Is metadata one word

Asked by: Pietro Larkin

Score: 4.8/5
(71 votes)

Meta must be combined with a root word, either with a hyphen or by concatenation. Therefore, the only proper terms are meta-data and metadata. … Because the term ‘metadata’ is a trademark of The Metadata Company, DAMA specifically uses the term meta-data.

Is metadata one word or two?

agree metadata is one word.

How do you spell meta data?

The short answer is there is no difference – it is simply a matter of the correct spelling of “metadata“. Call it what you will, taxonomy, meta data or metainformation, it is all metadata.

How do you use metadata in a sentence?

A number of metadata formats currently exist, influenced by the needs of the communities in which they emerged. The nationwide metadata enhanced search engine proved infeasible, federated metadata initiatives were not. From the conceptual model, a database design can be derived, or a definition of metadata .

What is an example of metadata?

Metadata is data about data. … A simple example of metadata for a document might include a collection of information like the author, file size, the date the document was created, and keywords to describe the document. Metadata for a music file might include the artist’s name, the album, and the year it was released.

36 related questions found

Metadata is «data that provides information about other data»,^[1] but not the content of the data, such as the text of a message or the image itself. There are many distinct types of metadata, including:

• Descriptive metadata – the descriptive information about a resource.^[vague] It is used for discovery and identification. It includes elements such as title, abstract, author, and keywords.
• Structural metadata – metadata about containers of data and indicates how compound objects are put together, for example, how pages are ordered to form chapters. It describes the types, versions, relationships, and other characteristics of digital materials.^[2]
• Administrative metadata^[3] – the information to help manage a resource, like resource type, permissions, and when and how it was created.^[4]
• Reference metadata – the information about the contents and quality of statistical data.
• Statistical metadata^[5] – also called process data, may describe processes that collect, process, or produce statistical data.^[6]
• Legal metadata – provides information about the creator, copyright holder, and public licensing, if provided.

Metadata is not strictly bound to one of these categories, as it can describe a piece of data in many other ways.

History[edit]

Metadata has various purposes. It can help users find relevant information and discover resources. It can also help organize electronic resources, provide digital identification, and archive and preserve resources. Metadata allows users to access resources by «allowing resources to be found by relevant criteria, identifying resources, bringing similar resources together, distinguishing dissimilar resources, and giving location information».^[7] Metadata of telecommunication activities including Internet traffic is very widely collected by various national governmental organizations. This data is used for the purposes of traffic analysis and can be used for mass surveillance.^[8]

Metadata was traditionally used in the card catalogs of libraries until the 1980s when libraries converted their catalog data to digital databases.^[9] In the 2000s, as data and information were increasingly stored digitally, this digital data was described using metadata standards.^[10]

The first description of «meta data» for computer systems is purportedly noted by MIT’s Center for International Studies experts David Griffel and Stuart McIntosh in 1967: «In summary then, we have statements in an object language about subject descriptions of data and token codes for the data. We also have statements in a meta language describing the data relationships and transformations, and ought/is relations between norm and data.»^[11]

Unique metadata standards exist for different disciplines (e.g., museum collections, digital audio files, websites, etc.). Describing the contents and context of data or data files increases its usefulness. For example, a web page may include metadata specifying what software language the page is written in (e.g., HTML), what tools were used to create it, what subjects the page is about, and where to find more information about the subject. This metadata can automatically improve the reader’s experience and make it easier for users to find the web page online.^[12] A CD may include metadata providing information about the musicians, singers, and songwriters whose work appears on the disc.

In many countries, government organizations routinely store metadata about emails, telephone calls, web pages, video traffic, IP connections, and cell phone locations.^[13]

Definition[edit]

Metadata means «data about data». Metadata is defined as the data providing information about one or more aspects of the data; it is used to summarize basic information about data that can make tracking and working with specific data easier.^[14] Some examples include:

• Means of creation of the data
• Purpose of the data
• Time and date of creation
• Creator or author of the data
• Location on a computer network where the data was created
• Standards used
• File size
• Data quality
• Source of the data
• Process used to create the data

For example, a digital image may include metadata that describes the size of the image, its color depth, resolution, when it was created, the shutter speed, and other data.^[15] 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 within web pages can also contain descriptions of page content, as well as key words linked to the content.^[16] These links are often called «Metatags», which were used as the primary factor in determining order for a web search until the late 1990s.^[16] The reliance on metatags in web searches was decreased in the late 1990s because of «keyword stuffing»,^[16] whereby metatags were being largely misused to trick search engines into thinking some websites had more relevance in the search than they really did.^[16]

Metadata can be stored and managed in a database, often called a metadata registry or metadata repository.^[17] However, without context and a point of reference, it might be impossible to identify metadata just by looking at it.^[18] 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 alternative sense «content about individual instances of data content» or metacontent, the type of data usually found in library catalogs.^[19][20] 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».^[21] While this is the generally accepted definition, various disciplines have adopted their own more specific explanations and uses of the term.

Slate reported in 2013 that the United States government’s interpretation of «metadata» could be broad, and might include message content such as the subject lines of emails.^[22]

Types[edit]

While the metadata application is manifold, covering a large variety of fields, there are specialized and well-accepted models to specify types of metadata. Bretherton & Singley (1994) distinguish between two distinct classes: structural/control metadata and guide metadata.^[23] Structural metadata describes the structure of database objects such as tables, columns, keys and indexes. Guide metadata helps humans find specific items and is usually expressed as a set of keywords in a natural language. According to Ralph Kimball, metadata can be divided into three categories: technical metadata (or internal metadata), business metadata (or external metadata), and process metadata.

NISO distinguishes three types of metadata: descriptive, structural, and administrative.^[21] Descriptive metadata is typically used for discovery and identification, as information to search and locate an object, such as title, authors, subjects, keywords, and publisher. Structural metadata describes 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 gives information to help manage the source. Administrative metadata refers to the technical information, such as 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 explains intellectual property rights, while preservation metadata contains information to preserve and save a resource.^[7]

Statistical data repositories have their own requirements for metadata in order to describe not only the source and quality of the data^[5] but also what statistical processes were used to create the data, which is of particular importance to the statistical community in order to both validate and improve the process of statistical data production.^[6]

An additional type of metadata beginning to be more developed is accessibility metadata. Accessibility metadata is not a new concept to libraries; however, advances in universal design have raised its profile.^{[24]: 213–214} Projects like Cloud4All and GPII identified the lack of common terminologies and models to describe the needs and preferences of users and information that fits those needs as a major gap in providing universal access solutions.^{[24]: 210–211} Those types of information are accessibility metadata.^[24]: 214 Schema.org has incorporated several accessibility properties based on IMS Global Access for All Information Model Data Element Specification.^[24]: 214 The Wiki page WebSchemas/Accessibility lists several properties and their values. While the efforts to describe and standardize the varied accessibility needs of information seekers are beginning to become more robust, their adoption into established metadata schemas has not been as developed. For example, while Dublin Core (DC)’s «audience» and MARC 21’s «reading level» could be used to identify resources suitable for users with dyslexia and DC’s «format» could be used to identify resources available in braille, audio, or large print formats, there is more work to be done.^[24]: 214

Structures[edit]

Metadata (metacontent) or, more correctly, the vocabularies used to assemble metadata (metacontent) statements, is 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.

Syntax[edit]

Metadata (metacontent) syntax refers to the rules created to structure the fields or elements of metadata (metacontent).^[25] 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.^[26]

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 2 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 of these elements can be thought of as «vocabulary». Both metadata and master data are vocabularies that 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.»^[27] This is particularly relevant when considering search engines of the internet, such as Google. The process indexes pages and then matches text strings using its complex algorithm; there is no intelligence or «inferencing» occurring, just the illusion thereof.

Hierarchical, linear, and planar schemata[edit]

Metadata schemata 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, in which metadata elements may belong to a parent metadata element.
Metadata schemata 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 the Dublin Core schema, which is one-dimensional.
Metadata schemata are often 2 dimensional, or planar, where each element is completely discrete from other elements but classified according to 2 orthogonal dimensions.^[28]

Granularity[edit]

The degree to which the data or metadata is structured is referred to as «granularity». «Granularity» refers to how much detail is provided. Metadata with a high granularity allows for deeper, more detailed, and more structured information and enables a greater level of technical manipulation. 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 costs. As soon as the metadata structures become outdated, so too is the access to the referred data. Hence granularity must take into account the effort to create the metadata as well as the effort to maintain it.

Hypermapping[edit]

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.^[29]

Standards[edit]

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 a consensus on standardizing metadata and registries. The core metadata registry standard is ISO/IEC 11179 Metadata Registries (MDR), the framework for the standard is described in ISO/IEC 11179-1:2004.^[30] A new edition of Part 1 is in its final stage for publication in 2015 or early 2016. It has been revised to align with the current edition of Part 3, ISO/IEC 11179-3:2013^[31] which extends the MDR to support the registration of Concept Systems.
(see ISO/IEC 11179). This standard specifies a schema for recording both the meaning and technical structure of the data for unambiguous usage by humans and computers. ISO/IEC 11179 standard refers to metadata as information objects about data, or «data about data». In ISO/IEC 11179 Part-3, the information objects are data about Data Elements, Value Domains, and other reusable semantic and representational information objects that describe the meaning and technical details of a data item. This standard also prescribes the details for a metadata registry, and for registering and administering the information objects within a Metadata Registry. ISO/IEC 11179 Part 3 also has provisions for describing compound structures that are derivations of other data elements, for example through calculations, collections of one or more data elements, or other forms of derived data. While this standard describes itself originally as a «data element» registry, its purpose is to support describing and registering metadata content independently of any particular application, lending the descriptions to being discovered and reused by humans or computers in developing new applications, databases, or for analysis of data collected in accordance with the registered metadata content. This standard has become the general basis for other kinds of metadata registries, reusing and extending the registration and administration portion of the standard.

The Geospatial community has a tradition of specialized geospatial metadata standards, particularly building on traditions of map- and image-libraries and catalogs. Formal metadata is usually essential for geospatial data, as common text-processing approaches are not applicable.

The Dublin Core metadata terms are a set of vocabulary terms that can be used to describe resources for the purposes of discovery. The original set of 15 classic^[32] metadata terms, known as the Dublin Core Metadata Element Set^[33] are endorsed in the following standards documents:

• IETF RFC 5013^[34]
• ISO Standard 15836-2009^[35]
• NISO Standard Z39.85.^[36]

The W3C Data Catalog Vocabulary (DCAT)^[37] is an RDF vocabulary that supplements Dublin Core with classes for Dataset, Data Service, Catalog, and Catalog Record. DCAT also uses elements from FOAF, PROV-O, and OWL-Time. DCAT provides an RDF model to support the typical structure of a catalog that contains records, each describing a dataset or service.

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.^[38]

Use[edit]

Photographs[edit]

Metadata may be written into a digital photo file that will identify who owns it, copyright and contact information, what brand or model of camera created the file, along with exposure information (shutter speed, f-stop, etc.) and descriptive information, such as keywords about the photo, making the file or image searchable on a computer and/or the Internet. Some metadata is created by the camera such as, color space, color channels, exposure time, and aperture (EXIF), while some is input by the photographer and/or software after downloading to a computer.^[39] Most digital cameras write metadata about the model number, shutter speed, etc., and some enable you to edit it;^[40] this functionality has been available on most Nikon DSLRs since the Nikon D3, on most new Canon cameras since the Canon EOS 7D, and on most Pentax DSLRs since the Pentax K-3. Metadata can be used to make organizing in post-production easier with the use of key-wording. Filters can be used to analyze a specific set of photographs and create selections on criteria like rating or capture time. On devices with geolocation capabilities like GPS (smartphones in particular), the location the photo was taken from may also be included.

Photographic Metadata Standards are governed by organizations that develop the following standards. They include, but are not limited to:

• IPTC Information Interchange Model IIM (International Press Telecommunications Council)
• IPTC Core Schema for XMP
• XMP – Extensible Metadata Platform (an ISO standard)
• Exif – Exchangeable image file format, Maintained by CIPA (Camera & Imaging Products Association) and published by JEITA (Japan Electronics and Information Technology Industries Association)
• Dublin Core (Dublin Core Metadata Initiative – DCMI)
• PLUS (Picture Licensing Universal System)
• VRA Core (Visual Resource Association)^[41]

Telecommunications[edit]

Information on the times, origins and destinations of phone calls, electronic messages, instant messages, and other modes of telecommunication, as opposed to message content, is another form of metadata. Bulk collection of this call detail record metadata by intelligence agencies has proven controversial after disclosures by Edward Snowden of the fact that certain Intelligence agencies such as the NSA had been (and perhaps still are) keeping online metadata on millions of internet users for up to a year, regardless of whether or not they [ever] were persons of interest to the agency.

Video[edit]

Metadata is particularly useful in video, where information about its contents (such as transcripts of conversations and text descriptions of its scenes) is not directly understandable by a computer, but where an efficient search of the content is desirable. This is particularly useful in video applications such as Automatic Number Plate Recognition and Vehicle Recognition Identification software, wherein license plate data is saved and used to create reports and alerts.^[42] There are 2 sources in which video metadata is derived: (1) operational gathered metadata, that is information about the content produced, such as the type of equipment, software, date, and location; (2) human-authored metadata, to improve search engine visibility, discoverability, audience engagement, and providing advertising opportunities to video publishers.^[43] Today most professional video editing software has access to metadata. Avid’s MetaSync and Adobe’s Bridge are 2 prime examples of this.^[44]

Geospatial metadata[edit]

Geospatial metadata relates to Geographic Information Systems (GIS) files, maps, images, and other data that is location-based. Metadata is used in GIS to document the characteristics and attributes of geographic data, such as database files and data that is developed within a GIS. It includes details like who developed the data, when it was collected, how it was processed, and what formats it’s available in, and then delivers the context for the data to be used effectively.^[45]

Creation[edit]

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. In this context an object refers to any of the following:

• A physical item such as a book, CD, DVD, a paper map, chair, table, flower pot, etc.
• An electronic file such as a digital image, digital photo, electronic document, program file, database table, etc.

A metadata engine collects, stores and analyzes information about data and metadata (data about data) in use within a domain.^[46]

Data virtualization[edit]

Data virtualization emerged in the 2000s as the new software technology to complete the virtualization «stack» in the enterprise. Metadata is used in data virtualization servers which are enterprise infrastructure components, alongside database and application servers. Metadata in these servers is saved as persistent repository and describe business objects in various enterprise systems and applications. Structural metadata commonality is also important to support data virtualization.

Statistics and census services[edit]

Standardization and harmonization work has brought advantages to industry efforts to build metadata systems in the statistical community.^[47][48] Several metadata guidelines and standards such as the European Statistics Code of Practice^[49] and ISO 17369:2013 (Statistical Data and Metadata Exchange or SDMX)^[47] provide key principles for how businesses, government bodies, and other entities should manage statistical data and metadata. Entities such as Eurostat,^[50] European System of Central Banks,^[50] and the U.S. Environmental Protection Agency^[51] have implemented these and other such standards and guidelines with the goal of improving «efficiency when managing statistical business processes».^[50]

Library and information science[edit]

Metadata has been used in various ways as a means of cataloging items in libraries in both digital and analog formats. Such data helps classify, aggregate, identify, and locate a particular book, DVD, magazine, or any object a library might hold in its collection.^[52] Until the 1980s, many library catalogs used 3×5 inch cards in file drawers to display a book’s title, author, subject matter, and an abbreviated alpha-numeric string (call number) which indicated the physical location of the book within the library’s shelves. The Dewey Decimal System employed by libraries for the classification of library materials by subject is an early example of metadata usage. The early paper catalog had information regarding whichever item was described on said card: title, author, subject, and a number as to where to find said item.^[53] Beginning in the 1980s and 1990s, many libraries replaced these paper file cards with computer databases. These computer databases make it much easier and faster for users to do keyword searches. Another form of older metadata collection is the use by the 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.^[54] Libraries employ metadata in library catalogues, most commonly as part of an Integrated Library Management System. Metadata is obtained by cataloging resources such as books, periodicals, DVDs, web pages or digital images. This data is 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.^[55] Library operation has for decades been a key topic in efforts toward international standardization. Standards for metadata in digital libraries include Dublin Core, METS, MODS, DDI, DOI, URN, PREMIS schema, EML, and OAI-PMH. Leading libraries in the world give hints on their metadata standards strategies.^[56][57] The use and creation of metadata in library and information science also include scientific publications:

In science[edit]

Metadata for scientific publications is often created by journal publishers and citation databases such as PubMed and Web of Science. The data contained within manuscripts or accompanying them as supplementary material is less often subject to metadata creation,^[58][59] though they may be submitted to e.g. biomedical databases after publication. The original authors and database curators then become responsible for metadata creation, with the assistance of automated processes. Comprehensive metadata for all experimental data is the foundation of the FAIR Guiding Principles, or the standards for ensuring research data are findable, accessible, interoperable, and reusable.^[60]

Such metadata can then be utilized, complemented, and made accessible in useful ways. OpenAlex is a free online index of over 200 million scientific documents that integrates and provides metadata such as sources, citations, author information, scientific fields, and research topics. Its API and open source website can be used for metascience, scientometrics, and novel tools that query this semantic web of papers.^[61][62][63] Another project under development, Scholia, uses the metadata of scientific publications for various visualizations and aggregation features such as providing a simple user interface summarizing literature about a specific feature of the SARS-CoV-2 virus using Wikidata’s «main subject» property.^[64]

In research labor, transparent metadata about authors’ contributions to works have been proposed – e.g. the role played in the production of the paper, the level of contribution and the responsibilities.^[65][66]

Moreover, various metadata about scientific outputs can be created or complemented – for instance, scite.ai attempts to track and link citations of papers as ‘Supporting’, ‘Mentioning’ or ‘Contrasting’ the study.^[67] Other examples include developments of alternative metrics^[68] – which, beyond providing help for assessment and findability, also aggregate many of the public discussions about a scientific paper on social media such as Reddit, citations on Wikipedia, and reports about the study in the news media^[69] – and a call for showing whether or not the original findings are confirmed or could get reproduced.^[70][71]

In museums[edit]

Metadata in a museum context is the information that trained cultural documentation specialists, such as archivists, librarians, museum registrars and curators, create to index, structure, describe, identify, or otherwise specify works of art, architecture, cultural objects and their images.^[72][73][74] Descriptive metadata is most commonly used in museum contexts for object identification and resource recovery purposes.^[73]

Usage[edit]

Metadata is developed and applied within collecting institutions and museums in order to:

• Facilitate resource discovery and execute search queries.^[74]
• Create digital archives that store information relating to various aspects of museum collections and cultural objects, and serve archival and managerial purposes.^[74]
• Provide public audiences access to cultural objects through publishing digital content online.^[73][74]

Standards[edit]

Many museums and cultural heritage centers recognize that given the diversity of artworks and cultural objects, no single model or standard suffices to describe and catalog cultural works.^[72][73][74] For example, a sculpted Indigenous artifact could be classified as an artwork, an archaeological artifact, or an Indigenous heritage item. The early stages of standardization in archiving, description and cataloging within the museum community began in the late 1990s with the development of standards such as Categories for the Description of Works of Art (CDWA), Spectrum, CIDOC Conceptual Reference Model (CRM), Cataloging Cultural Objects (CCO) and the CDWA Lite XML schema.^[73] These standards use HTML and XML markup languages for machine processing, publication and implementation.^[73] The Anglo-American Cataloguing Rules (AACR), originally developed for characterizing books, have also been applied to cultural objects, works of art and architecture.^[74] Standards, such as the CCO, are integrated within a Museum’s Collections Management System (CMS), a database through which museums are able to manage their collections, acquisitions, loans and conservation.^[74] Scholars and professionals in the field note that the «quickly evolving landscape of standards and technologies» creates challenges for cultural documentarians, specifically non-technically trained professionals.^{[75][page needed]} Most collecting institutions and museums use a relational database to categorize cultural works and their images.^[74] Relational databases and metadata work to document and describe the complex relationships amongst cultural objects and multi-faceted works of art, as well as between objects and places, people, and artistic movements.^[73][74] Relational database structures are also beneficial within collecting institutions and museums because they allow for archivists to make a clear distinction between cultural objects and their images; an unclear distinction could lead to confusing and inaccurate searches.^[74]

Cultural objects and artworks[edit]

An object’s materiality, function, and purpose, as well as the size (e.g., measurements, such as height, width, weight), storage requirements (e.g., climate-controlled environment), and focus of the museum and collection, influence the descriptive depth of the data attributed to the object by cultural documentarians.^[74] The established institutional cataloging practices, goals, and expertise of cultural documentarians and database structure also influence the information ascribed to cultural objects and the ways in which cultural objects are categorized.^[72][74] Additionally, museums often employ standardized commercial collection management software that prescribes and limits the ways in which archivists can describe artworks and cultural objects.^[75] As well, collecting institutions and museums use Controlled Vocabularies to describe cultural objects and artworks in their collections.^[73][74] Getty Vocabularies and the Library of Congress Controlled Vocabularies are reputable within the museum community and are recommended by CCO standards.^[74] Museums are encouraged to use controlled vocabularies that are contextual and relevant to their collections and enhance the functionality of their digital information systems.^[73][74] Controlled Vocabularies are beneficial within databases because they provide a high level of consistency, improving resource retrieval.^[73][74] Metadata structures, including controlled vocabularies, reflect the ontologies of the systems from which they were created. Often the processes through which cultural objects are described and categorized through metadata in museums do not reflect the perspectives of the maker communities.^[72][76]

Museums and the Internet[edit]

Metadata has been instrumental in the creation of digital information systems and archives within museums and has made it easier for museums to publish digital content online. This has enabled audiences who might not have had access to cultural objects due to geographic or economic barriers to have access to them.^[73] In the 2000s, as more museums have adopted archival standards and created intricate databases, discussions about Linked Data between museum databases have come up in the museum, archival, and library science communities.^[75] Collection Management Systems (CMS) and Digital Asset Management tools can be local or shared systems.^[74] Digital Humanities scholars note many benefits of interoperability between museum databases and collections, while also acknowledging the difficulties of achieving such interoperability.^[75]

Law[edit]

United States[edit]

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. The Federal Rules of Civil Procedure have specific rules for discovery of electronically stored information, and subsequent case law applying those rules has elucidated on the litigant’s duty to produce metadata when litigating in federal court.^[77] In October 2009, the Arizona Supreme Court has ruled that metadata records are public record.^[78] Document metadata have proven particularly important in legal environments in which litigation has requested metadata, that can include sensitive information detrimental to a certain party in court. Using metadata removal tools to «clean» or redact 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.

Opinion polls have shown that 45% of Americans are «not at all confident» in the ability of social media sites to ensure their personal data is secure and 40% say that social media sites should not be able to store any information on individuals. 76% of Americans say that they are not confident that the information advertising agencies collect on them is secure and 50% say that online advertising agencies should not be allowed to record any of their information at all.^[79]

Australia[edit]

In Australia, the need to strengthen national security has resulted in the introduction of a new metadata storage law.^[80] This new law means that both security and policing agencies will be allowed to access up to 2 years of an individual’s metadata, with the aim of making it easier to stop any terrorist attacks and serious crimes from happening.

In legislation[edit]

Legislative metadata has been the subject of some discussion in law.gov forums such as workshops held by the Legal Information Institute at the Cornell Law School on 22 and 23 March 2010. The documentation for these forums is titled, «Suggested metadata practices for legislation and regulations».^[81]

A handful of key points have been outlined by these discussions, section headings of which are listed as follows:

• General Considerations
• Document Structure
• Document Contents
• Metadata (elements of)
• Layering
• Point-in-time versus post-hoc

In healthcare[edit]

Australian medical research pioneered the definition of metadata 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 World Health Organization (WHO) umbrella. The medical community yet did not approve of the need to follow metadata standards despite research that supported these standards.^[82]

In biomedical research[edit]

Research studies in the fields of biomedicine and molecular biology frequently yield large quantities of data, including results of genome or meta-genome sequencing, proteomics data, and even notes or plans created during the course of research itself.^[83] Each data type involves its own variety of metadata and the processes necessary to produce these metadata. General metadata standards, such as ISA-Tab,^[84] allow researchers to create and exchange experimental metadata in consistent formats. Specific experimental approaches frequently have their own metadata standards and systems: metadata standards for mass spectrometry include mzML^[85] and SPLASH,^[86] while XML-based standards such as PDBML^[87] and SRA XML^[88] serve as standards for macromolecular structure and sequencing data, respectively.

The products of biomedical research are generally realized as peer-reviewed manuscripts and these publications are yet another source of data (see #In science).

Data warehousing[edit]

A data warehouse (DW) is a repository of an organization’s electronically stored data. Data warehouses are designed to manage and store the data. Data warehouses differ from business intelligence (BI) systems because BI systems are designed to use data to create reports and analyze the information, to provide strategic guidance to management.^[89] Metadata is an important tool in how data is stored in data warehouses. The purpose of a data warehouse is to house standardized, structured, consistent, integrated, correct, «cleaned» and timely data, extracted from various operational systems in an organization. The extracted data are integrated in the data warehouse environment to provide an enterprise-wide perspective. Data are structured in a way to serve the reporting and analytic requirements. The design of structural metadata commonality using a data modeling method such as entity-relationship model diagramming is important in any data warehouse development effort. They detail metadata on each piece of data in the data warehouse. An essential component of a data warehouse/business intelligence system is the metadata and tools to manage and retrieve the metadata. Ralph Kimball^[90] 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.^[91] refers to 3 main categories of metadata: Technical metadata, business metadata and process metadata. Technical metadata is primarily definitional, while business metadata and process metadata is primarily descriptive. The categories sometimes overlap.

• Technical metadata defines the objects and processes in a DW/BI system, as seen from a technical point of view. The technical metadata includes the system metadata, which defines the data structures such as tables, fields, data types, indexes, and partitions in the relational engine, as well as databases, dimensions, measures, and data mining models. Technical metadata defines the data model and the way it is displayed for the users, with the reports, schedules, distribution lists, and user security rights.
• Business metadata is content from the data warehouse described in more user-friendly terms. The business metadata tells you what data you have, where they come from, what they mean and what their relationship is to other data in the data warehouse. Business metadata may also serve as documentation for the DW/BI system. Users who browse the data warehouse are primarily viewing the business metadata.
• Process metadata is used to describe the results of various operations in the data warehouse. Within the ETL process, all key data from tasks is logged on execution. This includes start time, end time, CPU seconds used, disk reads, disk writes, and rows processed. When troubleshooting the ETL or query process, this sort of data becomes valuable. Process metadata is the fact measurement when building and using a DW/BI system. Some organizations make a living out of collecting and selling this sort of data to companies – in that case, the process metadata becomes the business metadata for the fact and dimension tables. Collecting process metadata is in the interest of business people who can use the data to identify the users of their products, which products they are using, and what level of service they are receiving.

On the Internet[edit]

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^[92] standards. Pages and files can also be geotagged with coordinates, categorized or tagged, including collaboratively such as with folksonomies.

When media has identifiers set or when such can be generated, information such as file tags and descriptions can be pulled or scraped from the Internet – for example about movies.^[93] Various online databases are aggregated and provide metadata for various data. The collaboratively built Wikidata has identifiers not just for media but also abstract concepts, various objects, and other entities, that can be looked up by humans and machines to retrieve useful information and to link knowledge in other knowledge bases and databases.^[64]

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 regular web users do not see, but computers, web crawlers and search engines can readily access. Many search engines are cautious about using metadata in their ranking algorithms because of exploitation of metadata and the practice of search engine optimization, SEO, to improve rankings. See the Meta element article for further discussion. This cautious attitude may be justified as people, according to Doctorow,^[94] are not executing care and diligence when creating their own metadata and that metadata is part of a competitive environment where the metadata is used to promote the metadata creators own purposes. Studies show that search engines respond to web pages with metadata implementations,^[95] and Google has an announcement on its site showing the meta tags that its search engine understands.^[96] Enterprise search startup Swiftype recognizes metadata as a relevance signal that webmasters can implement for their website-specific search engine, even releasing their own extension, known as Meta Tags 2.^[97]

In the broadcast industry[edit]

In the broadcast industry, metadata is linked to audio and video broadcast media to:

• identify the media: clip or playlist names, duration, timecode, etc.
• describe the content: notes regarding the quality of video content, rating, description (for example, during a sport event, keywords like goal, red card will be associated to some clips)
• classify media: metadata allows producers to sort the media or to easily and quickly find a video content (a TV news could urgently need some archive content for a subject). For example, the BBC has a large subject classification system, Lonclass, a customized version of the more general-purpose Universal Decimal Classification.

This metadata can be linked to the video media thanks to the video servers. Most major broadcast sporting events like FIFA World Cup or the Olympic Games use this metadata to distribute their video content to TV stations through keywords. It is often the host broadcaster^[98] who is in charge of organizing metadata through its International Broadcast Centre and its video servers. This metadata is recorded with the images and 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).^[99][100]

Geospatial[edit]

Metadata that describes geographic objects in electronic storage or format (such as datasets, maps, features, or documents with a geospatial component) has a history dating back to at least 1994 (refer to the MIT Library page on FGDC Metadata). This class of metadata is described more fully on the geospatial metadata article.

Ecological and environmental[edit]

Ecological and environmental metadata is intended to document the «who, what, when, where, why, and how» of data collection for a particular study. This typically means which organization or institution collected the data, what type of data, which date(s) the data was collected, the rationale for the data collection, and the methodology used for the data collection. Metadata should be generated in a format commonly used by the most relevant science community, such as Darwin Core, Ecological Metadata Language,^[101] or Dublin Core. Metadata editing tools exist to facilitate metadata generation (e.g. Metavist,^[102] Mercury, Morpho^[103]). Metadata should describe the 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.

Digital music[edit]

See also: § On the Internet

When first released in 1982, Compact Discs only contained a Table Of Contents (TOC) with the number of tracks on the disc and their length in samples.^[104][105] Fourteen years later in 1996, a revision of the CD Red Book standard added CD-Text to carry additional metadata.^[106] But CD-Text was not widely adopted. Shortly thereafter, it became common for personal computers to retrieve metadata from external sources (e.g. CDDB, Gracenote) based on the TOC.

Digital audio formats such as digital audio files superseded music formats such as cassette tapes and CDs in the 2000s. Digital audio files could be labeled with more information than could be contained in just the file name. That descriptive information is called the audio tag or audio metadata in general. Computer programs specializing in adding or modifying this information are called tag editors. Metadata can be used to name, describe, catalog, 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, typically through use of a search engine that accesses the metadata. As different digital audio formats were developed, attempts were made to standardize a specific location within the digital files where this information could be stored.

As a result, almost all digital audio formats, including mp3, broadcast wav, and AIFF files, have similar standardized locations that can be populated with metadata. 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.

Cloud applications[edit]

With the availability of cloud applications, which include those to add metadata to content, metadata is increasingly available over the Internet.

Administration and management[edit]

Storage[edit]

Metadata can be stored either internally,^[107] 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:

• Internal storage means metadata always travels as part of the data they describe; thus, metadata is always available with the data, and can be manipulated locally. This method creates redundancy (precluding normalization), and does not allow managing all of a system’s metadata in one place. It arguably increases consistency, since the metadata is readily changed whenever the data is changed.
• External storage allows collocating metadata for all the contents, for example in a database, for more efficient searching and management. Redundancy can be avoided by normalizing the metadata’s organization. In this approach, metadata can be united with the content when information is transferred, for example in Streaming media; or can be referenced (for example, as a web link) from the transferred content. On the downside, the division of the metadata from the data content, especially in standalone files that refer to their source metadata elsewhere, increases the opportunities for misalignments between the two, as changes to either may not be reflected in the other.

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.^[108] However, text-based formats are rarely optimized for storage capacity, communication time, or processing speed. A binary metadata format enables efficiency in all these respects, but requires special software to convert the binary information into human-readable content.

Database management[edit]

Each relational database system has its own mechanisms for storing metadata. Examples of relational-database metadata include:

• Tables of all tables in a database, their names, sizes, and number of rows in each table.
• Tables of columns in each database, what tables they are used in, and the type of data stored in each column.

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.^[109]

In popular culture[edit]

One of the first satirical examinations of the concept of Metadata as we understand it today is American Science Fiction author Hal Draper’s short story, MS Fnd in a Lbry (1961).
Here, the knowledge of all Mankind is condensed into an object the size of a desk drawer, however, the magnitude of the metadata (e.g. catalog of catalogs of… , as well as indexes and histories) eventually leads to dire yet humorous consequences for the human race.
The story prefigures the modern consequences of allowing metadata to become more important than the real data it is concerned with, and the risks inherent in that eventuality as a cautionary tale.

See also[edit]

References[edit]

Further reading[edit]

• Gartner, Richard. 2016. Metadata: Shaping Knowledge from Antiquity to the Semantic Web . Springer. ISBN 9783319408910.
• Zeng, Marcia & Qin, Jian. 2016. Metadata . Facet. ISBN 9781783300525.

External links[edit]

• Understanding Metadata: What is metadata, and what is it for? – NISO, 2017
• «A Guardian guide to your metadata» – The Guardian, Wednesday 12 June 2013.
• Metacrap: Putting the torch to 7 straw-men of the meta-utopia – Cory Doctorow’s opinion on the limitations of metadata on the Internet, 2001
• DataONE Investigator Toolkit
• Journal of Library Metadata, Routledge, Taylor & Francis Group, ISSN 1937-5034
• International Journal of Metadata, Semantics and Ontologies (IJMSO), Inderscience Publishers, ISSN 1744-263X
• «Metadata and metacontent» (PDF). Retrieved 25 June 2011. (PDF)
• LPR Standards (PDF), Department of Homeland Security (October 2012)

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Metadata Have Been Around for a While

Old-Timey Provenance: Proto-Metadata

Metadata is as Valuable as the Data

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Defining Metadata Using Multiple Sources

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What is metadata: Creating our own Definition

The W7 Ontological Model of Metadata

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How to Use Metadata to enhance data reuse

Using Ontologies to Enhance Discoverability in Metadata

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Our Data Enriched with Valuable Metadata

Other Discussions on Defining Metadata

Other Discussions on Ontologies and Ontology

Read more about metadata

Содержание

Каждый день мы создаем новую цифровую информацию и обмениваемся ею. Любое подобное действие, будь то отправка сообщения по email, заказ в онлайн-магазине, размещение статьи в блоге, автоматически генерирует метаданные. Они указывают на автора контента на сайте, позволяют установить лицензионные ограничения на использование информации, зафиксировать факт проведения транзакции и прочее. 

Разбираемся, что относится к метаданным и как их использовать.

Что такое метаданные

Буквально — это данные о данных. К метаданным относится информация о технических характеристиках файла, о любой манипуляции с ним или, как вариант, — о действии пользователя на интернет-ресурсе. Метаданные первоначально задумывались как инструмент для каталогизации файлов. Со временем это понятие масштабировалось и теперь охватывает «биографию» цифрового объекта целиком.

Например, если вы создаете документ Word, можете посмотреть метаданные в его свойствах. Там будут указаны название и описание документа, дата и время его создания, актуальная версия, автор, история редактирования, местоположение, технические свойства программы, в которой был создан файл, и другие сведения.

Виды метаданных

В классификации Национальной организации по информационным стандартам (NISO) выделяют три их разновидности:

• Описательные — сведения, которые отражают содержимое файлов или текстовых документов. Они нужны, чтобы ранжировать и группировать объекты, обеспечивать их быстрый поиск. Например, к описательным метаданным исследовательской работы относят ФИО автора, название, аннотацию, ключевые слова.
• Структурные — информация о способах хранения данных и их формальных свойствах. К структурным метаданным телефонного звонка относят длительность, время начала и завершения разговора, а электронной книги — размер и тип файла.
• Административные — то, что необходимо для управления сайтом или его содержимым, а также базами данных и трафиком. К таким метаданным относят права доступа или лицензионные правила.

Воспользуйтесь Коллтрекингом Calltouch, чтобы получать исчерпывающие данные о звонках в ваш контакт-центр. Сервис покажет источник каждого звонка, его дату и время, а также геоположение, операционную систему и браузер звонящего. Программа также выведет на удобный дашборд статистику по лидам и выручке. Вы узнаете, какие площадки наиболее эффективны для продвижения вашей компании.

Какая информация содержится в метаданных

Каждому типу файлов автоматически присваивается свой набор метаданных:

• Фото- и видеофайлы. Изображению автоматически присваивается следующая информация: формат, размеры, разрешение, глубина цвета, сжатие. Указываются и свойства камеры — например производитель, длина выдержки, диафрагма, ISO. В современных камерах часто настроены гео- и тематические теги. 

Видеофайлы имеют аналогичный набор метаданных, дополнительно им присваиваются частота кадров и свойства звука.

• Аудиофайлы. В стандартном перечне метаданных трека представлены сведения о дате создания и редактирования файла, исполнитель, альбом, название композиции и ее номер, битрейт, частота дискретизации.
• Сообщения в мессенджерах. Основные метаданные — время отправки и получения, адресат, вложения, реакции-эмоджи.
• Имейлы. Сохраняются время отправки, электронные адреса, IP отправителя.
• Учетные записи в соцсетях. В набор метаданных пользовательского профиля входят номер телефона, количество просмотров, лайков записей и друзей в френдлисте.
• Все типы файлов. Универсальные метаданные, которые присваиваются всем видам файлов без исключения, — место хранения, дата и время создания и последующих редактирований, размер, тип, владелец.

Наиболее важный тип метаданных — расширение файла. По нему операционные системы считывают кодировку и подбирают программу, способную его открыть.

Где и как используют метаданные

Метаданные необходимы владельцам информационных и авторских порталов, маркетологам, провайдерам, правительственным службам. Они позволяют установить авторство контента, обеспечивать безопасность информации и анализировать поведение клиентов. 

Основные цели отслеживания метаданных — это:

• Установка лицензионных ограничений. Метаданные используют, чтобы задать условия распространения информации, определить автора публикации или фото.
• Мониторинг активности в интернете. Сведения из переписок по email и в мессенджерах, а также об активности пользователей на веб-страницах помогают обнаружить авторов запрещенного контента, противодействовать терроризму и экстремизму. 
• Сортировка и идентификация содержимого сайта. С помощью метаданных упорядочивают процесс поиска информации, а алгоритмы Yandex и Google, например, определяют тип контента на сайте.
• Анализ поведения потребителей. Метаданные помогают онлайн-магазинам отслеживать запросы, потребности и изменения вкусов посетителей. Также маркетологи целенаправленно собирают информацию об их местонахождении, интересах, типах устройств, с которых они заходят на сайты. Все это помогает разработать эффективную стратегию продвижения и запустить результативную рекламную кампанию.
• Отслеживание местонахождения пользователей в законных и незаконных целях. Метаданными пользуются правительственные организации и, к сожалению, злоумышленники. Зная IP-адрес пользователя, можно получить личные сведения вплоть до его места работы и адреса проживания.

Дополнительные данные помогают улучшать сайт и увеличивать продажи. Сервис Calltouch Предикт позволяет получить массу полезной информации о звонке: его типе, цели, а также поле звонящего. Вы увидите информацию по каждому обращению в компанию и получите доступ к текстовой расшифровке разговора в личном кабинете. Точная статистика речевого анализатора покажет, насколько эффективны ваша маркетинговая стратегия и работа контакт-центра. Вы сможете улучшить скрипты для операторов и ускорить продвижение клиента по воронке продаж.

Представляют ли метаданные угрозу

Основная угроза безопасности — не метаданные, а само содержание файла. В непроверенных объектах нередко скрываются вирусы или программы, собирающие платежные сведения пользователей.

Однако и метаданные могут предоставлять злоумышленникам важную информацию. Вот лишь некоторые сценарии:

• Преступники узнают характеристики ПО компании и атакуют ее сеть. Для этого пишут эксплойт, который находит уязвимости в системе безопасности, а затем нарушает работу IT-инфраструктуры и/или помогает получить контроль над ней. Нужную информацию можно получить из любого файла компании, например документа Word.
• По метаданным фото определяют маршруты пользователя. Если вы выкладываете снимки в соцсеть или отправляете их своим контактам, злоумышленники могут вычислить геоданные и узнать, где вы работаете, живете и любите проводить свободное время.
• Данные о версии ПО, фото и сообщениях применяют для мошенничества и шантажа. Например, под определенное техническое окружение подбирают фишинговые ссылки или используют информацию о ваших адресатах, чтобы выдавать себя за них.

Способы сократить количество метаданных

Большинство соцсетей, мессенджеров и платформ автоматически удаляют метаданные графических файлов, если загружать их с помощью функции «Камера», а не вложенным документом. При таком способе отправки объекта в Telegram, WhatsApp или Viber картинка или видео не будут содержать информацию об устройстве пользователя, ПО и прочих характеристиках. Однако метаданные текстовых файлов сохраняются независимо от платформы и способа загрузки.

При размещении графики на фотостоках, таких как Unsplash, Pinterest, Pexels, метаданные полностью исчезают, а если отправлять файлы через почтовые сервисы (Google, Яндекс, Mail), — остаются.

Вот варианты уменьшения количества метаданных:

• Используйте ПО вместо онлайн-сервисов. Программы с открытым исходным кодом помогают генерировать меньше метаданных, чем веб-инструменты.
• Удаляйте метаданные. Для разных ОС разработаны программы, которые помогают избавляться от этого типа информации. Для Windows это Microsoft Office Document Inspector (текстовые документы), для Mac OS — ImageOptim (графические файлы), для Linux — Metadata Anonymisation Toolkit (разные форматы) или ExifTool (изображения).

Главное в статье

• К метаданным относят характеристики цифрового объекта: название, имя владельца, дату создания и изменения, размер и параметры ПО, с помощью которого был создан файл.
• У каждого формата объекта — фото, видео, аудио, email, телефонного звонка, тестового документа — есть свой набор метаданных.
• Метаданные собирают, чтобы устанавливать лицензионные ограничения, запускать рекламные кампании с учетом информации о пользователях, предотвращать преступления.
• Метаданными пользуются злоумышленники, чтобы взламывать корпоративные сети предприятий, рассылать мошеннические предложения пользователям или вычислять их местоположение и маршруты.
• Скрывайте метаданные своих файлов с помощью специальных сервисов и отправляйте снимки и видео в соцсетях и мессенджерах с помощью функции «Камера».

Metadata is data about data. In other words, it’s information that’s used to describe the data that’s contained in something like a web page, document, or file. Another way to think of metadata is as a short explanation or summary of what the data is.

A simple example of metadata for a document might include a collection of information like the author, file size, the date the document was created, and keywords to describe the document. Metadata for a music file might include the artist’s name, the album, and the year it was released.

For computer files, metadata can be stored within the file itself or elsewhere, like is the case with some EPUB book files that keep metadata in an associated ANNOT file.

Metadata represents behind-the-scenes information that’s used everywhere, by every industry, in multiple ways. It’s ubiquitous in information systems, social media, websites, software, music services, and online retailing. Metadata can be created manually to pick and choose what’s included, but it can also be generated automatically based on the data.

Types of Metadata

Metadata comes in several types and is used for a variety of broad purposes that can be roughly categorized as a business, technical, or operational.

• Descriptive metadata properties include title, subject, genre, author, and creation date, for example.
• Rights metadata might include copyright status, rights holder, or license terms.
• Technical metadata properties include file types, size, creation date and time, and type of compression. Technical metadata is often used for digital object management and interoperability.
• Preservation metadata is used in navigation. Example preservation metadata properties include an item’s place in a hierarchy or sequence.
• Markup languages include metadata used for navigation and interoperability. Properties might include heading, name, date, list, and paragraph.

Metadata and Website Searches

The metadata embedded in websites is critically important to the success of the site. It includes a description of the website, keywords, metatags, and more — all of which play a role in search results.

Some common metadata terms used when building a web page include meta title and meta description. The meta title briefly explains the topic of the page to help readers understand what they’ll get from the page should they open it. The meta description is further information, though brief, about the contents of the page.

Both of these metadata pieces are displayed on search engines for readers to get a quick glimpse of what the page is about. The search engine uses this information to group together similar items so that when you search for a specific keyword or group of keywords, the results are relevant to your search.

A web page’s metadata might also include the language the page was written in, like whether it’s an HTML page.

Metadata for Tracking

Retailers and online shopping sites use metadata to track consumers’ habits and movements. Digital marketers follow your every click and purchase, storing information about you such as the type of device you use, your location, the time of day, and any other data they’re legally allowed to gather.

Armed with this information, they create a picture of your daily routine and interactions, your preferences, your associations, and your habits, and can use that picture to market their products to you.

Internet service providers, governments, and anyone else with access to large collections of metadata information could potentially use the metadata from web pages, emails, and other places there are users online, to monitor web activity.

Since metadata is a short representation of the larger data, this information could be searched through and filtered to find information about millions of users at once and track things like hate speech, threats, etc. Some governments have been known to collect this data, including not only web traffic but also phone calls, location information, and more.

Metadata in Computer Files

Every file you save on your computer includes some basic information about the file so that the operating system understands how to deal with it, and so that you or someone else can quickly gather from the metadata what the file is.

For example, in Windows, when you view the properties of a file, you can clearly see the file’s name, the file type, where it’s stored, when it was created and last modified, how much space it’s taking up on the hard drive, who owns the file, and more.

The information can be used by the operating system as well as other programs. For instance, you might use a file search utility to quickly find all the files on your computer that were created sometime today and that is bigger than 3 MB.

Metadata in Social Media

Every time you friend someone on Facebook, listen to music Spotify recommends for you, post a status or share someone’s tweet, metadata is at work in the background. Pinterest users can create boards of related articles because of metadata stored with those articles.

Metadata is useful in very specific social media situations such as when you’re looking for someone on Facebook. You can see a profile image and a short description of the Facebook user to learn just the basics about them before deciding to friend them or send them a message

Metadata and Database Management

Metadata in the world of database management might address the size and formatting or other characteristics of a data item. It’s essential to interpreting the contents of database data. The eXtensible Markup Language (XML) is one markup language that defines data objects using a metadata format.

For example, if you have a set of data with dates and names spread all about, you can’t know what the data is representing or what the columns and rows are describing. With basic metadata like column names, you can quickly glance at the database and understand what a particular set of data is describing.

If there’s a list of names without metadata to describe them, they could be anything, but when you add metadata to the top that says «Employee’s Let Go,» you now know that those names represent all of the employees who have been fired. The date beside them can also be understood as something useful like «Termination Date» or «Hire Date.»

What Metadata Isn’t

Metadata is data that describes data, but it isn’t the data itself. The author and creation date metadata stored in a Microsoft Word document, for example, is not the entirety of the document but instead just a few details about the file.

Since metadata is not the actual data, it can usually safely be made public because it doesn’t give anyone access to the raw data. Knowing summary details about a web page or video file, for example, is enough to understand what the file is but not enough to actually see the whole page or play the whole video.

Think of metadata as a card file in your childhood library that contains information about a book; metadata isn’t the book itself. You can learn a lot about a book by examining its card file, but you have to open the book to read it.