Software Services Registry

The registry was created and is supported by the Institute of Communication and Computer Systems (ICCS) of the School of Electrical and Computer Engineering (ECE) of the National Technical University of Athens (NTUA).

The study and development of the software registry of services related both to the collection of metadata in an interoperable way, and to the semantic search and response to users’ questions, were produced in the context of the “DARIAH-ATTIKI National Digital Infrastructure for Research in the Arts and Humanities DYAS” project.
This project included the following studies:
Metadata mapping, collection and interoperable content management systems
This study describes the basic metadata schemas and ontologies used to represent content provider data, as well as the common model used within Europeana to which all heterogeneous content provider metadata schemas are mapped. It focuses on the collection and management of metadata, describing cultural artifacts from content providers, in an interoperable way, with the aim of providing advanced semantic search and response services to users’ queries.
Technologies and platforms for semantic representation of knowledge in answering questions
This study examines a set of theoretical issues, technologies and systems related to the subject of semantic representation of knowledge and data.
Semantic enrichment of metadata using multimedia information and linked data
This study describes the methodology and algorithms that allow the semantic enrichment of metadata of cultural content with the simultaneous analysis of multimedia information, mainly visual and audio-visual material, to answer user queries, as well as the use of linked data.
It refers to the use of semantic knowledge representation to answer queries in digital libraries that also include multimedia content. Its purpose is to present the cutting edge technology in the development of systems that offer effective search and access to digital library content, textual and visual, combining semantic analysis of the descriptive metadata of this content with machine learning techniques applied to the visual part of the content.

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