The term metadata is an ambiguous term which is used for two fundamentally different concepts (types). Although the expression "data about data" is often used, it does not apply to both in the same way. Structural metadata, the design and specification of data structures, cannot be about data, because at design time the application contains no data. In this case the correct description would be "data about the containers of data". Descriptive metadata, on the other hand, is about individual instances of application data, the data content. In this case, a useful description (resulting in a disambiguating neologism) would be "data about data contents" or "content about content" thus metacontent. Descriptive, Guide and the National Information Standards Organization concept of administrative metadata are all subtypes of metacontent.
Metadata (metacontent) is traditionally found in the card catalogs of libraries. As information has become increasingly digital, metadata is 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's 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.
Metadata (metacontent) is defined as data providing information about one or more aspects of the data, such as:
- Means of creation of the data
- Purpose of the data
- Time and date of creation
- Creator or author of data
- Placement on a computer network where the data was created
- Standards used
- The basic information of a piece of music
For example, a digital image may include metadata that describes 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 is data. As such, metadata can be stored and managed in a database, often called a registry or repository. However, it is impossible to identify metadata just by looking at it because a user would not know when data is metadata or just data.
Metadata has 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 helps 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 create patterns and to find patterns of distribution.  The term was coined in 1968 by Philip Bagley, one of the pioneers of computerized document retrieval. 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.
For the purposes of this article, an "object" refers to any of the following:
- A physical item such as a book, CD, DVD, map, chair, table, flower pot, etc.
- An electronic file such as a digital image, digital photo, document, program file, database table, etc.
Metadata may be written into a digital photo file that will identify who owns it, copyright & 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 is written by the camera and some is input by the photographer and/or software after downloading to a computer.
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 Adobe 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).
Metadata is 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 this data when adding pages to their search index.
Creation of metadata
Metadata can be created either by automated information processing or by manual work. Elementary metadata captured by computers can include information about when a file was created, who created it, when it was last updated, file size and file extension.
The metadata application is manifold 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 is used to describe the structure of computer systems such as tables, columns and indexes. Guide metadata is used to help 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 2 similar categories—Technical metadata and Business metadata. Technical metadata correspond to internal metadata, business metadata to external metadata. Kimball adds a third category named Process metadata. On the other hand, NISO distinguishes between three types of metadata: descriptive, structural and administrative. Descriptive metadata is the information used to search and locate an object such as title, author, subjects, keywords, publisher; structural metadata gives a description of how the components of the object are organised; and administrative metadata refers to the technical information including file type. Two sub-types of administrative metadata are rights management metadata and preservation metadata.
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.
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) (e.g. a book has this number on the 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 that the behemoth of the internet, Google, is simply indexing then matching text strings, there is no intelligence or "inferencing" occurring.
Hierarchical, linear and planar schemata
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.
Granularity is a term that applies to data as well as to metadata. The degree to which metadata is structured is referred to as its granularity. Metadata with a high granularity allows for deeper structured information and enables 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 data about containers of data and not to metadata (metacontent) as data about 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".
Data Virtualization has emerged 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, along side with Database and Application servers. Metadata in these servers is saved as persistent repository and describes business objects in various enterprise systems and applications.
SVN Checkout Metadata
.SVN hidden files created in the web root folder which can reveal crucial information of the code repositories.
Statistics and census services
Standardization work has had a large impact on efforts to build metadata systems in the statistical community. Several metadata standards are described, and their importance to statistical agencies is discussed. Applications of the standards 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.
Library and information science
Libraries employ metadata in library catalogues, most commonly as part of an Integrated Library Management System. Metadata is obtained by cataloguing 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.
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.
Metadata and the law
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 has 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.
Metadata in healthcare
Australian researches in medicine started a lot of metadata definition for applications in health care. That approach offers the first recognised 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.
Metadata and data warehousing
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 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 is integrated in the data warehouse environment in order to provide an enterprise wide perspective, one version of the truth. Data is structured in a way to specifically address the reporting and analytic requirements.
An essential component of a data warehouse/business intelligence system is the metadata and tools to manage and retrieve 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 is primarily definitional while business metadata and process metadata are primarily descriptive. Keep in mind that 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, and 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 it comes from, what it means and what its relationship is to other data in the data warehouse. Business metadata may also serves 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 are 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. Process metadata is in 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.
Metadata on the Internet
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.
Metadata on the broadcast industry
In broadcast industry, metadata are 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 allow 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).
These metadata can be linked to the video media thanks to the video servers. All last broadcasted sport events like FIFA World Cup or Olympic Games use these metadata to distribute their video content to TV stations through keywords. It's 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 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 & environmental metadata
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 it originated, as well as any transformations the data underwent) and how to give credit for (cite) the data products.
Metadata on CDs and DVDs
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.
With the availability of Cloud applications, which include those to add metadata to content, metadata is increasingly available over the Internet.
Metadata administration and management
Metadata can be stored either internally, in the same file as the data, or externally, in a separate file. Metadata that is embedded with content is called embedded metadata. A data repository typically stores the metadata detached from the data. Both ways have advantages and disadvantages:
- Internal storage allows transferring metadata together with the data it describes; thus, metadata is always at hand and can be manipulated easily. This method creates high redundancy and does not allow holding metadata together.
- External storage allows bundling metadata, for example in a database, for more efficient searching. There is no redundancy and metadata can be transferred simultaneously when using streaming. However, as most formats use URIs for that purpose, the method of how the metadata is linked to its data should be treated with care. What if a resource does not have a URI (resources on a local hard disk or web pages that are created on-the-fly using a content management system)? What if metadata can only be evaluated if there is a connection to the Web, especially when using RDF? How to realize that a resource is replaced by another with the same name but different content?
Moreover, there is the question of data format: 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 not optimized for storage capacity; it may be useful to store metadata in a binary, non-human-readable format instead to speed up transfer and save memory.
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.
- Vocabulary OneSource
- Agris: International Information System for the Agricultural Sciences and Technology
- Classification scheme
- Crosswalk (metadata)
- Data Dictionary (aka metadata repository)
- Dublin Core
- GEOMS – Generic Earth Observation Metadata Standard
- ISO/IEC 11179
- Knowledge tag
- Meta element
- Metadata from Wikiversity
- Metadata discovery
- Metadata facility for Java
- Metadata Access Point Interface
- Metadata publishing
- Metadata registry
- METAFOR Common Metadata for Climate Modelling Digital Repositories
- Mercury: Metadata Search System
- Ontology (computer science)
- Official statistics
- Preservation Metadata
- Semantic Web
- The Metadata Company
- Universal Data Element Framework
- ^ Hüner, K.; Otto, B.; Österle, H.: Collaborative management of business metadata, in: International Journal of Information Management, 2011
- ^ METADATA STANDARDS AND METADATA REGISTRIES: AN OVERVIEW
- ^ National Archives of Australia (2002). "AGLS Metadata Element Set - Part 2: Usage Guide - A non-technical guide to using AGLS metadata for describing resources". http://www.naa.gov.au/records-management/publications/agls-element.aspx. Retrieved 17 March 2010.
- ^ Bagley, Philip (Nov 1968), Extension of programming language concepts, Philadelphia: University City Science Center
- ^ "The notion of "metadata" introduced by Bagley". Solntseff, N+1; Yezerski, A (1974), A survey of extensible programming languages, Annual Review in Automatic Programming, 7, Elsevier Science Ltd, pp. 267–307, doi:10.1016/0066-4138(74)90001-9
- ^ a b NISO. Understanding Metadata. NISO Press. ISBN 1-880124-62-9. http://www.niso.org/publications/press/UnderstandingMetadata.pdf. Retrieved 5 January 2010.
- ^ Bretherton, F. P.; Singley, P.T. (1994). "Metadata: A User's View, Proceedings of the International Conference on Very Large Data Bases (VLDB)". pp. 1091–1094.
- ^ Cathro, Warwick (1997). "Metadata: an overview". http://www.nla.gov.au/nla/staffpaper/cathro3.html. Retrieved 6 January 2010.
- ^ DCMI (5 Oct 2009). "Semantic Recommendations". http://dublincore.org/specifications/. Retrieved 6 January 2010.
- ^ "Types of Metadata". University of Melbourne. 15 August 2006. http://www.infodiv.unimelb.edu.au/metadata/add_info.html. Retrieved 6 January 2010. [dead link]
- ^ [www.isprs.org/proceedings/XXXII/part4/www.ifp.uni.../kuebler51.pdf THE DESIGN AND DEVELOPMENT OF A GEOLOGIC HYPERMAP PROTOTYPE]
- ^ ISO/IEC 11179-1:2004 Information technology - Metadata registries (MDR) - Part 1: Framework
- ^ Library of Congress Washington DC on metadata
- ^ [www.d-nb.de/standardisierung/.../metadaten.htm Deutsche Nationalbibliothek Frankfurt on metadata]
- ^ Gelzer, Reed D. (February 2008). "Metadata, Law, and the Real World: Slowly, the Three Are Merging". Journal of AHIMA (American Health Information Management Association) 79 (2): 56–57, 64. http://library.ahima.org/xpedio/groups/public/documents/ahima/bok1_036537.hcsp?dDocName=bok1_036537. Retrieved 8 January 2010.
- ^ Walsh, Jim (30 October 2009). "Ariz. Supreme Court rules electronic data is public record". The Arizona Republic (Arizona, United States). http://www.azcentral.com/arizonarepublic/local/articles/2009/10/30/20091030metadata1030.html. Retrieved 8 January 2010.
- ^ M. Löbe, M. Knuth, R. Mücke TIM: A Semantic Web Application for the Specification of Metadata Items in Clinical Research, CEUR-WS.org, urn:nbn:de:0074-559-9
- ^ Inmon, W.H. Tech Topic: What is a Data Warehouse? Prism Solutions. Volume 1. 1995.
- ^ Ralph Kimball,The Data Warehouse Lifecycle Toolkit, Second Edition. New York, Wiley, 2008, ISBN 978-0-470-14977-5, page 10, 115–117, 131–132, 140, 154–155
- ^ Kimball et al., The Data Warehouse Lifecycle Toolkit, Second Edition. New York, Wiley, 2008, ISBN 978-0-470-14977-5, 116–117
- ^ National Archives of Australia, AGLS Metadata Standard, accessed 7 January 2010, 
- ^ HBS is the FIFA host broadcaster
- ^ Host Broadcast Media Server and Related Applications
- ^ logs during sport events
- ^ <http://knb.ecoinformatics.org/software/eml/eml-2.0.1/index.html
- ^ http://metavist.djames.net/
- ^ http://knb.ecoinformatics.org/morphoportal.jsp
- ^ Sualeh Fatehi. "SchemaCrawler". SourceForge. http://schemacrawler.sourceforge.net/.
- Mercury: Metadata Management, Data Discovery and Access, managed by Oak Ridge National Laboratory Distributed Active Archive Center
- Metacrap: Putting the torch to seven straw-men of the meta-utopia – Cory Doctorow's opinion on the limitations of metadata on the Internet, 2001
- Retrieving Meta Data from Documents and Pictures Online - AnonWatch
- Understanding Metadata - NISO, 2004
- DataONE Investigator Toolkit
- Journal of Library Metadata (Routledge, Taylor & Francis Group). ISSN 1937-5034. http://www.informaworld.com/openurl?genre=journal&issn=1938-6389. Retrieved 8 January 2010.
- International Journal of Metadata, Semantics and Ontologies (IJMSO) (Inderscience Publishers). ISSN 1744-263X. http://www.inderscience.com/ijmso. Retrieved 8 January 2010.
- AFC2IC Vocabulary OneSource Tool
- On metadata and metacontent
- Managing Metadata blog
Software engineering Fields Concepts Orientations ModelsDevelopment modelsOther modelsModeling languages Software
- Kent Beck
- Grady Booch
- Fred Brooks
- Barry Boehm
- Ward Cunningham
- Ole-Johan Dahl
- Tom DeMarco
- Martin Fowler
- C. A. R. Hoare
- Watts Humphrey
- Michael A. Jackson
- Ivar Jacobson
- Craig Larman
- James Martin
- Bertrand Meyer
- David Parnas
- Winston W. Royce
- Colette Rolland
- James Rumbaugh
- Niklaus Wirth
- Edward Yourdon
- Victor Basili
Related fields Data warehouse Creating the data warehouseConceptsVariantsElementsFactDimensionFilling Using the data warehouseConceptsLanguagesTools RelatedPeopleProducts
- Comparison of OLAP Servers
- Data warehousing products and their producers
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