The quantity of published Linked Data continues to increase. However, applications that consume Linked Data are not yet widespread. Reasons may include a lack of suitable methods for a number of open problems, including the seamless integration of Linked Data from multiple sources, dynamic discovery of available data and data sources, provenance and information quality assessment, application development environments, and appropriate end user interfaces. Addressing these issues requires well-founded research, including the development and investigation of concepts that can be applied in systems which consume Linked Data from the Web. Our main objective is to provide a venue for scientific discourse (including systematic analysis and rigorous evaluation) of concepts, algorithms and approaches for consuming Linked Data.
The workshop will be co-located with the 15th International Semantic Web Conference (ISWC) in Kobe, Japan.
The term Linked Data refers to a set of foundational principles for publishing and interlinking structured data on the Web. After Linked Data was first proposed in 2006, a grass-roots movement, led by the Linking Open Data project, started to publish and to interlink multiple open databases on the Web following the proposed principles. Due to conference workshops, tutorials and general evangelism, an increasing number of data publishers – such as the BBC, Thomson Reuters, The New York Times, the Library of Congress, BestBuy, Getty, the US and UK government – have since adopted this practice. This ongoing effort resulted in bootstrapping the “Web of Linked Data” which, today, comprises of billions of RDF triples and millions of RDF links between datasets. The published datasets now include data about books, movies, music, radio and television programs, reviews, scientific publications, genes, proteins, diseases, medicine and clinical trials, geographic locations, people, statistical and census data, companies, and many more topics besides.
All of these published datasets are openly available on the Web in standardised interoperable formats, which presents novel opportunities for the next generation of Web-based applications: data from different providers can be aggregated, allowing fragmentary information from multiple sources to be integrated so as to achieve a complementary and more complete view. While a few applications, such as the BBC music guide have used Linked Data to significant benefit, the deployment methodology has been to harvest the data of interest from the Web to create a private, disconnected repository for each specific application. Such “harvesting approaches” are typically only feasible for vertical applications tied to specific datasets, incur a high up-front cost, and are insensitive to updates in the original data-sources. New concepts for consuming Linked Data – that do not require up-front harvesting of all sources – are required to lead the Web of Linked Data to its fullest and most general potential. The concepts, patterns, and tools necessary are very different from situations where relevant resource identifiers are known a priori, where queries can be run over complete local repositories, where access to the repository is reliable and cheap, and where relevant data sources are known to be trustworthy.
Open issues include (but are not limited to) a lack of approaches for seamless integration of Linked Data from multiple sources, for dynamic, on-the-fly discovery of available data, for information quality assessment, for querying and caching dynamic remote sources, and for implementing appropriate end-user interfaces.
These open issues can only be addressed appropriately when they are conceived as research problems that require the development and systematic investigation of novel approaches. The 7th International Workshop on Consuming Linked Data (COLD 2016) aims to provide a platform for the presentation and discussion of such approaches. Our main objective is to attract submissions that present scientific discussion (including systematic evaluation and/or formal results) of broadly-applicable concepts and approaches.
While previous editions of the workshop have attracted a number of submissions that addressed topics related to (RDF and) Linked Data management in general, with COLD 2016 we aim to continue steering the workshop back towards the aforementioned core goals. To this end, we explicitly seek submissions that address research problems related to at least one of the following two aspects of Linked Data consumption:
In the context of these two aspects of Linked Data consumption, relevant topics for COLD 2016 include but are not limited to:
We seek novel technical research papers in the context of consuming Linked Data with a length of up to 12 pages.
All submissions must be in English. Paper submissions must be formatted in the style of the Springer Publications format for Lecture Notes in Computer Science (LNCS).
We accept submissions in PDF but also encourage submissions in HTML. In the latter case, you should submit a ZIP archive containing all of the necessary files. If you are new to HTML submissions, you may find the following useful:
Please note that independently of the format used, we require articles to be submitted in LNCS format and to abide by the permitted font sizes, font selection, margins, etc., irrespective of the format used. This is to ensure visual consistency of the proceedings as well as to have comparative page limits. Submissions not conforming to the LNCS format or papers that are exceed the page limit will be rejected without review.
Please submit your paper via EasyChair at https://easychair.org/conferences/?conf=cold2016
The author list does not need to be anonymised since we do not have a double-blind review process. Submissions will be peer reviewed by three independent reviewers. Accepted papers have to be presented at the workshop to be published in the proceedings. Proceedings will be published online at CEUR-WS.
The workshop proceedings are online as CEUR-WS Vol-1666.
Session 1: Welcome and Keynote (09:00–10:30)
Session 2: Research Track (11:00–12:30)
Session 3: Linked Data Debate (14:00–15:30)
Session 4: Linked Data Panel, Town Hall, Conclusion (16:00–17:30)
COLD Beers (Evening)
It's been 10 years since the introduction of the Linked Data principles, and even though there have been outstanding advances, the dream of "querying the web as if it were a giant database" is still far from being realised. Facing different opinions from "we just need faster connections" to "it is impossible to do it", my personal impression is that the community has been slow in recognising the enormous potential for interesting and challenging problems brought forward by the idea of treating the web as a database.
This talk will be mostly focused on the algorithmic aspects of querying Linked Data, emphasising that, despite the efforts of this community and this workshop, there is still much work to do. More interestingly, many of the problems we face are completely novel in computer science, requiring fresh ideas and bringing techniques from other neighbouring areas. As an example, I will describe our recent efforts in using AI search techniques for querying Linked Data, especially when facing navigational queries. Finally, we will make a case that these problems are not only confined to the world of Linked Data; on the contrary, the technologies we develop can be used in other contexts.
Juan is an assistant professor at the Computer Science Department at Pontificia Universidad Catolica de Chile and an associate investigator of the Chilean Center for Semantic Web Research. He received his PhD from the University of Edinburgh in May, 2013. His research interests are in data management and automata theory. He was the recipient of the Ramon Salas Award for the best Chilean work in engineering and the best paper award for the ACM-PODS conference in 2011. In 2014 he won the BCS distinguished dissertation competition and received the Cor Baayen Award from ERCIM, the European Research Consortium for Informatics and Mathematics. He has served on the program comittees of various conferences and workshops, including SIGMOD and AAAI.
The Linked Data principles, as described by Tim Berners-Lee, recently passed their decade anniversary. By some accounts, the glass is half full: Linked Data has been a huge success and enjoys healthy adoption. By other accounts, the glass is half empty: Linked Data has failed to live up to its original promise by a wide margin. But by all accounts, the glass could be more full.
Within the community, there is a natural tendency to see the glass as half full, at least when we are not too busy solving low-level technical topics and writing papers.
The goal of this session will be to take a step back and to try to view the glass as being half-empty, to try to understand why that might be, to see what challenges need to be addressed, what unforeseen problems have arisen from the adoption of the past 10 years, and what is holding us back from further success.
We will invite a selection of experts to foment debate on these topics. In particular, in the style of a debate, we will ask each expert to argue the position that, Linked Data, as it is current stands, is doomed to fail. After stating their position, the expert will then debate their position with the audience. Each expert will thus act as a devil's advocate. They will argue as convincingly as possible a critical stance against Linked Data, regardless of their own position on the topic. It will be the role of the audience to defend Linked Data, if they so choose.
For further information about the workshop, please contact the workshops chairs at firstname.lastname@example.org
COLD 2016 is the seventh edition of the Consuming Linked Data workshop series. Previous editions include COLD 2015, COLD 2014, COLD 2013, COLD 2012, COLD 2011, and COLD 2010.