Resources.
Presentations
Making Cities Smarter
The first video explores the problem of semantic interoperability in Smart cities. As the application of data analytics to urban problems grows, so has need for more and varied sources of data. One example, crime analysis in the City of Edmonton, uses over 200 data sets. As these data sets are often developed independently, they give rise to semantic interoperability problems. Semantic interoperability is the ability of computer systems to exchange data with unambiguous, shared meaning. While "wrangling" the data can certainly address some of the interoperability problems, there is another way. Ontologies provide a means of reducing semantic ambiguity and overlapping interpretations of data. This video will review the interoperability problem in smart cities, provide an introduction to the representation of knowledge, and applied ontologies. Topics covered in this video are:
1.Introduction to Smart Cities
2.Data Interoperability Problem
3.What is Knowledge Representation?
4.Introduction to Applied Ontologies
5.Reasoning with Applied Ontologies
Applied Ontologies
This video provides an in depth understanding of Description Logic, the language used by Artificial Intelligent to represent knowledge. The last part covers how applied ontologies are implemented on the World Wide Web as link data and the Web Ontology Language OWL. Topics covered in this video are:
1.Anatomy of a Concept Definition
2.Description Logic Terms and Roles
3.Description Logic Examples
4.Description Logic Individuals + Examples
5.Linked Data and SPARQL
6.OWL - Web Ontology Language
Building Ontologies
This video reviews the process used to construct Applied Ontologies. It describes each step taken to understand the problem requirements and how to design an Ontology to address them. Tools, such as Protege are reviewed, Topics covered in this video are:
1.Ontology Engineering Process
2.Building Ontologies with Protégé
3.Documenting Ontologies
4.Knowledge Graph Creation
Foundation Ontologies
This video reviews ontologies that represent concepts that are domain and application independent, and are found in most applications. The foundation concepts significantly reduce the time of ontology/data model design by providing “pre-packaged” solutions to representing foundational concepts. They also enhance interoperability when different application use the same foundational concepts. Topics covered in this video are:
1.Time
2.Change
3.Spatial
4.Measurement
5.Provenance
6.Activity
7.Organization
Common Impact Data Standard
This video introduces the Common Impact Data Standard (CIDS). The standard is part of the Common Approach to Impact Measurement created to bridge the tension between uniform and flexible approaches for social purpose organizations. Topics covered in this video are:
1.Six Dimension of Impact Measurements
2.CIDS Core Concepts: Impact Model Pattern, Outcome Pattern, Stakeholder Pattern, Impact Report Pattern
3.CIDS Fondation Layer
4.GCIO Indicator Pattern
5. Evaluation, Adoption, and Next Steps
Examples
This video reviews four applications of ontologies: 1) Measurement of city performance; 2) Impact modelling for social purpose organizations; 3) a COVID-19 decision support system; and 4) an ontology for integrating transportation planning related knowledge. Applications covered in this video are:
1.PolisGnosis Project - ontologies for measuring city performance
2.Common Impact Data Standard - an ontology for Impact Modelling of Social Services
3.Epidemic Management
4.iCity Project: Transportation Planning