A methodology for semantic qualification of schemas

The semantics of vocabulary elements use to be defined locally with scarce rigorousness and without consideration to shared definitions in other vocabularies, this approach produces a lack in the interoperability between resources. This document provides metadata vocabularies with a semantic map, articulated by a new qualifier set. The qualifier set is named semantic qualifiers, which permits to use semantics included in public reference resources. Moreover, a methodology is proposed. The solution improves previous initiatives concerning metadata management like Metadata Registries or other DCMI proposals. As example, the Dublin Core semantic qualification is carried out, making use of W3C-WordNet as reference ontology. In addition, this approach considers Modularity, Extensibility, Refining and Plurilinguistic criteria. A descriptive document is proposed with two views, one aimed to the user and an additional in RDF. The fields that would get benefits from the proposal are conceptual recovery of elements in the Semantic Web, the use of application profiles, and the friendlier use of vocabularies.

Metadata interoperability is a fundamental requirement for access to information within networked knowledge organization systems. The Harmony International Digital Library Project [1] has developed a common underlying data model (the ABC model) to enable the scalable mapping of metadata descriptions across domains and media types. The ABC model, described in [2], provides a set of basic building blocks for metadata modeling and recognizes the importance of 'events' to unambiguously describe metadata for objects with a complex history. In order to test and evaluate the interoperability capabilities of this model, we applied it to some real multimedia examples and analysed the results of mapping from the ABC model to various different metadata domains using XSLT [3]. This work revealed serious limitations in XSLT's ability to support flexible dynamic semantic mapping. In order to overcome this, we developed MetaNet [4], a metadata term thesaurus which provides the additional semantic knowledge which is non-existent within declarative XML-encoded metadata descriptions. This paper describes MetaNet, its RDF Schema [5] representation and a hybrid mapping approach which combines the structural and syntactic mapping capabilities of XSLT with the semantic knowledge of MetaNet, to enable flexible and dynamic mapping among metadata standards. 2. Definitions of Terms This section defines the key terms used throughout the remainder of the paper: Metadata-data about data-or more commonly "descriptive information about web resources". The use of standardized descriptive metadata can substantially improve the discovery and retrieval of relevant networked resources. Different communities or domains have developed their own standardized metadata vocaularies to meet their specific needs. Vocabularies-shared terminologies with commonly agreed-upon semantics for a domain. Common vocabularies enable search engines, agents, authors and users to communicate within a domain. Schemas-provide a standard way of defining standard domain-specific vocabularies by defining a common set of elements, their semantics and the relationships between the elements. Ontology-a formal description of the concepts, roles and relationships that exist for an agent or community of agents. Ontologies provide a shared and common understanding of a domain that can be communicated across people and applications, and play a major role in supporting information exchange and discovery. Thesaurus-the vocabulary of a controlled indexing language, formally organized so that the a priori relationships between concepts (for example "broader" and "narrower") are made explicit. [7] Metadata Thesaurus-a thesaurus (defined according to ISO 2788 standard for monolingual thesauri [7]) which defines the relationships between metadata terms from different domain vocabularies.

Lecture Notes in Computer Science, 2005

Ontologies have seen quite an enormous development and application in many domains within the last years, especially in the context of the next web generation, the Semantic Web. Besides the work of countless researchers across the world, industry starts developing ontologies to support their daily operative business. Currently, most ontologies exist in pure form without any additional information, e.g. authorship information, such as provided by Dublin Core for text documents. This burden makes it difficult for academia and industry e.g. to identify, find and apply -basically meaning to reuse -ontologies effectively and efficiently. Our contribution consists of (i) a proposal for a metadata standard, so called Ontology Metadata Vocabulary (OMV) which is based on discussions in the EU IST thematic network of excellence Knowledge Web 1 and (ii) two complementary reference implementations which show the benefit of such a standard in decentralized and centralized scenarios, i.e. the Oyster P2P system and the Onthology metadata portal.

2018

The data deluge - or Big Data - brings us to think differently about data management and shows us the urgent need to move towards FAIR (Findable, Accessible, Interoperable, Reusable) data. Semantic resources (ontologies, vocabularies, thesauri and terminologies) are no exception to this rule. Between February 16 and March 30, 2018, we conducted a survey on the use of metadata vocabularies to describe such resources. We wanted to evaluate the current state of practice and discuss recommendations in terms of metadata standards for ontologies. In this paper, we present and discuss the results of this survey. The analyze shows that the core semantic web languages (RDFS, OWL, SKOS) and vocabularies such as DCAT or Dublin Core are among the most known and used vocabularies to describe ontologies. More surprisingly, most of the numerous vocabularies really relevant for describing ontologies are barely known and never used: DOOR, VANN, ADMS, OMV, MOD. This demonstrates a lack of a clearly i...

2016

Bio-ontologies are becoming increasingly important in semantic alignment for data integration, information exchange, and semantic interoperability. Due to the large number of emerging bio-ontologies, it is challenging for naïve ontology users to search, select, and adopt a “right” ontology for their applications. Therefore, it is important to have a consistent terminology metadata model and a resource for discovering appropriate ontologies or other resource for use in annotating data. This paper aims to seek a common, shareable, and comprehensive method to create, disseminate, and consume metadata about terminology resources. Keywords—Ontology; Metadata, Ontology Metadata Model

2015

Ontology is an important artifact of Semantic Web applications. Today, there are an enormous number of ontologies available on the Web. Even so, finding and identifying the right ontology is not easy. This is because the majority of ontologies are either not described or described with a general-purpose metadata vocabulary like Dublin Core. On the other hand, ontology construction, irrespective of its types (e.g., general ontology, domain ontology, application ontology), is an expensive affair both in terms of human resources and other infrastructural resources. Hence, the ideal situation would be to reuse the existing ontologies to reduce the development effort and cost, and also to improve the quality of the original ontology. In the current work we present an ontology metadata vocabulary called Metadata for Ontology Description and publication (MOD). To design the vocabulary, we also propose a set of generic guiding principles and a well-established methodology which take into ac...

Integrated Series in Information Systems, 2007

D-Lib Magazine, 2002

The authors hope to make explicit the strong foundations of agreement shared by two prominent metadata Initiatives: the Dublin Core Metadata Initiative (DCMI) and the Institute for Electrical and Electronics Engineers (IEEE) Learning Object Metadata (LOM) Working Group. This agreement emerged from a joint metadata taskforce meeting in Ottawa in August, 2001. By elucidating shared principles and practicalities of metadata, we hope to raise the level of understanding among our respective (and shared) constituents, so that all stakeholders can move forward more decisively to address their respective problems. The ideas in this paper are divided into two categories. are those concepts judged to be common to all domains of metadata and which might inform the design of any metadata schema or application. are the rules of thumb, constraints, and infrastructure issues that emerge from bringing theory into practice in the form of useful and sustainable systems. Principles Practicalities II. Principles The paragraphs in the Principles section set out general truths the authors believe provide a guiding framework for the development of practical solutions for semantic and machine interoperability in any domain using any set of metadata standards. A. Modularity Metadata modularity is a key organizing principle for environments characterized by vastly diverse sources of content,

Language Resources and Evaluation, 2008

Metadata registries comprising sets of categories to be used in data collections exist in many fields. The purpose of a metadata registry is to facilitate data exchange and interoperability within a domain, and registries often contain definitions and examples. In this paper we will argue that in order to ensure completeness, consistency, user-friendliness and extensibility, metadata registries should be structured

2001

The term "application profile" has recently become highly topical. Heery and Patel [1] define application profiles as metadata schemas which consist of metadata elements drawn from one or more namespaces, combined together by implementers and optimised for a particular local application. They state that the principal characteristics of an application profile are that: it may draw on one or more existing namespaces; does not introduce new metadata elements; it can specify permitted schemes and values; and it can refine standard metadata elements. Significant new initiatives such as TV-Anytime [2], MPEG-21 [3] and the Open Archives Initiative (OAI) [4] are demanding application profiles which combine elements from a number of different existing standardized metadata schemas whilst maintaining interoperability and satisfying their own specific requirements through refinements, extensions and additions. So far approaches to application profiles have been based on either RDF Schemas or XML Schemas . The SCHEMAS project [9] has adopted a purely RDF Schema approach. Justification for a pure XML Schema approach to application profiles is given in . Despite high level assurances of unification from the W3C [11, 12], a purist and competitive attitude has prevailed amongst implementers. This has been because the demarcation of roles and the interface between these two disparate W3C Candidate Recommendations has been fuzzy; no low level details or implementations describing interface mechanisms have been provided; and implementers have been afraid of compromising interoperability. In this paper we describe a hybrid collaborative approach which combines the semantic knowledge of RDF Schemas with the explicit structural, cardinality and datatyping constraints provided by XML Schemas in a complementary manner. First we describe our view of how XML Schema and RDF Schema fit into the overall web metadata architecture. We then describe possible schema interface mechanisms.