- News
- Introduction
- Important Dates
- Programme
- Topics of Interest
- Pioneering the Linked Open Research Cloud
- Submissions
- Proceedings
- Organising Committee
- 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.
The 11th Workshop on Linked Data on the Web (LDOW2018) aims to stimulate discussion and further research into the challenges of publishing, consuming, and integrating structured data from the Web as well as mining knowledge from the global Web of Data.
Social media hashtag: #LDOW2018
The timing for presentations and breaks at LDOW2018 is shown below.
In this new version of an old legend two brothers, linked data and semantics, had grown apart. One brother considered the simplicity and pragmatism of data publishing and reuse with minimal formal commitment to be the ultimate beauty. He feared and loathed the expressive power of rich semantics, which few people understand, and even fewer apply in reasonably correct ways. For his brother, though, few things were more beautiful than predictable inference based on formal entailment, and he felt constantly threatened by the beast of large scale messy linked data, a complex system few people understand, and even fewer apply in reasonably unambiguous ways.
In this talk, I will propose a rethink of formal semantics in order to combine the beauty of both paradigms. This means that the formal systems we usually apply to capture the meaning of data and knowledge on the Web need to be extended so as to also capture the often implicit intentions of the user. I will discuss some recent experiments we ran to better understand patterns in the data and how those could become part of novel formalisms to properly describe such social and pragmatic semantics. An crucial ingredient of this rethink is a strong empirical component of the approach, which in turn heavily depends on quick and seamless access to massive Linked Data. To this end we have developed the LOD Laundromat infrastructure which allows efficient (centralised) access to a massive subset of the Linked Data cloud.
Linked Data Next Steps
Topics of interest for the workshop include, but are not limited to, the following:
Web Data Quality AssessmentProblem: 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:
Articles can be formatted using HTML or PDF, however LDOW prefers HTML.
HTML based contributions: the use of Linked Data and interactive content is strongly encouraged. Publish your article on the Web, and send us the URL. For authoring along the lines of the Linked Research initiative, authors may want to use dokieli (see also source). There are a variety of examples in the wild. See the Linked Open Research Cloud for further details on how to make your article discoverable.
PDF based contributions: use the ACM SIG template.
Please share your work via EasyChair: https://easychair.org/conferences/?conf=ldow2018.
LDOW 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. They will also be published as a volume of the CEUR series of workshop proceedings.