Introduction

Computer applications generate computerized data at very high rates. This requires to confront such growth with new technologies to be developed for both hardware and software.

In the early days of the computer era, data files and data stores were enough to perform required tasks on data. Later on, relational databases, distributed databases, and database management systems needed to be developed. Data management was separated from applications, and it required full-time administration and maintenance apart from software. Organizations started new departments for developing information technologies (IT) [105].

As organizations and businesses grew, so did the need to automatize business transactions and exchange data among them. Dependency on external data enforced standardization in data communications and exchange. National and international standards bodies developed new standards allowing data exchange over private networks inside and among organizations and businesses. Computing and storage capabilities of personal computers (PCs) on employees’ desktops increased as PCs gained power leading to client/server applications being developed. Data was distributed over networks, making data design and management more complicated.

Popularity of the Internet in 1990s further helped small businesses, individuals, and academic organizations around the world to communicate through public networks. This created a giant open digital library and opened millions of potential businesses to commerce.When data became available in massive amounts, IT managers were caught unprepared. Tannenbaum [105] sees the reason in not paying attention to metadata and metadata solutions. According to her, IT departments were so overwhelmed by massive data flow and maintenance that they ignored the fact that individual departments started to develop their own information technologies. Tannenbaum defines information as processed data in any form that assists a decision maker, and she claims it is the IT crews’ job to provide such information to departments.

Metadata Solutions
XML as a Modeling Language
    Extensible Markup Language (XML)
    Structured Documents
    Freedom in Language Design
    Language for Specifications
    Configuration
    Data Presentation
    Communication
    Data Persistence
    Document and Object Modeling
    Summary
Metadata Models for the web
    Attribute-Value Pairs and The Dublin Core
    Metadata Statements and RDF
    Schema-based Structured Models
    Summary
Metadata Repositories
    Related Work
    Metadata Models
    Naming and Discovery Services
    Authoring, Generation, and Rendering of Metadata
    Metadata Persistence
    Metadata Queries 
Summary