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The AgMES (Agricultural Metadata Element set) initiative was developed by the Food and Agriculture Organization (FAO) of the United Nations and aims to encompass issues of semantic standards in the domain of agriculture with respect to description, resource discovery, interoperability, and data exchange for different types of information resources.
There are numerous other metadata schemas for different types of information resources. The following list contains a list of a few examples:
AgMES as a namespace is designed to include agriculture specific extensions for terms and refinements from established standard metadata namespaces like Dublin Core, AGLS [2] etc. Thus, to be used for Document-like Information Objects, for example like publications, articles, books, web sites, papers, etc., it will have to be used in conjunction with the standard namespaces mentioned before. The AgMES initiative strives to achieve improved interoperability between information resources in agricultural domain by enabling means for exchange of information.
Describing a DLIO with AgMES means exposing its major characteristics and contents in a standard way that can be reused easily in any information system. The more institutions and organizations in the agricultural domain that use AgMES to describe their DLIOs, the easier it will be to interchange data in between information systems like digital libraries and other repositories of agricultural information.
Metadata on agricultural Document-like Information Objects (DLIOs) can be created and stored in various formats:
AgMES defines elements that can be used to describe a DLIO that can be used together with other metadata standards such as the Dublin Core, the Australian Government Locator Service. A complete list of all elements, refinements and schemes endorsed by AgMES is available from the AgMES website. [3]
Application profiles are defined as schemas which consist of data elements drawn from one or more namespaces, combined by implementers, and optimized for a particular local application. Application profiles share the following four characteristics:
One of the advantages of the AgMES metadata schema is the ability to link between the metadata element and controlled vocabularies. The use of controlled vocabulary provides a "known" set of options to the indexer (and the search programmer) as to how the field can be filled out. Often the values may come from a specific thesaurus (e.g. AGROVOC) or classification schemes (e.g. the AGRIS/CARIS classification scheme) etc. [6]
Thanks to the possibility to use controlled vocabularies for metadata elements, the user is provided with the most precise information. In this context, work is also being carried out on exploiting the power of controlled vocabularies expressed as using URIs and machine-understandable semantics. [7] In this context, FAO is promoting the Agricultural Ontology Service (AOS) initiative with the objective of expressing more semantics within the traditional thesaurus AGROVOC and build a Concept Server [8] as a repository from which it will be always possible to extract traditional KOS.
The Dublin Core vocabulary, also known as the Dublin Core Metadata Terms (DCMT), is a general purpose metadata vocabulary for describing resources of any type. It was first developed for describing web content in the early days of the World Wide Web. The Dublin Core Metadata Initiative (DCMI) is responsible for maintaining the Dublin Core vocabulary.
In information science, an ontology encompasses a representation, formal naming, and definitions of the categories, properties, and relations between the concepts, data, or entities that pertain to one, many, or all domains of discourse. More simply, an ontology is a way of showing the properties of a subject area and how they are related, by defining a set of terms and relational expressions that represent the entities in that subject area. The field which studies ontologies so conceived is sometimes referred to as applied ontology.
Learning Object Metadata is a data model, usually encoded in XML, used to describe a learning object and similar digital resources used to support learning. The purpose of learning object metadata is to support the reusability of learning objects, to aid discoverability, and to facilitate their interoperability, usually in the context of online learning management systems (LMS).
RDF Schema (Resource Description Framework Schema, variously abbreviated as RDFS, RDF(S), RDF-S, or RDF/S) is a set of classes with certain properties using the RDF extensible knowledge representation data model, providing basic elements for the description of ontologies. It uses various forms of RDF vocabularies, intended to structure RDF resources. RDF and RDFS can be saved in a triplestore, then one can extract some knowledge from them using a query language, like SPARQL.
NIEMOpen, frequently referred to as NIEM, originated as an XML-based information exchange framework from the United States, but has transitioned to an OASISOpen Project. This initiative formalizes NIEM's designation as an official standard in national and international policy and procurement. NIEMOpen's Project Governing Board recently approved the first standard under this new project; the Conformance Targets Attribute Specification (CTAS) Version 3.0. A full collection of NIEMOpen standards are anticipated by end of year 2024.
The semantic spectrum, sometimes referred to as the ontology spectrum, the smart data continuum, or semantic precision, is a series of increasingly precise or rather semantically expressive definitions for data elements in knowledge representations, especially for machine use.
RDFa or Resource Description Framework in Attributes is a W3C Recommendation that adds a set of attribute-level extensions to HTML, XHTML and various XML-based document types for embedding rich metadata within Web documents. The Resource Description Framework (RDF) data-model mapping enables its use for embedding RDF subject-predicate-object expressions within XHTML documents. It also enables the extraction of RDF model triples by compliant user agents.
Simple Knowledge Organization System (SKOS) is a W3C recommendation designed for representation of thesauri, classification schemes, taxonomies, subject-heading systems, or any other type of structured controlled vocabulary. SKOS is part of the Semantic Web family of standards built upon RDF and RDFS, and its main objective is to enable easy publication and use of such vocabularies as linked data.
Agricultural Information Management Standards (AIMS) is a web site managed by the Food and Agriculture Organization of the United Nations (FAO) for accessing and discussing agricultural information management standards, tools and methodologies connecting information workers worldwide to build a global community of practice. Information management standards, tools and good practices can be found on AIMS:
The Metadata Encoding and Transmission Standard (METS) is a metadata standard for encoding descriptive, administrative, and structural metadata regarding objects within a digital library, expressed using the XML schema language of the World Wide Web Consortium (W3C). The standard is maintained as part of the MARC standards of the Library of Congress, and is being developed as an initiative of the Digital Library Federation (DLF).
SIMILE was a joint research project run by the World Wide Web Consortium (W3C), Massachusetts Institute of Technology Libraries and MIT CSAIL and funded by the Andrew W. Mellon Foundation. The project ran from 2003 to August 2008. It focused on developing tools to increase the interoperability of disparate digital collections. Much of SIMILE's technical focus is oriented towards Semantic Web technology and standards such as Resource Description Framework (RDF).
Observations and Measurements (O&M) is an international standard which defines a conceptual schema encoding for observations, and for features involved in sampling when making observations. While the O&M standard was developed in the context of geographic information systems, the model is derived from generic patterns proposed by Fowler and Odell, and is not limited to geospatial information. O&M is one of the core standards in the OGC Sensor Web Enablement suite, providing the response model for Sensor Observation Service (SOS).
The FAO geopolitical ontology is an ontology developed by the Food and Agriculture Organization of the United Nations (FAO) to describe, manage and exchange data related to geopolitical entities such as countries, territories, regions and other similar areas.
AGRIS is a global public domain database with more than 12 million structured bibliographical records on agricultural science and technology. It became operational in 1975 and the database was maintained by Coherence in Information for Agricultural Research for Development, and its content is provided by more than 150 participating institutions from 65 countries. The AGRIS Search system, allows scientists, researchers and students to perform sophisticated searches using keywords from the AGROVOC thesaurus, specific journal titles or names of countries, institutions, and authors.
The FAO Country Profiles is a multilingual web portal that repackages the Food and Agriculture Organization of the United Nations (FAO) information archive on its global activities in agriculture and food security in a single area and catalogues it exclusively by country and thematic areas.
The Publishing Requirements for Industry Standard Metadata (PRISM) for the Internet, computing, and computer science, is a specification that defines a set of XML metadata vocabularies for syndicating, aggregating, post-processing and multi-purposing content.
ISO/IEC 19788Information technology – Learning, education and training – Metadata for learning resources is a multi-part standard prepared by subcommittee SC 36 of the joint technical committee ISO/IEC JTC 1, Information Technology for Learning, Education and Training.
The Asset Description Metadata Schema (ADMS) is a common metadata vocabulary to describe standards, so-called interoperability assets, on the Web.
In the context of information retrieval, a thesaurus is a form of controlled vocabulary that seeks to dictate semantic manifestations of metadata in the indexing of content objects. A thesaurus serves to minimise semantic ambiguity by ensuring uniformity and consistency in the storage and retrieval of the manifestations of content objects. ANSI/NISO Z39.19-2005 defines a content object as "any item that is to be described for inclusion in an information retrieval system, website, or other source of information". The thesaurus aids the assignment of preferred terms to convey semantic metadata associated with the content object.
OntoLex is the short name of a vocabulary for lexical resources in the web of data (OntoLex-Lemon) and the short name of the W3C community group that created it.
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