
  • Semantic description of business process models: Models, tools and use cases.
  • Semantic service-based business process management: Systems, tools and use cases.
  • Process mining and business process service re-use: tools and use cases.
  • Semantics and services for cloud management
  • Semantics and services for cloud interoperability
  • Semantics and services for trusted and secure cloud computing
  • Scalable automation of the service life cycle
  • Semantics for service governance and sciences
  • Semantic services for mobile applications
  • Mobile services and public/private clouds
 

In-Use & Industrial Track

Semantic Web technologies are making it to the society in a myriad different ways. In some cases, technology uptake loyally resembles the original vision of the researchers pioneering this research field. However, more and more frequently semantic technologies are being adopted in unanticipated ways, shaped by the actual needs of the market and its players, who appreciate the value added by these technologies and seek to gain some competitive advantage through selective adoption.
The Semantic Web in Use and Industry track provides a common ground for both researchers and industry, taking the outcome of their research to the market and adopting Semantic Technologies in specific businesses, respectively.
Submissions to the Semantic Web in Use and Industry track will provide a deeper insight on the exploitation of Semantic Web technologies in different economic sectors. Papers will be therefore evaluated on the basis of the impact of semantic technologies in the market and the society and how it addresses real-life problems. A strong evaluation of the systems and methods discussed proving evidence of such impact is therefore required. Submissions on novel research directions needed to be developed by the Semantic Web community to collaborate with industry and government partners are also encouraged.
Topics of interests include but are not limited to the following:
 
  • Applications of Semantic Technologies in industry or government
  • Best practices and lessons learnt from using the Semantic Web and Linked Data
  • Industry and Business Trends related to the use of Semantic Technologies and Linked Data
  • Financial and research investment in Semantic Technologies and Linked Data
  • Areas in need of more research to make Semantic Technologies and Linked Data successful
  • The role of Machine Learning for semantic understanding
  • The role of information exchange standards in industry and government
  •  

Research Track: Cognition and Semantic Web

Our society and economy is at the verge of an era where dealing with large amounts of structured data plays an increasingly important role. Such data can be obtained from climate, pollution or traffic sensors in a city, it can comprise customer demand of an online travel agency or crowd-sourced spatial data such as collected by the OpenStreetMaps community. Integrating, analysing and using such data can result in completely new insights, applications as well as products and services. For example, we will be able to re-route traffic, if we detect traffic patterns causing increased air pollution in certain weather conditions. Travel companies can suggest background information on events, historic sights or attractions for certain travel destinations. Governments and public administrations can come closer to citizens and leverage their creative potential by opening up governmental data. In this track we aim to explore the scientific and technological challenges and innovative approaches for managing big data and large amounts of small data. 

The range of topics of interest includes, but is not limited to:
 
  • Analogy and analogical learning
  • Semantic similarity
  • Cultural aspects of categorization, Theories of categorization, e.g., prototypes
  • Framing and conceptual metaphor
  • Exploratory search and information seeking in Linked Data
  • Dialog systems
  • Approximate reasoning
  • Semantic heterogeneity and interoperability
  • Cognitive constraints
  • Symbol grounding
  • Emerging semantics
  • Change and ontology evolution
  • Knowledge patterns and pattern recognition
  • Cognitive strategies for interfaces and reasoners, Novel user interaction paradigms and interfaces
  • Common-sense reasoning
  • Personalization
  • Inductive and Abductive Reasoning
  • Semantic translation, mapping, and alignment
  • Spatial cognition
  • Conceptual spaces
  • Human competencies on the Semantic Web
  • Heuristics based on human knowledge representation
  • Consequences of task-switching, priming, and stopping-rules
  • Neuroscience for the Semantic Web
  • Linked Data Visualization

Research Track:  Semantic Web Policies, Rights and Governance

The Semantic Web’s foundations provides unprecedented advances for the specification of formal rules and assertions that can underpin many of the legal, business, and social propositions required by current and future ICT systems.

The aim of this track is to provide practical and exploratory usage of the Semantic Web in the areas of policies, rights, privacy, law, data protection, regulations, and governance of data and services on the Web.

Submissions are sought that can address the Topics from a number of dimensions, including legal (eg directives, regulations, statutes and court rulings), ethical (e.g. principles and best practices), technical (eg semantic platforms, languages, ontology engineering, and tools), and governance (eg legal ontologies, communities, democratic participation). The track goal is to stimulate discussion about state-of-the-art approaches for the development of policy frameworks for rights and privacy, identify legal issues with the Semantic Web, and provide concrete use cases for the application of the Semantic Web to the governance and implications of community participation in policies.

Topics of interests include but are not limited to the following:

  •  
  • Law, Intellectual property and legal issues for data and schemas
  • Vocabularies and inferences for rights and legal aspects
  • Rights and licences for data and semantics
  • Licenses for Linked Open Data
  • Access control, Trust & Security
  • Privacy by Design and semantics
  • Digital Rights Management  (DRM)
  • Legal ontology process and management
  • Policy and ethical aspects of Privacy, Data Protection and Security by Design
  • Smart data and the Semantic Web
  • Natural Language Processing and the law
  • SW, Robotics and the law
  • Normative Multi-agent Systems and the SW
  • Agreement Technologies, Online Dispute Resolution and Electronic Institutions
  • Best Practices and Ethical Codes for data exchange and interoperability
  • Informational ethics and the SW
  • Provenance semantics
  • Legal reasoning and argumentation
  • Law and governance in deliberative democracy and democratic participation
  • Access to legal information and visualization

 

Research Track:  Semantic Multimedia Web

This track aims at exploring capabilities, research questions and applications of semantic multimedia in the context of social media, semantic Web and media delivery systems. We welcome original paper submissions that contribute to state-of-the-art technologies, standards, tools and methodologies or that present new concepts and approaches.

Why semantic multimedia? Linked Open Data as a container for structured content experience a significant growth offering an extensive source for knowledge annotation, referencing, hyper-linking and inferring. Social media get more and more entangled in multimedia management (e.g., youtube, flickr, and mixbit). While in 2007 CacheLogic already observed that 60 percent of Internet traffic consists of multimedia content, Cisco now goes a step further and asserts that rich multimedia content is driving the mobile development predicting that "by 2015, over 90 percent of all Internet traffic is expected to be video". This is also exemplified in fast growing markets of TV on Web and Web on TV and also by corresponding W3C activities (e.g., Web and TV IG).

Digital text, audio, image, video, 3D data and their hyperlinked combinations are representative examples of media that we subsume under Web multimedia for the purpose of this call. The following topics are particularly relevant, but by no means exhaustive:

  • State-of-the-art of multimedia metadata formats for Web support
  • Sharing and reuse of Web knowledge that is encoded in different media
  • Management of multimedia Web repositories
  • Content- and context-based indexing, search, retrieval and browsing of multimedia on the Web
  • Multimedia content analysis and understanding
  • Query models, paradigms, and languages for semantic multimedia
  • Community-based semantic multimedia content management
  • Semantic multimedia summarization and visualization
  • Linked open multimedia
  • Semantic-based multimedia applications
  • Semantic multimedia & social media
  • Semantic media tools and methodologies