Metadata is "data about data". The term is ambiguous, as it is used for two fundamentally different concepts (types). Structural metadata is about the design and specification of data structures and is more properly called "data about the containers of data"; descriptive metadata, on the other hand, is about individual instances of application data, the data content.
Metadata is traditionally in the card catalogs of libraries. As information has become increasingly digital, metadata are also used to describe digital data using metadata standards specific to a particular discipline. By describing the contents and context of data files, the quality of the original data/files is greatly increased. For example, a webpage may include metadata specifying what language it is written in, what tools were used to create it, and where to go for more on the subject, allowing browsers to automatically improve the experience of users. Wikipedia encourages the use of metadata by asking editors to add category names to articles, and to include information with citations such as title, source and access date.
The main purpose of metadata is to facilitate in the discovery of relevant information, more often classified as resource discovery. Metadata also helps organize electronic resources, provide digital identification, and helps support archiving and preservation of the resource. Metadata assists in resource discovery by "allowing resources to be found by relevant criteria, identifying resources, bringing similar resources together, distinguishing dissimilar resources, and giving location information." 
Metadata (metacontent) are defined as the data providing information about one or more aspects of the data, such as:
For example, a digital image may include metadata that describe how large the picture is, the color depth, the image resolution, when the image was created, and other data. A text document's metadata may contain information about how long the document is, who the author is, when the document was written, and a short summary of the document.
Metadata are data. As such, metadata can be stored and managed in a database, often called a metadata registry or metadata repository. However, without context and a point of reference, it might be impossible to identify metadata just by looking at them. For example: by itself, a database containing several numbers, all 13 digits long could be the results of calculations or a list of numbers to plug into an equation - without any other context, the numbers themselves can be perceived as the data. But if given the context that this database is a log of a book collection, those 13-digit numbers may now be identified as ISBNs - information that refers to the book, but is not itself the information within the book.
The term "metadata" was coined in 1968 by Philip Bagley, in his book "Extension of programming language concepts" where it is clear that he uses the term in the ISO 11179 "traditional" sense, which is "structural metadata" i.e. "data about the containers of data"; rather than the alternate sense "content about individual instances of data content" or metacontent, the type of data usually found in library catalogues. Since then the fields of information management, information science, information technology, librarianship and GIS have widely adopted the term. In these fields the word metadata is defined as "data about data". While this is the generally accepted definition, various disciplines have adopted their own more specific explanation and uses of the term.
Metadata have been used in various forms as a means of cataloging archived information. The Dewey Decimal System employed by libraries for the classification of library materials is an early example of metadata usage. Library catalogues used 3x5 inch cards to display a book's title, author, subject matter, and a brief plot synopsis along with an abbreviated alpha-numeric identification system which indicated the physical location of the book within the library's shelves. Such data help classify, aggregate, identify, and locate a particular book. Another form of older metadata collection is the use by US Census Bureau of what is known as the "Long Form." The Long Form asks questions that are used to create demographic data to find patterns of distribution.
Metadata may be written into a digital photo file that will identify who owns it, copyright and contact information, what camera created the file, along with exposure information and descriptive information such as keywords about the photo, making the file searchable on the computer and/or the Internet. Some metadata are written by the camera and some is input by the photographer and/or software after downloading to a computer. However, not all digital cameras enable you to edit metadata; this functionality has been available on most Nikon DSLRs since the Nikon D3 and on most new Canon cameras since the Canon EOS 7D.
Photographic Metadata Standards are governed by organizations that develop the following standards. They include, but are not limited to:
Metadata are particularly useful in video, where information about its contents (such as transcripts of conversations and text descriptions of its scenes) are not directly understandable by a computer, but where efficient search is desirable.
Web pages often include metadata in the form of meta tags. Description and keywords meta tags are commonly used to describe the Web page's content. Most search engines use these data when adding pages to their search index.
Metadata can be created either by automated information processing or by manual work. Elementary metadata captured by computers can include information about when an object was created, who created it, when it was last updated, file size and file extension.
For the purposes of this article, an "object" refers to any of the following:
The metadata application is manyfold covering a large variety of fields of application there are nothing but specialised and well accepted models to specify types of metadata. Bretheron & Singley (1994) distinguish between two distinct classes: structural/control metadata and guide metadata. Structural metadata are used to describe the structure of database objects such as tables, columns, keys and indexes. Guide metadata are used to help humans find specific items and are usually expressed as a set of keywords in a natural language. According to Ralph Kimball metadata can be divided into 2 similar categories: technical metadata and business metadata. Technical metadata correspond to internal metadata, and business metadata correspond to external metadata. Kimball adds a third category named process metadata. On the other hand, NISO distinguishes among three types of metadata: descriptive, structural and administrative.
Descriptive metadata are typically used for discovery and identification, as information used to search and locate an object such as title, author, subjects, keywords, publisher. Structural metadata give a description of how the components of an object are organized. An example of structural metadata would be how pages are ordered to form chapters of a book. Finally, administrative metadata give information to help manage the source. They refer to the technical information including file type or when and how the file was created. Two sub-types of administrative metadata are rights management metadata and preservation metadata. Rights management metadata explain intellectual property rights, while preservation metadata contain information that is needed to preserve and save a resource.
Metadata (metacontent), or more correctly, the vocabularies used to assemble metadata (metacontent) statements, are typically structured according to a standardized concept using a well-defined metadata scheme, including: metadata standards and metadata models. Tools such as controlled vocabularies, taxonomies, thesauri, data dictionaries and metadata registries can be used to apply further standardization to the metadata. Structural metadata commonality is also of paramount importance in data model development and in database design.
Metadata (metacontent) syntax refers to the rules created to structure the fields or elements of metadata (metacontent). A single metadata scheme may be expressed in a number of different markup or programming languages, each of which requires a different syntax. For example, Dublin Core may be expressed in plain text, HTML, XML and RDF.
A common example of (guide) metacontent is the bibliographic classification, the subject, the Dewey Decimal class number. There is always an implied statement in any "classification" of some object. To classify an object as, for example, Dewey class number 514 (Topology) (i.e. books having the number 514 on their spine) the implied statement is: "<book><subject heading><514>. This is a subject-predicate-object triple, or more importantly, a class-attribute-value triple. The first two elements of the triple (class, attribute) are pieces of some structural metadata having a defined semantic. The third element is a value, preferably from some controlled vocabulary, some reference (master) data. The combination of the metadata and master data elements results in a statement which is a metacontent statement i.e. "metacontent = metadata + master data". All these elements can be thought of as "vocabulary". Both metadata and master data are vocabularies which can be assembled into metacontent statements. There are many sources of these vocabularies, both meta and master data: UML, EDIFACT, XSD, Dewey/UDC/LoC, SKOS, ISO-25964, Pantone, Linnaean Binomial Nomenclature etc. Using controlled vocabularies for the components of metacontent statements, whether for indexing or finding, is endorsed by ISO-25964: "If both the indexer and the searcher are guided to choose the same term for the same concept, then relevant documents will be retrieved." This is particularly relevant when considering the behemoth of the internet, Google. It simply indexes pages then matches text strings using its complex algorithm, there is no intelligence or "inferencing" occurring. Just the illusion thereof.
Metadata schema can be hierarchical in nature where relationships exist between metadata elements and elements are nested so that parent-child relationships exist between the elements. An example of a hierarchical metadata schema is the IEEE LOM schema where metadata elements may belong to a parent metadata element. Metadata schema can also be one-dimensional, or linear, where each element is completely discrete from other elements and classified according to one dimension only. An example of a linear metadata schema is Dublin Core schema which is one dimensional. Metadata schema are often two dimensional, or planar, where each element is completely discrete from other elements but classified according to two orthogonal dimensions.
In all cases where the metadata schemata exceed the planar depiction, some type of hypermapping is required to enable display and view of metadata according to chosen aspect and to serve special views. Hypermapping frequently applies to layering of geographical and geological information overlays.
The degree to which the data or metadata are structured is referred to as their granularity. Metadata with a high granularity allow for deeper structured information and enable greater levels of technical manipulation however, a lower level of granularity means that metadata can be created for considerably lower costs but will not provide as detailed information. The major impact of granularity is not only on creation and capture, but moreover on maintenance. As soon as the metadata structures get outdated, the access to the referred data will get outdated. Hence granularity shall take into account the effort to create as well as the effort to maintain.
International standards apply to metadata. Much work is being accomplished in the national and international standards communities, especially ANSI (American National Standards Institute) and ISO (International Organization for Standardization) to reach consensus on standardizing metadata and registries.
The core standard is ISO/IEC 11179-1:2004  and subsequent standards (see ISO/IEC 11179). All yet published registrations according to this standard cover just the definition of metadata and do not serve the structuring of metadata storage or retrieval neither any administrative standardisation. It is important to note that this standard refers to metadata as the data about containers of the data and not to metadata (metacontent) as the data about the data contents. It should also be noted that this standard describes itself originally as a "data element" registry, describing disembodied data elements, and explicitly disavows the capability of containing complex structures. Thus the original term "data element" is more applicable than the later applied buzzword "metadata".
The Dublin Core metadata terms are a set of vocabulary terms which can be used to describe resources for the purposes of discovery. The original set of 15 classic  metadata terms, known as the Dublin Core Metadata Element Set  are endorsed in the following standards documents:
Although not a standard, Microformat (also mentioned in the section metadata on the internet below) is a web-based approach to semantic markup which seeks to re-use existing HTML/XHTML tags to convey metadata. Microformat follows XHTML and HTML standards but is not a standard in itself. One advocate of microformats, Tantek Çelik, characterized a problem with alternative approaches:
|“||Here's a new language we want you to learn, and now you need to output these additional files on your server. It's a hassle. (Microformats) lower the barrier to entry.||”|
Data virtualization has emerged as the new software technology to complete the virtualization stack in the enterprise. Metadata are used in data virtualization servers which are enterprise infrastructure components, alongside database and application servers. Metadata in these servers are saved as persistent repository and describe business objects in various enterprise systems and applications. Structural metadata commonality is also important to support data virtualization.
Standardization work has had a large impact on efforts to build metadata systems in the statistical community. Several metadata standards[which?] are described, and their importance to statistical agencies is discussed. Applications of the standards[which?] at the Census Bureau, Environmental Protection Agency, Bureau of Labor Statistics, Statistics Canada, and many others are described. Emphasis is on the impact a metadata registry can have in a statistical agency.
Libraries employ metadata in library catalogues, most commonly as part of an Integrated Library Management System. Metadata are obtained by cataloguing resources such as books, periodicals, DVDs, web pages or digital images. These data are stored in the integrated library management system, ILMS, using the MARC metadata standard. The purpose is to direct patrons to the physical or electronic location of items or areas they seek as well as to provide a description of the item/s in question.
More recent and specialized instances of library metadata include the establishment of digital libraries including e-print repositories and digital image libraries. While often based on library principles, the focus on non-librarian use, especially in providing metadata, means they do not follow traditional or common cataloging approaches. Given the custom nature of included materials, metadata fields are often specially created e.g. taxonomic classification fields, location fields, keywords or copyright statement. Standard file information such as file size and format are usually automatically included.
Standardization for library operation has been a key topic in international standardization (ISO) for decades. Standards for metadata in digital libraries include Dublin Core, METS, MODS, DDI, ISO standard Digital Object Identifier (DOI), ISO standard Uniform Resource Name (URN), PREMIS schema, Ecological Metadata Language, and OAI-PMH. Leading libraries in the world give hints on their metadata standards strategies.
Problems involving metadata in litigation in the United States are becoming widespread.[when?] Courts have looked at various questions involving metadata, including the discoverability of metadata by parties. Although the Federal Rules of Civil Procedure have only specified rules about electronic documents, subsequent case law has elaborated on the requirement of parties to reveal metadata. In October 2009, the Arizona Supreme Court has ruled that metadata records are public record.
Document metadata have proven particularly important in legal environments in which litigation has requested metadata, which can include sensitive information detrimental to a party in court.
Using metadata removal tools to "clean" documents can mitigate the risks of unwittingly sending sensitive data. This process partially (see Data remanence) protects law firms from potentially damaging leaking of sensitive data through electronic discovery.
Australian researches in medicine started a lot of metadata definition for applications in health care. That approach offers the first recognized attempt to adhere to international standards in medical sciences instead of defining a proprietary standard under the WHO umbrella first.
The medical community yet did not approve the need to follow metadata standards despite respective research.
Data warehouse (DW) is a repository of an organization's electronically stored data. Data warehouses are designed to manage and store the data whereas the business intelligence (BI) focuses on the usage of the data to facilitate reporting and analysis.
The purpose of a data warehouse is to house standardized, structured, consistent, integrated, correct, cleansed and timely data, extracted from various operational systems in an organization. The extracted data are integrated in the data warehouse environment in order to provide an enterprise wide perspective, one version of the truth. Data are structured in a way to specifically address the reporting and analytic requirements. The design of structural metadata commonality using a data modeling method such as entity relationship model diagramming is very important in any data warehouse development effort.
An essential component of a data warehouse/business intelligence system is the metadata and tools to manage and retrieve the metadata. Ralph Kimball describes metadata as the DNA of the data warehouse as metadata defines the elements of the data warehouse and how they work together.
Kimball et al. refers to three main categories of metadata: Technical metadata, business metadata and process metadata. Technical metadata are primarily definitional, while business metadata and process metadata are primarily descriptive. Keep in mind that the categories sometimes overlap.
The HTML format used to define web pages allows for the inclusion of a variety of types of metadata, from basic descriptive text, dates and keywords to further advanced metadata schemes such as the Dublin Core, e-GMS, and AGLS standards. Pages can also be geotagged with coordinates. Metadata may be included in the page's header or in a separate file. Microformats allow metadata to be added to on-page data in a way that users do not see, but computers can readily access.
Interestingly, many search engines are cautious about using metadata in their ranking algorithms due to exploitation of metadata and the practice of search engine optimization, SEO, to improve rankings. See Meta element article for further discussion. Studies show that search engines respond to web pages with metadata implementations, and Google has an announcement on its site showing the meta tags that its search engine understands.
These metadata can be linked to the video media thanks to the video servers. Most major broadcast sport events like FIFA World Cup or the Olympic Games use these metadata to distribute their video content to TV stations through keywords. It is often the host broadcaster who is in charge of organizing metadata through its International Broadcast Centre and its video servers. Those metadata are recorded with the images and are entered by metadata operators (loggers) who associate in live metadata available in metadata grids through software (such as Multicam(LSM) or IPDirector used during the FIFA World Cup or Olympic Games).
Metadata that describe geographic objects (such as datasets, maps, features, or simply documents with a geospatial component) have a history dating back to at least 1994 (refer MIT Library page on FGDC Metadata). This class of metadata is described more fully on the Geospatial metadata page.
Ecological and environmental metadata are intended to document the who, what, when, where, why, and how of data collection for a particular study. Metadata should be generated in a format commonly used by the most relevant science community, such as Darwin Core, Ecological Metadata Language, or Dublin Core. Metadata editing tools exist to facilitate metadata generation (e.g. Metavist, Mercury: Metadata Search System, Morpho). Metadata should describe provenance of the data (where they originated, as well as any transformations the data underwent) and how to give credit for (cite) the data products.
Metadata is "information about information" and it is one of the really useful features of digital audio files. When audio went from analogue to digital, it became possible to label or encode audio files with more information than could be contained in just the file name. That descriptive information is called "metadata".
Metadata can be used to name, describe, catalogue and indicate ownership or copyright for a digital audio file, and its presence makes it much easier to locate a specific audio file within a group – through use of a search engine that accesses the metadata. As different digital audio formats were developed, it was agreed that a standardized and specific location would be set aside within the digital files where this information could be stored.
CDs such as recordings of music will carry a layer of metadata about the recordings such as dates, artist, genre, copyright owner, etc. The metadata, not normally displayed by CD players, can be accessed and displayed by specialized music playback and/or editing applications.
The metadata for compressed and uncompressed digital music is often encoded in the ID3 tag. Common editors such as TagLib support MP3, Ogg Vorbis, FLAC, MPC, Speex, WavPack TrueAudio, WAV, AIFF, MP4 and ASF file formats.
With the availability of Cloud applications, which include those to add metadata to content, metadata is increasingly available over the Internet.
|This section does not cite any references or sources. (June 2010)|
Metadata can be stored either internally, in the same file or structure as the data (this is also called embedded metadata), or externally, in a separate file or field from the described data. A data repository typically stores the metadata detached from the data, but can be designed to support embedded metadata approaches. Each option has advantages and disadvantages:
Metadata can be stored in either human-readable or binary form. Storing metadata in a human-readable format such as XML can be useful because users can understand and edit it without specialized tools. On the other hand, these formats are rarely optimized for storage capacity, communication time, and processing speed. A binary metadata format enables efficiency in all these respects, but requires special libraries to convert the binary information into human-readable content.
Each relational database system has its own mechanisms for storing metadata. Examples of relational-database metadata include:
In database terminology, this set of metadata is referred to as the catalog. The SQL standard specifies a uniform means to access the catalog, called the information schema, but not all databases implement it, even if they implement other aspects of the SQL standard. For an example of database-specific metadata access methods, see Oracle metadata. Programmatic access to metadata is possible using APIs such as JDBC, or SchemaCrawler.
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