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KR on the Web
Rinke Hoekstra and Stefan Schlobach
KR on the Web Pitch Slides by Rinke Hoekstra, licensed under a Creative Commons Attribution 4.0 International License.
Thanks to: These slides are based on decks by Stefan Schlobach, Frank van Harmelen, Paul Groth, Laura Hollink, Antonis Loizou, Ronald Siebes, and the "Semantic Technologies" course at the University of Oslo.
[email protected]@vu.nl
What is Knowledge Representation?Represent information about the world in a form that a computer system can use to solve complex tasks
Formalisms guided by how humans solve problems and represent knowledge
Incorporate findings form logic to automate various kinds of reasoning
What is Knowledge Representation?Represent information about the world in a form that a computer system can use to solve complex tasks
Formalisms guided by how humans solve problems and represent knowledge
Incorporate findings form logic to automate various kinds of reasoning
Traditional KR deals with relatively small, curated knowledge bases
The Web as a Ginormous Knowledge Graph?
From: https://www-01.ibm.com/software/data/bigdata/images/4-Vs-of-big-data.jpg
Overview - KR on the Web
• Study the implications of veracity, variety and volume for KR on the Web
• Organisation:
• Invited lectures by key people from research & industry
• Literature groups prepare & present for invited lectures
• Project groups write “conference papers” on each theme (milestones).
• Related courses are Knowledge Representation, and Knowledge Engineering, and Semantic Web
Preliminaries - A “systems paper”
• Learn how to use the technologies for KR on the Web
• Learn about the formal semantics of KR languages for the Web
• Convert existing datasets to Linked Data
• Define models at different levels of expressiveness over the data
• Query the data, and use a reasoner to infer new knowledge
• Build a simple web-application that shows it all.
4. Laptop Lectures are hands-on sessions where students are familiarizedwith the tools and techniques of KR on the web (bring your own laptop!).
5. EHBO Lectures where students work on the practical assignments andcan ask feedback and help on the choices they make.
Every module ends with the submission of a milestone, a research paper thatdescribes and defends the work done over two weeks.
The papers are written and prepared by the project groups, and are based onthe work done by the two students in that group.
The papers are to be submitted to EasyChair for peer review (see Evaluation& Grading below).
The papers should be accompanied by a proof that the reported work hasbeen done (as is customary in academic peer review). This proof is typically inthe form of a link to the dataset, model, code or working system that isreported on.
These assignments are (in short):
1. Milestone 1 - Systems Paper
A paper (8 pages, Springer LNCS style) that describes a live Semantic Websystem, its use case and potential benefits, the datasets used and how theywere converted, a formal model for the data and interesting queries over thedata.
1. Milestone 2 - Data and Ontology Track Paper
A paper (8 pages, Springer LNCS style) that convincingly argues why themodel and data are correct (for the envisioned purpose), shows that they areevaluated using state-of-the-art methods (quality, suitability), compared toother data, and that it follows best practices.
1. Milestone 3 - Ontology Matching Paper
3. Assignments
Milestones
Veracity - A “data & ontology” paper
• What is the best model & level of expressiveness for your data?
• Quality measures of model and data
• Prevent ambiguity, safeguard trust (where does the data come from?)
• Maximise findability, understandability and reusability
• Follow best practices for data publication
4. Laptop Lectures are hands-on sessions where students are familiarizedwith the tools and techniques of KR on the web (bring your own laptop!).
5. EHBO Lectures where students work on the practical assignments andcan ask feedback and help on the choices they make.
Every module ends with the submission of a milestone, a research paper thatdescribes and defends the work done over two weeks.
The papers are written and prepared by the project groups, and are based onthe work done by the two students in that group.
The papers are to be submitted to EasyChair for peer review (see Evaluation& Grading below).
The papers should be accompanied by a proof that the reported work hasbeen done (as is customary in academic peer review). This proof is typically inthe form of a link to the dataset, model, code or working system that isreported on.
These assignments are (in short):
1. Milestone 1 - Systems Paper
A paper (8 pages, Springer LNCS style) that describes a live Semantic Websystem, its use case and potential benefits, the datasets used and how theywere converted, a formal model for the data and interesting queries over thedata.
1. Milestone 2 - Data and Ontology Track Paper
A paper (8 pages, Springer LNCS style) that convincingly argues why themodel and data are correct (for the envisioned purpose), shows that they areevaluated using state-of-the-art methods (quality, suitability), compared toother data, and that it follows best practices.
1. Milestone 3 - Ontology Matching Paper
3. Assignments
Milestones
Variety - An “ontology matching” paper
• How to algorithmically integrate data with that of others?
• Identity reconciliation: what entities are the same? What does identity mean?
• Ontology alignment: what concepts and relations are the same?
• How do these integrations affect your own model and data?
• What new use cases can we cover?A paper (8 pages, Springer LNCS style) that describes, motivates andevaluates the methods and algorithms used to extend the data and model withexternal data (from other students or from the LOD cloud).
1. Milestone 4 - Reasoning Track Paper
A paper (8 pages, Springer LNCS style) in which students, based on ananalysis of the data, describe, motivate and evaluate a reasoner thatimplements (part of the) standard Semantic Web entailments over their data.
For each of the Milestones there will be a separate folder on Blackboard,containing a more detailed description of the task (see also the respectiveLatex templates) as well as some example papers from recent majorconferences in the field.
Spread across the course there are 5 literature sessions, near the end of eachmodule. Topics studied are related to the guest lecture that will follow the weekafter.
Two groups of 3 students will each prepare a 45 minute discussion on apaper. These groups are not the same as the project groups.
The papers should be read by everyone, and participation in the literaturegroup session is mandatory.
Everyone should post questions/comments to this Google Drive inadvance, to help prepare the discussion.
The final grade is determined by three factors:
1. The four submitted research papers (milestones), each accounting for20% of the final grade (a total of 80%).
2. The preparation of and participation in a literature session, accounting for10% of the final grade.
Literature Groups
4. Evaluation & Grading
Volume - A “reasoning track” paper
• Knowledge graphs as complex system
• How does volume affect our ability to query and reason over the data?
• What complex system properties does the data display?
• Can we exploit the structure of the graph to guide computation?
A paper (8 pages, Springer LNCS style) that describes, motivates andevaluates the methods and algorithms used to extend the data and model withexternal data (from other students or from the LOD cloud).
1. Milestone 4 - Reasoning Track Paper
A paper (8 pages, Springer LNCS style) in which students, based on ananalysis of the data, describe, motivate and evaluate a reasoner thatimplements (part of the) standard Semantic Web entailments over their data.
For each of the Milestones there will be a separate folder on Blackboard,containing a more detailed description of the task (see also the respectiveLatex templates) as well as some example papers from recent majorconferences in the field.
Spread across the course there are 5 literature sessions, near the end of eachmodule. Topics studied are related to the guest lecture that will follow the weekafter.
Two groups of 3 students will each prepare a 45 minute discussion on apaper. These groups are not the same as the project groups.
The papers should be read by everyone, and participation in the literaturegroup session is mandatory.
Everyone should post questions/comments to this Google Drive inadvance, to help prepare the discussion.
The final grade is determined by three factors:
1. The four submitted research papers (milestones), each accounting for20% of the final grade (a total of 80%).
2. The preparation of and participation in a literature session, accounting for10% of the final grade.
Literature Groups
4. Evaluation & Grading
• Expose traditional KR to the idiosyncrasies of the Web
• Combine research themes from Big Data with semantics and KR
• Learn about state-of-the-art research in this field
• Learn how to do your own state-of-the-art research
• Discuss, engage, and communicate your work
Rinke Hoekstra and Stefan Schlobach
Summary - KR on the Web
• Expose traditional KR to the idiosyncrasies of the Web
• Combine research themes from Big Data with semantics and KR
• Learn about state-of-the-art research in this field
• Learn how to do your own state-of-the-art research
• Discuss, engage, and communicate your work
Rinke Hoekstra and Stefan Schlobach
Summary - KR on the Web
