The USEWOD workshop series has created and maintained a forum for researchers to investigate the synergy between the Web of Data and Web usage mining. This involves the analysis of semantic data usage but also the exploitation of Semantic Web technologies to advance usage mining approaches in general. Among other things, USEWOD hosts what has become the reference data set for research on query logs of Linked Data endpoints. This 4th edition of USEWOD will focus on this as a special theme: building a USEWOD Web Observatory to track the distribution of research based on the USEWOD data set. Web Observatories study a global network of heterogeneous data repositories, each observing and analysing the activity on the Web across a range of topics. Of course, the USEWOD data set will be extended again and a data challenge offered. We invite submissions on this theme (and other topics pertinent to USEWOD), and in addition to paper presentations, the workshop will host a live crowdsourcing activity to collect the provenance metadata that finally brings together the root data set and as many publications that refer to it as possible. Complementing the contributed presentations and the crowdsourcing activity, Professor Dame Wendy Hall plans to give a keynote at USEWOD2014.

Over the years, Semantic Web based systems, applications, and tools have shown significant improvement. Their development and deployment shows the steady maturing of semantic technologies and demonstrates their value in solving current and emerging problems. Examples include enabling generic clients, facilitating autonomous agents and large scale distributed data integration. Despite the encouraging figures, the number of enterprises working on and with these technologies is dwarfed by the large number who have not yet adopted Semantic Web technologies. Current adoption is mainly restricted to methodologies provided by the research community. Although the Semantic Web acts as a candidate technology to the industry, it does not win through in current enterprise challenges like data fusion, data integration or natural language processing. To better understand the market dynamics uptake needs to be addressed and if possible quantified.

The PROFILES 2014 workshop aims to gather innovative search approaches for large-scale, distributed and heterogeneous linked datasets inline with dedicated approaches to analyse, describe and discover endpoints, as an inherent task of query distribution. PROFILES 2014 will equally consider both novel scientific methods and techniques for querying, assessment, profiling, and curation distributed datasets as well as the application perspective, such as the innovative use of tools and methods for providing structured knowledge about distributed datasets, their evolution and fundamentally, means to search and query the Web of Data. The workshop will provide a highly interactive forum for researchers in the fields of Semantic Web and Linked Data, Databases, Semantic Search, Text Mining, NLP as well as Information Retrieval.

In Social Media and Linked Data for Emergency Response (SMILE2014) workshop we gather innovative approaches for exploitation of social media and Linked Data for emergency response and crisis management using semantic web technologies. The workshop will cover advancements in relevant technology and application areas. We mainly aim to bring together expertise from three research areas: Semantic Web and Linked Data; Social Sciences; Emergency Response and Crisis Management. Topics of the SMILE currently attract more attention than ever from the research community. For instance, two recently started W3C community groups are related to SMILE: W3C RDF Stream Processing Community Group (dealing with issues of RDF data delivered and processed in a streaming fashion), and W3C Emergency Information Community Group (dealing with vocabularies and best practices for semantic web technologies in emergency response)

This workshop focuses on the introduction, presentation, and discussion of novel approaches to semantic sentiment analysis. Special focus will be given to semantic methods, models, and tools that exploit common-sense knowledge bases to perform multi- or open-domain sentiment analysis. The intended audience of the workshop includes researchers from academia and industry as well as professionals and industrial practitioners to discuss and exchange positions on new hybrid techniques, which use semantics for sentiment analysis.

With this workshop, we aim to discover new ways to embrace the opportunities that Web APIs offer in terms of data consumption, processing and provisioning but also to investigate the possibilities of integrating them more closely with Linked Data. We want to challenge researchers towards developing integrated description and implementation approaches through both paper submissions and interactive on-site discussion and dialog. In particular, we are looking for description approaches, implementation solutions, use cases and applications that support a more automated and unified Web API use.

The Empirical 2014 workshop is a half-day workshop that will open the Extended Semantic Web Conference 2014 and seeks to gather people from all fields to work together to enhance our evaluation methodology. Statistical inference using hypothesis-testing methods is not commonly used to support empirical results reported in the Semantic Web literature. Thus, given the impact that these statistical methods may have on different domains, attendees may see the workshop as a venue to discuss the applicability of these methods in their current studies. Trivial use of hypothesis testing is not in the scope of the workshop. The primary focus, as will be detailed in the call for papers, is on statistical methods to evaluate assertions on performance of complex systems. Hitherto, the focus of the community has been on benchmarking. Currently, it suffers from several problems, e.g., lack of summary statistics, no hypothesis tests, no structured approach to control of experiments, oversimplification of the benchmark in face of complex problems, etc.

Semantic publishing is central to the openness that has been embraced by scholarly communication, e-science, data journalism, e-government and across many other domains. This openness implies deep changes in making the semantics of the data available for integration, consumption and analysis. Researchers are moving from a narrative based communication into a data-based convincing argument. Such shift impacts all layers of scholarly; data needs to be archived and kept readily available and interoperable. Scholars across many disciplines are undergoing an important shift in their communication practices; reproducibility, smart data storage, intelligent use of the Web as a platform and not solely as a dissemination channel, business intelligence for e-science content and many others are currently a matter of discussion in the academic community.
The validation of scientific results requires reproducible methods, which can only be achieved if the same data, processes, and algorithms as those used in the original experiments are available in a complete and computationally amenable form. Although Biomedical journals often ask for “Materials and Methods” and datasets to be made available, reproducing experiments, sharing, reusing and leveraging scientific data is becoming increasingly difficult. Experimental data in scientific disciplines is a Big Data problem; how can we make effective use of scientific data, how should it be semantically represented, interlinked, reused, how to effectively represent experiments in scientific publications? How to bridge the gap between publications and data repositories?

The HSWI workshop aims to explore and evaluate good practices in interface design, and ultimately feed into possible recommendations for standardizing and consolidating knowledge and good practices into a set of guidelines for semantic web developers, to ensure the usability and reasonably functional user experiences of the next generation of Semantic Web applications.

This 2nd workshop on Linked Media (LiME-2014), building on last year’s successful event held at WWW2013, aims at promoting the principles of Linked Media on the Web by gathering semantic multimedia and Linked Data researchers to exchange current research and development work on creating conceptual descriptions of media items, multimedia metadata publication on the Web, and its semantic processing, particular based on Linked Data approaches to concept matching and relationships. Specifically, we aim to build a research community to promote a future Web where automated multimedia analysis results can be used as a basis to integrate Linked Data-based conceptual annotations into structured media descriptions, which can be published and shared online. When media descriptions are more easily findable and processable, new applications and services can be created in which online media is more easily shared, retrieved and re-used. This will offer a wide range of possibilities for various stakeholders in the creative industries.

Abstract:

Developing ontologies is not an easy task and, as the ontologies grow in size, they are likely to show a number of defects. Such ontologies, although often useful, also lead to problems when used in semantically-enabled applications. Wrong conclusions may be derived or valid conclusions may be missed. Defects in ontologies can take different forms. Syntactic defects are usually easy to find and to resolve. Defects regarding style include such things as unintended redundancy. More interesting and severe defects are the modeling defects which require domain knowledge to detect and resolve such as defects in the structure, and semantic defects such as unsatisfiable concepts and inconsistent ontologies. Further, during the recent years more and more mappings between ontologies with overlapping information have been generated, e.g. using ontology alignment systems, thereby connecting the ontologies in ontology networks. This has led to a new opportunity to deal with defects as the mappings and other ontologies in the network may be used in the debugging of a particular ontology in the network. It also has introduced a new difficulty as the mappings may not always be correct and need to be debugged themselves.

Knowledge discovery is a well-established field with a large community investigating methods for the discovery of patterns and regularities in large data sets, including relational databases and unstructured text. Research in this field has led to the development of practically relevant and scalable approaches such as association rule mining, subgroup discovery, graph mining, and clustering. At the same time, the Web of Data has grown to one of the largest publicly available collections of structured, cross-domain data sets. While the growing success of Linked Data and its use in applications, e.g., in the e-Government area, has provided numerous novel opportunities, its scale and heterogeneity are posing several challenges to the field of knowledge discovery and data mining: The extraction and discovery of knowledge from very large data sets; The maintenance of high quality data and provenance information; The scalability of processing and mining the distributed Web of Data; and The discovery of novel links, both on the instance and the schema level.

The tremendous growth in multilingual text has significantly increased the need for multilingual resources in many research areas. Multilingual lexical knowledge is indispensable for implementing the next step towards the multilingual Semantic Web, i.e. a Web in which multilinguality is not a barrier, but an opportunity for sharing and spreading information across cultures and languages. A key recent development in the Semantic Web area is the Linguistic Linked Open Data cloud. However, this cloud does not contain many rich resources and, with the exception of DBpedia, is mostly monolingual. To address this and many other issues in semantics, we have introduced BabelNet, a very large multilingual semantic network that was created by automatically integrating existing knowledge resources, including machine-readable dictionaries such as WordNet, OmegaWiki and Wiktionary, and encyclopedic knowledge from Wikipedia. As a result BabelNet provides a unified multilingual repository of knowledge for solving issues in many areas such as multilingual semantic processing and linked open data.

The integration of the GoodRelations ontology into schema.org is one huge success story of applying Semantic Web technology to business challenges. In this tutorial, we will 1. give a comprehensive overview and hands-on training on the conceptual structures of schema.org for e-commerce, including patterns for ownership and demand, 2. present the full tool chain for producing and consuming respective data, 3. explain the long-term vision of linked open commerce, 4. describe the main challenges for future research in the field, and 5. discuss advanced topics, like access control, identity and authentication (e.g. with WebID); micropayment services (like Payswarm), and data management issues from the publisher and consumer perspective. We will also cover research opportunities resulting from the growing adoption and the respective amount of data in RDFa and Microdata syntaxes.

The tutorial describes existing approaches to model graph databases, different techniques implemented in RDF and Database engines, and their main drawbacks when a large volume of interconnected data needs to be traversed. We will focus on current solutions that have been proposed in the context of both the Semantic Web and Databases to manage large graphs. The target audience includes researchers and practitioners that develop or use query engines to consume RDF graphs. The participants will learn the properties of existing RDF and graph-based engines and how current approaches need to be extended to support efficient graph-based operations. A hands-on session will allow attendees to evaluate the performance and robustness of existing approaches.

The increasing availability of essential information as Linked Open Data has empowered ordinary citizens and organisations with means to increase their understanding of their political, social, economic and cultural environment. Social Media, on the other hand, provide citizens and organisations with means to share their own experiences, connect with friends/relatives, keep updated with situations and understand the public perception of events, places or individuals. With the availability of large datasets, a considerable challenge is how to quickly and efficiently consume such datasets. Visual Analytics solutions offer a promising direction of research for consuming large semantic datasets, providing authorities, citizens and organisations with means to quickly identify hidden trends, patterns and anomalies, explore and gather overview of large data spaces and quickly reach data points of interest. The VisLOD tutorial is arranged at ESWC2014 to bring together researchers and practitioners interested in visual and interactive techniques for exploring Linked Open Data and Social Media for e-Governance. The hands-on tutorial will cover technical aspects from two perspectives: Social Media analysis and Visualisation of Social Media and Linked Data.

The demand to access large amounts of heterogeneous structured data is emerging as a solid trend for many applications and users on the Web. However, the effort involved in finding and querying heterogeneous and distributed third-party data sources on the Web can create barriers for data consumers. At the core of this problem is the vocabulary gap between the way users express their information needs and the data representation. Question Answering (QA) approaches over Linked Data provide principled and multidisciplinary solutions to cope with the growing semantic heterogeneity of databases, merging elements from natural language processing, information retrieval and databases. The study of existing approaches for QA over Linked Data can provide key insights on how future applications and users will cope with increasing data variety. In this tutorial we will provide a comprehensive introduction and description of the state-of-the art for Question Answering (QA) approaches over Linked Data. The tutorial will cover emerging challenges & trends in the database landscape (Big Data & Linked Data), aligning how QA principles and methods can be used to address these challenges. The core terminology and concepts in the area, and the components of QA approaches will be introduced. The semantic assumptions behind QA systems will be examined under the Computational Linguistics perspective and the Semantic Web perspective, followed by the description of state-of-the-art approaches for QA over Linked Data (Lopez et al. (2006), Cimiano et al. (2007), Damljanovic et al. (2010), Freitas et al. (2012), Unger et al. (2012), Cabrio et al. (2012), Pradel et al. (2013). IBM Watson (Ferrucci et al. (2010)) will also be analyzed as a case study. The methodologies and existing test collections for evaluating QA over Linked Data systems will be covered. After the analysis of existing approaches, relevant semantic patterns used in the construction of QA systems, which can be used in other application scenarios, are analyzed. Finally, a roadmap for the research in the field based on the analysis of the literature will be covered.

The tutorial provides a comprehensive view of the RDF-Stream Processing (RSP) research area. It consists of four parts. The first one introduces the RSP basic concepts: RDF streams to represent temporally-ordered sequence of data items; continuous SPARQL extensions to query RDF streams, and RSP engines to execute continuous query answering over RDF streams. The second part presents the available RSP engine implementations. It starts with an overview on the existing RSP engines, highlighting similarities and differences among them. Next, two existing implementations are analysed in depth: C-SPARQL and SPARQLstream. The third part is a hands-on session where the attendees learn how to (1) use the three presented RSP engines presented above and (2) let the systems interact among them. Finally, the fourth part of the tutorial provides an overview on RSP-related topics: RSP engine benchmarking, stream reasoning and real-world deployments. The tutorial closes with a discussion on the open challenges and the research problems of this research field.

The Web of Data is assisting to a growth of interest with respect to the open challenge of representing and reasoning in an automated way over licenses and copyright. In particular, publishing and consuming Linked Data require to be aware of the terms of reuse which can be applied to the data itself. This tutorial explains what every Linked Data publisher or consumer should know about intellectual property rights and Linked Data, and it gives an advanced knowledge for acquainted users. After this tutorial, the participants will have a knowledge of which Linked Data resources are protected by intellectual property rights, how to use the well- known licenses, how to write specific rights expressions and how to reason about the licensing terms to be associated to derivative or aggregated data. In addition to each theoretical session, a short hands-on session is scheduled.

Social networks generate major economic value and form pivotal parts of commercial services, advertisement, entertainment, etc. Multiple tools and technologies have emerged in the last few years that aim to monitor and analyse data from these networks in order to exploit their value. This tutorial aims to provide a comprehensive overview of where and how semantic information has been used to represent and analyse social networking data. The presented research and development covers different use cases and applications including education, e-government and business cooperation. With the help of hands on session attendees will make use of some of these technologies to collect and analyse data from popular social networking sites, such as Facebook or Twitter. Semantic technologies will be applied to perform topic and sentiment analysis over these data.

The Semantic Web has redefined itself throughout the last years as a Web of ‘Linked Data’, by establishing principles that support sharing of large datasets on the Web together with a technology stack – fundamentally based on the use of URIs, RDF, and SPARQL – aimed at facilitating these principles. The huge success and widespread adoption of the Linked Data approach has led to the availability of vast amounts of public data such as DBpedia, WordNet RDF or the data.gov.uk initiative. More recently, these approaches started to get adopted by education institutions, with Linked Data technologies being used to expose public information regarding course offerings, open educational resources and educational facilities in a readily accessible and reusable way. While the very nature of the Linked Data approach thus clearly offers promising solutions that can potentially transform education, it is not yet adopted widely within the educational field. The LinkedUp project is an FP7 Support Action that seeks to explore and exploit open and linked data for education. This includes data with an explicit educational purpose, as well as other data and information that may not have an explicit educational remit, but can usefully be applied to an educational context. We aim to organize a half-day workshop dedicated to the second competition on innovative and robust prototypes and demos for tools that analyse and/or integrate open web data for educational purposes.