ITKS5440 Semantic Web and Linked Data (5 op)

Sisältö

The course concerns the so called Top-Down (“Symbolic”) approach to AI, when AI is designed on the basis of data, information and knowledge, which is represented in a standardized way and suitable for automated machine processing and understanding, sharing, data and application integration, reuse, reasoning and inference, etc. This includes various aspects of Knowledge Representation and Reasoning, Data Tagging, Metadata Creation, Semantic Web, Linked Data, Ontology (i.e. Web-based shared knowledge) Engineering, etc.

This course includes an introduction and practical tutorial on the Semantic Web, ontology engineering; and also reviews some modern applications of these methods and techniques for Web-based intelligent applications and services. You will learn Semantic Web mission; concepts of semantic interoperability, integration and automation; concept of metadata and ontology; Semantic Web standards; RDF (Resource Description Framework); Linked Data; Ontology Engineering; OWL (Web Ontology Language); Rules for inferring knowledge; SWRL (Semantic Web Rules Language); Semantic Technology; Semantic (Web) Applications and Services. Course has 1 assignment (the basis for the grade) and no exam. Remote mode of study is possible. Some background info: The Semantic Web is originated from Semantic Computing which is an emergent field of Computing. It is a collaborative ongoing activity led by the World Wide Web Consortium (W3C) to promote common data formats on the World Wide Web specifically for machine-processable and machine understandable data aiming to convert the current web, dominated by unstructured and semi-structured documents, into a "web of data" (often referred as Web 3.0). The Semantic Web stack builds on the W3C's Resource Description Framework (RDF). Publishing machine-understandable data on the web is going as a mainstream. Linked Data (the activity originated from the Semantic Web vision) has seen explosive growth over the past few years. Linked Data assumes publishing structured data so that it can be interlinked with standard Web technologies such as HTTP, RDF and URIs, aiming to share information in a way that can be read automatically by computers. This enables data from different sources to be connected and queried. For example, DBPedia is a collection of data structured in RDF after being extracted from the Wikipedia, which allows Semantic Web-based applications to automatically infer implicit or new data and make advanced queries over the Wikipedia-derived dataset. The FOAF (Friend-of-a-Friend) is another example of how the Semantic Web attempts to make use of the data about people and their relationships within a social context. Organization of data based on RDF (graph) model makes it possible to connect data from distinct heterogeneous sources, organize and query huge volumes (Big Data challenge) of data. Ontologies are helpful to provide interoperability among various schemas used in the data and enable applications automatically discover and explore new previously unknown sources of data. Semantic-Web-standards-driven so-called Semantic Technology as a software technology allows the meaning of information to be known and processed at execution time of various applications making them naturally interoperable in the Web and within various digital ecosystems and clouds. Therefore as a summary: the Semantic Web is an evolving development of the World Wide Web in which the meaning (semantics) of information and services published on the Web and their inter-relationships are explicitly defined, making it possible for the Web-based software tools, agents, applications and systems to discover, extract and “understand” Web information resources and capabilities and automatically utilize it. Related to these, the Linked Data activity aims to expose, share, and connect distributed pieces of data, information, and knowledge; to extend the Web by publishing various open datasets and by setting semantic links between data items from different data sources. The Semantic Web vision assumes annotating Web resources with machine-interpretable descriptions (metadata) referred to shared conceptual vocabularies (Ontologies), and provides mechanisms for automated reasoning about them.

Suoritustavat

.Lectures and assignment

Arviointiperusteet

Research maturity, functional integrity and quality of the assignment

Knowledge on Semantic Web, Linked Data, Ontology Engineering standards, technology and tools; Capability to design Linked Data, Metadata and Ontologies; Skills to structure, query and integrate data and knowledge.

https://ai.it.jyu.fi/vagan/itks544.html