BBY 464 Semantic Information Management (Spring 2016) Data and Metadata Management Yaşar Tonta & Orçun Madran [yasartonta, Hacettepe University Department of Information Management

Semantic Web

Web 3.0 = Web Semantic Web Social semantic Web Meaning Locating and fusing information automatically Performing basic reasoning Source: Mark Greaves, Peter Mika. Semantic Web and Web 2.0, In J. Web Sem., 6(1):1-3, 2008Peter MikaSemantic Web and Web 2.0

Metadata Structured description for all types of information resources Tagging (web content) Metadata is – artificial (no metadata in the nature) – Constructive (can be used to solve problems) – Actionable (can be used to meet some info needs) Source: Glushko, 2013

Metadata Artificial Constructive Actionable

DNA Metadata Source: Coyle, 2010

Comparing fields Source:

MARC to DC Crosswalk Source:

XML-RDF Converter

Chapter 3/14 Copyright © 2004 A Data Modeling Process Steps in the data modeling process – Plan project – Determine requirements – Specify entities – Specify relationships – Determine identifiers – Specify attributes – Specify domains – Validate model

Chapter 3/15 Copyright © 2004 Validating Model Data model is a model of humans’ models, not a model of reality A data model is wrong if it does not accurately reflect the ways the users think about their world Data models are validated through a series of reviews – Normally, a team review is followed by user reviews E-R model as well as prototypes of forms and reports may be used to communicate to users features of the data model

Chapter 2/16 Copyright © 2004 E-R Model Entity-Relationship model is a set of concepts and graphical symbols that can be used to create conceptual schemas Four versions – Original E-R model by Peter Chen (1976) – Extended E-R model: the most widely used model – Information Engineering (IE) by James Martin (1990) – IDEF1X national standard by the National Institute of Standards and Technology – Unified Modeling Language (UML) supporting object-oriented methodology

Chapter 2/17 Copyright © 2004 Example: E-R Diagram

Chapter 2/18 Copyright © 2004 Binary Relationships 1:1 1:N N:M

Chapter 3/19 Copyright © 2004 Example: Identifying Connection Relationships

Chapter 3/20 Copyright © 2004 Example: University System

Chapter 2/22 Copyright © 2004 IDEF1X Standard IDEF1X (Integrated Definition 1, Extended) was announced as a national standard in 1993 It defines entities, relationships, and attributes in more specific meanings It changed some of the E-R graphical symbols It includes definition of domains, a component not present in the extended E-R model Four Relationship Types – Non-Identifying Connection Relationships – Identifying Connection Relationships – Non-Specific Relationships – Categorization Relationships Products supporting IDEF1X: ERWin, Visio, Design/2000

Chapter 2/23 Copyright © 2004 Example: IDEF1X

Chapter 2/24 Copyright © 2004 UML-style E-R Diagrams The Unified Modeling Language (UML) is a set of structures and techniques for modeling and designing object-oriented programs (OOP) and applications The concept of UML entities, relationships, and attributes are very similar to those of the extended E-R model Several OOP constructs are added: – indicates that the entity class exist in the database – UML allows entity class attributes – UML supports visibility of attributes and methods – UML entities specify constraints and methods in the third segment of the entity classes Currently, the object-oriented notation is of limited practical value

Chapter 2/25 Copyright © 2004 Example: UML

Chapter 2/26 Copyright © 2004 Example: UML

Chapter 2/27 Copyright © 2004 Example: UML

Database

Dictionary for a Database

Object Relational Database

ER & OO Schemas

Dictionary for an ER Model

Dictionary for an OO Model

Four parts of dictionary

Supermodel in the metalevel directory

Description of some models in the dictionary

Model-generic dictionary based on supermodel

Semantic Web – Layered Architecture