- News
- Introduction
- Important Dates
- Accepted Contributions
- Programme
- Topics of Interest
- Pioneering the Linked Open Research Cloud
- Submissions
- Proceedings
- Organising Committee (in alphabetic order)
- Programme Committee
- Previous Workshops
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. Recently, Distributed Ledger Technologies (DLTs) have emerged as a novel way to manage and exchange digital assets among a large number of agents in a decentralised way, leading to a rethink of consensus algorithms. Distributed Ledgers may be one answer to the problems of trust and redecentralisation of the Web, for instance in the context of Linked Data. Conversely, Linked Data and Web technologies could help Distributed Ledger technologies for solving their very own challenges, like interoperability and querying. The workshop on Linked Data on the Web and its Relationship to Distributed Ledgers (LDOW/LDDL) aims to stimulate discussion and further research into the challenges of publishing, consuming, and integrating structured data from the Web, covering established topics of the Linked Data on the Web (LDOW) community. As this year’s edition represents the coming together of the established Workshop on Linked Data On the Web (LDOW) with Workshop on Linked Data and Distributed Ledgers we'll additionally address the question of how distributed ledgers could help towards solving some of these challenges, and how Linked Data technologies may help distributed ledgers to become more open and interoperable.
In alphabetical order
The timing for presentations and breaks at LDOW/LDDL is shown below.
Abstract: We can build impactful applications from the data locked up in web sites, stored in spreadsheets, or contained in databases by turning those sources into an integrated semantic network of data, called a knowledge graph. However, exploiting the available data to build knowledge graphs is difficult due to the heterogeneity of the sources, scale in the amount of data, and noise in the data. In this talk I will present our approach to building knowledge graphs, including acquiring data from online sources, extracting information from those sources, aligning and linking the data across sources, and building and querying knowledge graphs at scale. We have applied our approach, to a variety of challenging real-world problems including combating human trafficking by analyzing web ads, identifying illegal arms sales from online marketplaces, predicting cyber attacks using data extracted from both the open and dark web, and estimating potential threats in space by integrating the combination of structured and unstructured data on the web.
Bio: Craig Knoblock is Executive Director of the Information Sciences Institute of the University of Southern California (USC), Research Professor of both Computer Science and Spatial Sciences at USC, and Director of the Data Science Program at USC. He received his Bachelor of Science degree from Syracuse University and his Master's and Ph.D. from Carnegie Mellon University in computer science. His research focuses on techniques for describing, acquiring, and exploiting the semantics of data. He has worked extensively on source modeling, schema and ontology alignment, entity and record linkage, data cleaning and normalization, extracting data from the Web, and combining all of these techniques to build knowledge graphs. He has published more than 300 journal articles, book chapters, and conference papers on these topics and has received 7 best paper awards on this work. Dr. Knoblock is a Fellow of the Association for the Advancement of Artificial Intelligence (AAAI), a Fellow of the Association of Computing Machinery (ACM), past President and Trustee of the International Joint Conference on Artificial Intelligence (IJCAI), and winner of the Robert S. Engelmore Award.
Abstract: For too long the world has assumed that an individual must have their identity defined by, and controlled by, someone else. This centralization assumption, whether it comes from governments or from for-profit corporations, has led to almost continuous reports of privacy breaches or abuses around the world. There is a better way: Verifiable Credentials (VCs) and Decentralized Identifiers (DIDs). In this talk Dr. Daniel Burnett, Co-chair of the VC Working Group at W3C, will show how a bottom-up web of trust built on credentials gives the power back to individuals and organizations to reduce centralization as much as is needed for their particular use cases. With strong support for JSON-LD, both technologies take full advantage of user-definable and -extensible data vocabularies.
Bio: Dr. Daniel Burnett has been at the forefront of key Web and Internet standards for two decades now. Dan has a reputation for rapidly becoming a known expert in each field he enters, as author/editor of a dozen specifications, chair or co-chair of multiple working groups in W3C and IETF, co-author of the most popular book on WebRTC, past Chairman of the Board of the VoiceXML Forum, and currently a Director of the IEEE-ISTO. Although Dan began his career with a Ph.D. in Speech Recognition technology, his career has taken him from Southwestern Bell and Nuance through Voxeo, Tropo, his own standards consulting business, and now ConsenSys, in the PegaSys standards group. He is very excited to be working on standards in the blockchain space. As a co-editor of the Verifiable Credentials Data Model specification and a co-chair of the Verifiable Claims Working Group at W3C, Dan is committed to realizing the vision of self-sovereign identity.
Topics of interest for the workshop include, but are not limited to, the following:
Integrating Web Data from Large Numbers of Data SourcesProblem: The LOD Cloud contains minimal information about the research output from Web Science, Semantic Web, and Linked Data venues (including, a decade on, our very own LDOW workshop). Moreover, our interactions with these publications are static, and not very social. Simply put, we are not taking full advantage of what the Web enables us to do, let alone applying our own tools and standards to publish, consume, or enhance the output. Challenge: What if we were to semantically capture the core parts of our research at a granular level, and offer user interactions and participation? Could this help to improve our work, and bring the community to new levels of understanding, and increase usage of tools and techniques? What if we were able to search or query for these parts? We might be able to answer questions such as: "Which scholarly articles are relevant to my research?", "What is the hypothesis of a given article?", "Which other researchers might find my results/output directly useful?", "What new ways are there to cluster related research together?", "Is there a research gap on a topic of interest?" Proposal on how to proceed: Progress has been made with regards to gathering and using metadata (eg., author names, article titles, year, abstract) - see the Semantic Web Dogfood / ScholarlyData - but we need to take this to a new level. We strongly promote self-dogfooding, encouraging authors to demonstrate that they use Semantic Web tooling or techniques in their own practice. We also promote decentralisation and data ownership, and encourage participants to share their contribution by publishing a document at a domain they control or consider sufficiently authoritative (e.g., a university webpage), and sending us the URL. Reviews will be based on a persistent copy of the URL’s contents e.g., from an archive.org snapshot of the article at the submission deadline. See Submissions below for more information. We encourage all research contributions (articles and reviews) to be part of the Linked Open Research Cloud (LORC). Check it out!
We seek the following kinds of contributions:
Submissions in pdf should adhere to the ACM format published in the ACM guidelines , selecting the generic “sigconf” sample. Note however, that contrary to the WebCof Research Papers guidelines that the author list does not need to be anonymized, as we do not operate a double-blind review process. The formatting is a requisite for being able to publish the paper in the companion volume of the Web Conference proceedings.
We also encourage authors to submit and publish their contributions according to the Linked Research principles and the Linked Open Research Cloud initiative. For this authors can use dokieli - a decentralized authoring and annotation tooling. Authors may submit to EasyChair either an URL to their paper (in HTML+RDFa, CSS, JavaScript etc.) with supporting files, or an archived zip file including all the material. However, note that in case of acceptance, the paper will need to be formatted in .pdf according to ACM rules if the authors wish to see it published in the proceedings.
Please submit your work through EasyChair
LDOW/LDDL encourages open peer review, and recommend that reviewers are named and attributed; however reviewers may be anonymous if so desired. Reviewers are welcome to publish their reviews using the same guidelines as the research articles.
All contributions will be archived at Internet Archive. Accepted contributions will be presented at the workshop and included in the CEUR workshop proceedings. At least one author of each article is expected to register for the workshop and attend to present their contribution.
Accepted contributions will be made available on this website or linked to canonical and archived URLs. We also aim at publishing them in the Companion Volume of the Web Conference.