VEST Registry. Metadata
The VEST Registry browser by Metadata Sets includes namespaces and application profiles. They are classified in different types of information:
- Document-like Information Objects. This term is used to indicate resources comparable to paper documents such as Web sites, power-point files, photos etc. but does not cover, for example, organizations or projects.
- Event Metadata. An event can be defined simply as "something that happens at a given place and time." An event can be broken into different 'subsets', for example, by day or session.
- Geospatial Metadata. Metadata describing a class of data that has a geographic or spatial nature. Appropriate geo-referenced information on physical and socio-economic resources for agriculture in the broadest sense (including forestry and fisheries) is of substantial value in the analysis of economic feasibility and environmental acceptability of agricultural and rural development and food security programmes.
- Learning Object Metadata. Metadata describing learning resources with the objective of supporting the dissemination, use and interoperability of learning objects.
- Organization Metadata. Metadata describing an organization. They can for example help to communicate with the source or creator of information (responsible party).
- Person/Expert Metadata. Metadata describing an expert. An expert is someone normally recognized as a reliable source within a specific domain of knowledge.
- Project Metadata. Metadata describing projects. Project descriptions are created by different institutions, or by different departments within institutions, for a variety of purposes and with a variety of formalized or less formalized methods.
- Research metadata like Biodiversity and Genetic Resources. All major crops contain genes that have been introduced from their wild relatives to provide important characteristics such as resistance to diseases and pests, enhanced tolerance to stress, and improved levels of vitamins or other nutrients.
- Statistical Metadata. Metadata describing statistical data. Statistical metadata facilitate sharing, querying, and understanding statistical data over the lifetime of the data.
If you want to suggest a new type of metadata element set, we invite you to contact us, fill in the form AIMS: VEST Registry providing the following information: type of metadata set, type of suggestion, contact person and organization.
Select any element on the types list or types of information resource and click Apply. If you want to browse by type of metadata set, select only items from the type of metadata set and click Apply. While if you want to retrieve all the records used by types of information resource by any metadata set, select the information resource and click Apply. If you wish to list all the metadata sets, click Apply without selecting any item. Hold CONTROL key for selecting 2 or more types30 results by Metadata Set
This Application Profile defines the metadata elements for exchanging information about events within the Agricultural Community.
There is no DTD for this AP, as it is based on the RSS specification and extends it with event-specific elements and agriculture-specific schemes from the AgMES namespace.
The goal of this Application Profile is to define a standard exchange format for “basic” metadata about an organization. Metadata about an organization are a means to help identify regional, national and international organizations specializing in different agriculture-related domains.
The Agricultural Metadata Element Set (AgMES) is the abbreviation for Agricultural Metadata Element Set. AgMES is the metadata standard developed by the Food and Agriculture Organization (FAO) of the United Nations for the description and discovery of agricultural information resources
The Bibliographic Ontology (BIBO) describe bibliographic things on the semantic Web in RDF. This ontology can be used as a citation ontology, as a document classification ontology, or simply as a way to describe any kind of document in RDF. It has been inspired by many existing document description metadata formats, and can be used as a common ground for converting other bibliographic data sources.
The IEEE 1484.12.1 – 2002 Standard for Learning Object Metadata (IEEE LOM) 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).
MARC 21 is a result of the combination of the United States and Canadian MARC formats (USMARC and CAN/MARC). MARC21 is based on the ANSI standard Z39.2, which allows users of different software products to communicate with each other and to exchange data.MARC 21 was designed to redefine the original MARC record format for the 21st century and to make it more accessible to the international community.
The Metadata Authority Description Schema (MADS) is an XML schema for an authority element set that may be used to provide metadata about agents (people, organizations), events, and terms (topics, geographics, genres, etc.). MADS serves as a companion to the Metadata Object Description Schema (MODS) to provide metadata about the authoritative entities used in MODS descriptions. The standard is maintained by the MODS/MADS Editorial Committee with the Network Development and MARC Standards Office of the Library of Congress and input from users.
Metadata Object Description Schema (MODS) is a schema for a bibliographic element set that may be used for a variety of purposes, and particularly for library applications. The standard is maintained by the Network Development and MARC Standards Office of the Library of Congress with input from users.
RSS stands for Really Simple Syndication and is a Web content syndication format.
The RSS specification identifies a few metadata elements for the exchange of basic information about news and contents in general (web pages, articles).
This metadata set is encoded as RDF in the RSS 1.0 specification (which also includes Dublin Core elements) and as XML in the RSS 2.0 specification.
Schema.org is an initiative launched on 2 June 2011 by Bing, Google and Yahoo! to introduce the concept of the Semantic Web to websites. On 1 November Yandex (largest search engine in Russia) joined the initiative.
The site schema.org provides a collection of schemas, i.e., html tags, that webmasters can use to markup their pages in ways recognized by major search providers. Search engines rely on this markup to improve the display of search results, making it easier for people to find the right web pages.
Many sites are generated from structured data, which is often stored in databases. When this data is formatted into HTML, it becomes very difficult to recover the original structured data. Many applications, especially search engines, can benefit greatly from direct access to this structured data. On-page markup enables search engines to understand the information on web pages and provide richer search results in order to make it easier for users to find relevant information on the web. Markup can also enable new tools and applications that make use of the structure.
Simple Knowledge Organization System (SKOS) is a common data model for sharing and linking knowledge organization systems via the Web. Many knowledge organization systems, such as thesauri, taxonomies, classification schemes and subject heading systems, share a similar structure, and are used in similar applications. SKOS captures much of this similarity and makes it explicit, to enable data and technology sharing across diverse applications.
The SKOS data model provides a standard, low-cost migration path for porting existing knowledge organization systems to the Semantic Web. SKOS also provides a lightweight, intuitive language for developing and sharing new knowledge organization systems. It may be used on its own, or in combination with formal knowledge representation languages such as the Web Ontology language (OWL).