OWL Representing Information Using the Web Ontology Language.

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Presentation transcript:

OWL Representing Information Using the Web Ontology Language

Section 1

Chapter 1: Historical Web ▫Web history, context, features, & shortcomings Chapter 2: Semantic Web ▫Challenges, requirements, & solutions Chapter 3: Ontologies ▫Concepts, purposes, relationships, features, & languages Chapter 4: OWL Introduction ▫OWL language, layered architecture, & supporting technologies

Chapter 1

1 Current Web Publishing medium Dominated by HTML ▫Hyper Text Markup Language Pages accessible using URLs ▫Uniform Resource Locators ▫ Supports human readers using browsers

1.1 Current Web History Internet infrastructure created by DARPA Mostly text-based (telnet, ftp, gopher) 1992: Tim Berners-Lee/CERT developed ▫HTML & HTTP (Hyper Text Transfer Protocol) ▫Web browser (Mosaic) Allows anyone to publish structured documents connected by hyperlinks Combined with TCP/IP and XML (eXtensible Markup Language) to create “killer app”

1.2 Current Web Characteristics Features Benefits Applications

1.2.1 Current Web Features Diverse Document-centric Virtual repository of information No controlling authority Managed by open standards from W3C ▫World Wide Web Consortium Intended for human access & reading

1.2.2 Current Web Benefits Superior to private networks Transactions are cheaper (self-service) Cheap to communicate world-wide Created online communities ▫Open-source movement – free high-quality tools ▫Countless online forums

1.2.3 Current Web Applications Most content designed for humans Variety of purposes ▫E-commerce ▫Education ▫Financial services ▫Auctions ▫Music Many sites use generated HTML & XML generated from databases

1.3 The Web is Not Enough Not enough structure to support computer processing of content No way to connect information to enable complex queries HTML too focused on format/display Need to add markup to explain meaning (semantics) Semantics will enable automated interpretation of structured web content

1.3.1 Information Structure HTML documents ▫Semi-structured formatting ▫Unstructured text Natural Language Processing (NLP) ▫Improving, but impractical on a large scale Structured database information must be shared in a computer-parseable maner Goal: allow automated software agents to mine the web, creating new functionality

1.3.2 Finding Requires Metadata  “Find the cheapest Key lime pie within 5 miles.” Keyword-based search engines ▫Find pages that might contain desired content ▫Don’t provide answers to questions…the goal! ▫Have to find local restaurants, then look at their menus Query engines aim to answer questions ▫Should be able to filter restaurants within 5 miles, access menus, compare prices, get answer ▫Show how answer gotten from reliable sources

1.3.3 Semantics Must Be Explicit Providing semantic information explicitly in documents enables software to: ▫Manipulate information (filter, summarize) ▫Infer new facts (inference) ▫Link multiple distributed information representations (semantic join)

1.4 Current Web Summary Current Web ▫Document-centric ▫Focused on humans using browsers ▫Insufficient for automated data processing New technologies needed ▫Structure information for automated processing ▫Improve searches ▫Link disparate data sources with each other The Semantic Web!

Chapter 2

2 Semantic Web Introduction Web information representation challenges Requirements for a solution Semantic Web concepts that satisfy those requirements

2.1 Web Information Representation Challenges Increased Need for Information Representation Ambiguous Human Descriptions Software Demands for Specificity

2.1.1 Information Representation Volume of information increasing exponentially User expectations of the Internet also growing To satisfy expectations, we need more than just HTML, XML & databases

2.1.2 Ambiguous Descriptions Many human information formats ▫Specialized domains with unique terminology ▫Regional language differences ▫Many sublanguages within communities ▫Difficult to get consensus Language agreement impossible Meta-language agreement possible ▫Language to express language We need a language that can represent information from many domains

2.1.3 Demands for Specificity Computers need information to be ▫Structured ▫Consistent ▫Well-formed ▫Logical

2.2 Requirements for a Solution Minimize Human Investment Satisfy Computer Requirements Compromise between these goals

2.2.1 Minimize Human Investment Information Representation Producers Information Representation Consumers Requirements common to both

Representation Producers Provide content from existing sources Aim to generate information representations ▫Quickly ▫Effectively ▫Inexpensively Represent data using natural models that are ▫Extendable ▫Versionable ▫Configuration-managed

Representation Consumers Aim to create software to ▫Parse information ▫Interpret information ▫Manipulate information Software should be able to ▫Combine information from different domains ▫Use others’ data without needing to understand the underlying data model ▫Reduce human intervention

Semantic Web  Download Eclipse  Download Java  Create a Model using Java and Jena.  Write one statement to Jena's Model  Write the statement in the model to output. Setup for The Course

Semantic Web  Use ant and Junit to run projects.  Optionally use Eclipse for development.  Show all projects as Junit tests.  Have Fun. So You Will be Expected to: