Visualization of semantic metadata and ontologies

Composition of software applications from component parts in response to high-level goals is a long-standing and highly challenging goal. We target the problem of composition in flow-based information processing systems and demonstrate how application composition and component development can be facilitated by the use of semantically described application metadata. The semantic metadata describe both the data flowing through each application and the processing performed in the associated application code. In this paper, we explore some of the key features of the semantic model, including the matching of outputs to input requirements, and the transformation and the propagation of semantic properties by components.

Download Full-text

Ontology Supported Automatic Generation of High-Quality Semantic Metadata

On the Move to Meaningful Internet Systems 2006: CoopIS, DOA, GADA, and ODBASE - Lecture Notes in Computer Science ◽

10.1007/11914853_48 ◽

2006 ◽

pp. 791-806 ◽

Cited By ~ 1

Author(s):

Ümit Yoldas ◽

Gábor Nagypál

Keyword(s):

Automatic Generation ◽

High Quality ◽

Semantic Metadata

Download Full-text

Semantic Framework for an Efficient Information Retrieval in the E-Government Repositories

Advances in Electronic Government, Digital Divide, and Regional Development - Handbook of Research on Democratic Strategies and Citizen-Centered E-Government Services ◽

10.4018/978-1-4666-7266-6.ch011 ◽

2015 ◽

pp. 192-213

Author(s):

Antonio Martín ◽

Carlos León

Keyword(s):

Case Based Reasoning ◽

Use Case ◽

Digital Collections ◽

Distributed Information ◽

Semantic Framework ◽

Semantic Metadata ◽

Common Framework ◽

Efficient Information ◽

New Form ◽

Semantic Search Engine

An enormous quantity of heterogeneous and distributed information is stored in e-government repositories. Access to these collections poses a serious challenge, however, because present search techniques based on manually annotated metadata and linear replay of material selected by the user do not scale effectively or efficiently to large collections. The artificial intelligence and Semantic Web provide a common framework that allows knowledge to be shared and reused in an efficient way. This chapter proposes a comprehensive approach for discovering information objects in large digital collections based on analysis of recorded semantic metadata in those objects and the application of expert system technologies. The authors suggest a conceptual architecture for a semantic search engine. They use case-based reasoning methodology to develop a prototype. OntoloGov is a collaborative effort that proposes a new form of interaction between citizens and e-government repositories, where the latter are adapted to users and their surroundings.

Download Full-text