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Metadata
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In the 2010s, metadata typically refers to digital forms; however, even traditional card catalogues from the 1960s and 1970s are an example of metadata, as the cards contain information about the books in the library (author, title, subject, etc.).
Metadata is "data [information] that provides information about other data".[1] Three distinct types of metadata exist: descriptive metadata, structural metadata, and administrative metadata.[2]
Descriptive metadata describes a resource for purposes such as discovery and identification. It can include elements such as title, abstract, author, and keywords.
Structural metadata is 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. [3]
Administrative metadata provides information to help manage a resource, such as when and how it was created, file type and other technical information, and who can access it.[4]
Contents
[hide]
1 History
2 Definition
3 Types
4 Structures
4.1 Syntax
4.2 Hierarchical, linear and planar schemata
4.3 Hypermapping
4.4 Granularity
5 Standards
6 Use
6.1 Photographs
6.2 Telecommunications
6.3 Video
6.4 Web pages
7 Creation
7.1 Data virtualization
7.2 Statistics and census services
7.3 Library and information science
7.4 In museums
7.4.1 Usage
7.4.2 Standards
7.4.3 Cultural objects and art works
7.4.4 Museums and the Internet
7.5 Law
7.5.1 United States of America
7.5.2 Australia
7.6 In healthcare
7.7 Data warehousing
7.8 On the Internet
7.9 In broadcast industry
7.10 Geospatial
7.11 Ecological and environmental
7.12 Digital music
7.13 Cloud applications
8 Administration and management
8.1 Storage
8.2 Database management
9 See also
10 References
11 External links
History[edit]
Metadata was traditionally used in the card catalogs of libraries until the 1980s, when libraries converted their catalog data to digital databases. In the 2000s, as digital formats were becoming the prevalent way of storing data and information, metadata was also used to describe digital data using metadata standards.
There are different metadata standards for each different discipline (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.[5] A CD may include metadata providing information about the musicians, singers and songwriters whose work appears on the disc.
A principal purpose of metadata is to help users find relevant information and discover resources. Metadata also helps to organize electronic resources, provide digital identification, and support the archiving and preservation of resources. Metadata assists users in resource discovery by "allowing resources to be found by relevant criteria, identifying resources, bringing similar resources together, distinguishing dissimilar resources, and giving location information."[6] 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.[7]
In many countries, the metadata relating to emails, telephone calls, web pages, video traffic, IP connections and cell phone locations are routinely stored by government organizations.[8]
Definition[edit]
Metadata means "data about data". Although the "meta" prefix (from the Greek preposition and prefix μετά-) means "after" or "beyond", it is used to mean "about" in epistemology. 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 which can make tracking and working with specific data easier.[9] 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
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, the shutter speed, and other data.[10] 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.[11] These links are often called "Metatags", which were used as the primary factor in determining order for a web search until the late 1990s.[11] The reliance of metatags in web searches was decreased in the late 1990s because of "keyword stuffing".[11] Metatags were being largely misused to trick search engines into thinking some websites had more relevance in the search than they really did.[11]
Metadata can be stored and managed in a database, often called a metadata registry or metadata repository.[12] However, without context and a point of reference, it might be impossible to identify metadata just by looking at it.[13] For example: by itself, a database containing several numbers, all 13 digits long could be the results of calculations or a list of numbers to plug into an equation - without any other context, the numbers themselves can be perceived as the data. But if given the context that this database is a log of a book collection, those 13-digit numbers may now be identified as ISBNs - information that refers to the book, but is not itself the information within the book. The term "metadata" was coined in 1968 by Philip Bagley, in his book "Extension of Programming Language Concepts" where it is clear that he uses the term in the ISO 11179 "traditional" sense, which is "structural metadata" i.e. "data about the containers of data"; rather than the alternate sense "content about individual instances of data content" or metacontent, the type of data usually found in library catalogues.[14][15] 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".[16][page needed] While this is the generally accepted definition, various disciplines have adopted their own more specific explanation and uses of the term.
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.[17] Structural metadata describes the structure of database objects such as tables, columns, keys and indexes. Guide metadata helps humans find specific items and are usually expressed as a set of keywords in a natural language. According to Ralph Kimball metadata can be divided into 2 similar categories: technical metadata and business metadata. Technical metadata corresponds to internal metadata, and business metadata corresponds to external metadata. Kimball adds a third category, process metadata. On the other hand, NISO distinguishes among three types of metadata: descriptive, structural, and administrative.[16]
Descriptive metadata is typically used for discovery and identification, as information to search and locate an object, such as title, author, subjects, keywords, 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, including file type, or when and how the file was created. Two sub-types of administrative metadata are rights management metadata and preservation metadata. Rights management metadata explains intellectual property rights, while preservation metadata contains information to preserve and save a resource.[6][page needed]
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).[18] 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.[19]
A common example of (guide) metacontent is the bibliographic classification, the subject, the Dewey Decimal class number. There is always an implied statement in any "classification" of some object. To classify an object as, for example, Dewey class number 514 (Topology) (i.e. books having the number 514 on their spine) the implied statement is: "<book><subject heading><514>. This is a subject-predicate-object triple, or more importantly, a class-attribute-value triple. The first two elements of the triple (class, attribute) are pieces of some structural metadata having a defined semantic. The third element is a value, preferably from some controlled vocabulary, some reference (master) data. The combination of the metadata and master data elements results in a statement which is a metacontent statement i.e. "metacontent = metadata + master data". All of 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."[20] This is particularly relevant when considering search engines of the internet, such as Google. The process indexes pages 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 two dimensional, or planar, where each element is completely discrete from other elements but classified according to two orthogonal dimensions.[21]
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.[22]
Granularity[edit]
The degree to which the data or metadata is structured is referred to as its "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 greater levels 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.
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 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.[23] 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[24] which extends the MDR to support 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 catalogues. 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 which can be used to describe resources for the purposes of discovery. The original set of 15 classic[25] metadata terms, known as the Dublin Core Metadata Element Set[26] are endorsed in the following standards documents:
IETF RFC 5013[27]
ISO Standard 15836-2009[28]
NISO Standard Z39.85.[29]
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.[30] ”
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 and some is input by the photographer and/or software after downloading to a computer. Most digital cameras write metadata about model number, shutter speed, etc., and some enable you to edit it;[31] 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.
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)[32]
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 Intelligence agencies such as the NSA are keeping online metadata of millions of internet user for up to a year, regardless of whether or not they are 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 efficient search of the content is desirable. There are two 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.[33] In today's society most professional video editing software has access to metadata. Avid's MetaSync and Adobe's Bridge are two prime examples of this.[34]
Web pages[edit]
Web pages often include metadata in the form of meta tags. Description and keywords in meta tags are commonly used to describe the Web page's content. Meta elements also specify page description, key words, authors of the document, and when the document was last modified.[11] Web page metadata helps search engines and users to find the types of web pages they are looking for.
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.
Data virtualization[edit]
Main article: Data virtualization
Data virtualization has 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 work has had a large impact on efforts to build metadata systems in the statistical community[citation needed]. Several metadata standards[which?] are described, and their importance to statistical agencies is discussed. Applications of the standards[which?] at the Census Bureau, Environmental Protection Agency, Bureau of Labor Statistics, Statistics Canada, and many others are described[citation needed]. Emphasis is on the impact a metadata registry can have in a statistical agency.
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 format. Such data helps classify, aggregate, identify, and locate a particular book, DVD, magazine or any object a library might hold in its collection. Until the 1980s, many library catalogues used 3x5 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. 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 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.[35] 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.[36] 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.[37][38]
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.[39][40][page needed][41][page needed] Descriptive metadata is most commonly used in museum contexts for object identification and resource recovery purposes.[40]
Usage[edit]
Metadata is developed and applied within collecting institutions and museums in order to:
Facilitate resource discovery and execute search queries.[41]
Create digital archives that store information relating to various aspects of museum collections and cultural objects, and serves for archival and managerial purposes.[41]
Provide public audiences access to cultural objects through publishing digital content online.[40][41]
Standards[edit]
Many museums and cultural heritage centers recognize that given the diversity of art works and cultural objects, no single model or standard suffices to describe and catalogue cultural works.[39][40][41] 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.[40] These standards use HTML and XML markup languages for machine processing, publication and implementation.[40] The Anglo-American Cataloguing Rules (AACR), originally developed for characterizing books, have also been applied to cultural objects, works of art and architecture.[41] 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.[41] Scholars and professionals in the field note that the "quickly evolving landscape of standards and technologies" create challenges for cultural documentarians, specifically non-technically trained professionals.[42][page needed] Most collecting institutions and museums use a relational database to categorize cultural works and their images.[41] 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.[40][41] 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.[41]
Cultural objects and art works[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.[41] 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.[39][41] Additionally, museums often employ standardized commercial collection management software that prescribes and limits the ways in which archivists can describe artworks and cultural objects.[42] As well, collecting institutions and museums use Controlled Vocabularies to describe cultural objects and artworks in their collections.[40][41] Getty Vocabularies and the Library of Congress Controlled Vocabularies are reputable within the museum community and are recommended by CCO standards.[41] Museums are encouraged to use controlled vocabularies that are contextual and relevant to their collections and enhance the functionality of their digital information systems.[40][41] Controlled Vocabularies are beneficial within databases because they provide a high level of consistency, improving resource retrieval.[40][41] 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.[39][43]
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.[40] 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.[42] Collection Management Systems (CMS) and Digital Asset Management tools can be local or shared systems.[41] Digital Humanities scholars note many benefits of interoperability between museum databases and collections, while also acknowledging the difficulties achieving such interoperability.[42]
Law[edit]
United States of America[edit]
The examples and perspective in this article may not represent a worldwide view of the subject. You may improve this article, discuss the issue on the talk page, or create a new article, as appropriate. (March 2015) (Learn how and when to remove this template message)
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.[44] In October 2009, the Arizona Supreme Court has ruled that metadata records are public record.[45] Document metadata have proven particularly important in legal environments in which litigation has requested metadata, which 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.
Australia[edit]
In Australia, the need to strengthen national security has resulted in the introduction of a new metadata storage law.[46] This new law means that both security and policing agencies will be allowed to access up to two years of an individual's metadata, with the aim of making it easier to stop any terrorist attacks and serious crimes from happening.
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 the need to follow metadata standards despite research that supported these standards.[47]
Data warehousing[edit]
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.[48] 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[49][page needed] 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.[50] 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 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 a 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[51] 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 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 due to exploitation of metadata and the practice of search engine optimization, SEO, to improve rankings. See Meta element article for further discussion. This cautious attitude may be justified as people, according to Doctorow,[52] 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,[53] and Google has an announcement on its site showing the meta tags that its search engine understands.[54] 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.[55]
In broadcast industry[edit]
In 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 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 have 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 sport 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[56] who is in charge of organizing metadata through its International Broadcast Centre and its video servers. This metadata is recorded with the images and are entered by metadata operators (loggers) who associate in live metadata available in metadata grids through software (such as Multicam(LSM) or IPDirector used during the FIFA World Cup or Olympic Games).[57][58]
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 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,[59] or Dublin Core. Metadata editing tools exist to facilitate metadata generation (e.g. Metavist,[60] Mercury: Metadata Search System, Morpho[61]). Metadata should describe provenance of the data (where they originated, as well as any transformations the data underwent) and how to give credit for (cite) the data products.
Digital music[edit]
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.[3][dead link][4] Fourteen years later in 1996, a revision of the CD Red Book standard added CD-Text to carry additional metadata.[5] 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 labelled 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, catalogue and indicate ownership or copyright for a digital audio file, and its presence makes it much easier to locate a specific audio file within a group, 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,[62] 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 down side, 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.[63] 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.[64]
See also[edit]
Agris: International Information System for the Agricultural Sciences and Technology
Classification scheme
Crosswalk (metadata)
DataONE
Data Dictionary (aka metadata repository)
Dublin Core
Folksonomy
GEOMS – Generic Earth Observation Metadata Standard
Geospatial metadata
IPDirector
ISO/IEC 11179
Knowledge tag
Mercury: Metadata Search System
Meta element
Metadata Access Point Interface
Metadata discovery
Metadata facility for Java
Metadata from Wikiversity
Metadata publishing
Metadata registry
Metamathematics
METAFOR Common Metadata for Climate Modelling Digital Repositories
Microcontent
Microformat
Multicam (LSM)
Observations and Measurements
Ontology (computer science)
Official statistics
Paratext
Preservation Metadata
SDMX
Semantic Web
SGML
The Metadata Company
Universal Data Element Framework
Vocabulary OneSource
XSD
References[edit]
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Jump up ^ Zeng, Marcia (2004). "Metadata Types and Functions". NISO. Retrieved 5 October 2016.
Jump up ^ http://www.dlib.org/dlib/february97/cnri/02arms1.html
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Jump up ^ "Best Practices for Structural Metadata". University of Illinois. 15 December 2010. Retrieved 17 June 2016.
^ Jump up to: a b National Information Standards Organization; Rebecca Guenther; Jaqueline Radebaugh (2004). Understanding Metadata (PDF). Bethesda, MD: NISO Press. ISBN 1-880124-62-9. Retrieved 2 April 2014.
Jump up ^ https://www.schneier.com/essays/archives/2014/03/metadata_surveillanc.html
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Jump up ^ "A Guardian Guide to your Metadata". theguardian.com. Guardian News and Media Limited. 12 June 2013.
Jump up ^ "ADEO Imaging: TIFF Metadata". Retrieved 2013-05-20.
^ Jump up to: a b c d e Rouse, Margaret (July 2014). "Metadata". WhatIs. TechTarget.
Jump up ^ Hüner, K.; Otto, B.; Österle, H.: Collaborative management of business metadata, in: International Journal of Information Management, 2011
Jump up ^ "Metadata Standards And Metadata Registries: An Overview" (PDF). Retrieved 2011-12-23.
Jump up ^ Philip Bagley (November 1968). "Extension of programming language concepts" (PDF). Philadelphia: University City Science Center.
Jump up ^ "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: 267–307. doi:10.1016/0066-4138(74)90001-9.
^ Jump up to: a b NISO. Understanding Metadata (PDF). NISO Press. ISBN 1-880124-62-9. Retrieved 5 January 2010.
Jump up ^ 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.
Jump up ^ Cathro, Warwick (1997). "Metadata: an overview". Retrieved 6 January 2010.
Jump up ^ DCMI (5 October 2009). "Semantic Recommendations". Retrieved 6 January 2010.
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Jump up ^ "Types of Metadata". University of Melbourne. 15 August 2006. Archived from the original on 2009-10-24. Retrieved 6 January 2010.
Jump up ^ Kübler, Stefanie; Skala, Wolfdietrich; Voisard, Agnès. "THE DESIGN AND DEVELOPMENT OF A GEOLOGIC HYPERMAP PROTOTYPE" (PDF).
Jump up ^ "ISO/IEC 11179-1:2004 Information technology - Metadata registries (MDR) - Part 1: Framework". Iso.org. 2009-03-18. Retrieved 2011-12-23.
Jump up ^ "ISO/IEC 11179-3:2013 Information technology-Metadata registries - Part 3: Registry metamodel and basic attributes". iso.org. 2014.
Jump up ^ "DCMI Specifications". Dublincore.org. 2009-12-14. Retrieved 2013-08-17.
Jump up ^ "Dublin Core Metadata Element Set, Version 1.1". Dublincore.org. Retrieved 2013-08-17.
Jump up ^ J. Kunze, T. Baker (2007). "The Dublin Core Metadata Element Set". ietf.org. Retrieved 17 August 2013.
Jump up ^ "ISO 15836:2009 - Information and documentation - The Dublin Core metadata element set". Iso.org. 2009-02-18. Retrieved 2013-08-17.
Jump up ^ "NISO Standards - National Information Standards Organization". Niso.org. 2007-05-22. Retrieved 2013-08-17.
Jump up ^ "What's the Next Big Thing on the Web? It May Be a Small, Simple Thing -- Microformats". Knowledge@Wharton. Wharton School of the University of Pennsylvania. 2005-07-27.
Jump up ^ "How To Copyright Your Photos With Metadata". Guru Camera. gurucamera.com.
Jump up ^ "VRA Core Support Pages". Visual Resource Association Foundation. Visual Resource Association Foundation. Retrieved 27 February 2016.
Jump up ^ Webcase, Weblog (2011). "Examining video file metadata". Retrieved 25 November 2015.
Jump up ^ Oak Tree Press (2011). "Metadata for Video". Retrieved 25 November 2015.
Jump up ^ National Archives of Australia (2002). "AGLS Metadata Element Set - Part 2: Usage Guide - A non-technical guide to using AGLS metadata for describing resources". Retrieved 17 March 2010.
Jump up ^ Solodovnik, Iryna (2011). "Metadata issues in Digital Libraries: key concepts and perspectives". JLIS.it: Italian Journal of Library, Archives and Information Science. University of Florence. 2 (2). doi:10.4403/jlis.it-4663. Retrieved 29 June 2013.
Jump up ^ Library of Congress Network Development and MARC Standards Office (2005-09-08). "Library of Congress Washington DC on metadata". Loc.gov. Retrieved 2011-12-23.
Jump up ^ "Deutsche Nationalbibliothek Frankfurt on metadata".
^ Jump up to: a b c d Zange, Charles S. (31 January 2015). "Community makers, major museums, and the Keet S'aaxw: Learning about the role of museums in interpreting cultural objects". Museums and the Web.
^ Jump up to: a b c d e f g h i j k Baca, Murtha (2006). Cataloging cultural objects: a guide to describing cultural works and their images. Visual Resources Association. Visual Resources Association.
^ Jump up to: a b c d e f g h i j k l m n o p q Baca, Murtha (2008). Introduction to Metadata: Second Edition. Los Angeles: Getty Information Institute. Los Angeles: Getty Information Institute.
^ Jump up to: a b c d Hooland, Seth Van; Verborgh, Ruben (2014). Linked Data for Libraries, Archives and Museums: How to Clean, Link and Publish Your Metadata. London: Facet.
Jump up ^ Srinivasan, Ramesh (December 2006). "Indigenous, ethnic and cultural articulations of new media". International Journal of Cultural Studies. 9 (4). doi:10.1177/1367877906069899.
Jump up ^ 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. Retrieved 8 January 2010.
Jump up ^ Walsh, Jim (30 October 2009). "Ariz. Supreme Court rules electronic data is public record". The Arizona Republic. Phoenix, Arizona. Retrieved 8 January 2010.
Jump up ^ Senate passes controversial metadata laws
Jump up ^ 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
Jump up ^ Inmon, W.H. Tech Topic: What is a Data Warehouse? Prism Solutions. Volume 1. 1995.
Jump up ^ Kimball, Ralph (2008). The Data Warehouse Lifecycle Toolkit (Second ed.). New York: Wiley. pp. 10, 115–117, 131–132, 140, 154–155. ISBN 978-0-470-14977-5.
Jump up ^ Kimball 2008, pp. 116–117
Jump up ^ National Archives of Australia, AGLS Metadata Standard, accessed 7 January 2010, [1]
Jump up ^ Metacrap: Putting the torch to seven straw-men of the meta-utopia http://www.well.com/~doctorow/metacrap.htm
Jump up ^ The impact of webpage content characteristics on webpage visibility in search engine results http://web.simmons.edu/~braun/467/part_1.pdf
Jump up ^ "Meta tags that Google understands". Google.com. Retrieved 2014-05-22.
Jump up ^ "Swiftype-specific Meta Tags". Swiftype Documentation. Swiftype. 3 October 2014.
Jump up ^ "HBS is the FIFA host broadcaster". Hbs.tv. 2011-08-06. Retrieved 2011-12-23.
Jump up ^ "Host Broadcast Media Server and Related Applications" (PDF). Archived from the original (PDF) on 2 November 2011. Retrieved 2013-08-17.
Jump up ^ "logs during sport events". Broadcastengineering.com. Retrieved 2011-12-23.
Jump up ^ [2] Archived 23 April 2011 at the Wayback Machine.
Jump up ^ "Metavist 2". Metavist.djames.net. Retrieved 2011-12-23.
Jump up ^ "KNB Data :: Morpho". Knb.ecoinformatics.org. 2009-05-20. Retrieved 2011-12-23.
Jump up ^ O'Neill, Dan. "ID3.org".
Jump up ^ De Sutter, Robbie; Notebaert, Stijn; Van de Walle, Rik (September 2006). "Evaluation of Metadata Standards in the Context of Digital Audio-Visual Libraries". In Gonzalo, Julio; Thanos, Constantino; Verdejo, M. Felisa; Carrasco, Rafael. Research and Advanced Technology for Digital Libraries: 10th European Conference, EDCL 2006. Springer. p. 226. ISBN 978-3540446361.
Jump up ^ Sualeh Fatehi. "SchemaCrawler". SourceForge.
External links[edit]
Look up metadata in Wiktionary, the free dictionary.
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 seven 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 at the Wayback Machine (archived 26 January 2013) (PDF, archived version)
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Cash flow statement
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In financial accounting, a cash flow statement, also known as statement of cash flows,[1] is a financial statement that shows how changes in balance sheet accounts and income affect cash and cash equivalents, and breaks the analysis down to operating, investing and financing activities. Essentially, the cash flow statement is concerned with the flow of cash in and out of the business. The statement captures both the current operating results and the accompanying changes in the balance sheet.[1] As an analytical tool, the statement of cash flows is useful in determining the short-term viability of a company, particularly its ability to pay bills. International Accounting Standard 7 (IAS 7), is the International Accounting Standard that deals with cash flow statements.
People and groups interested in cash flow statements include:
Accounting personnel, who need to know whether the organization will be able to cover payroll and other immediate expenses
Potential lenders or creditors, who want a clear picture of a company's ability to repay
Potential investors, who need to judge whether the company is financially sound
Potential employees or contractors, who need to know whether the company will be able to afford compensation
Shareholders of the business.
Contents
[hide]
1 Purpose
2 History and variations
3 Cash flow activities
3.1 Operating activities
3.2 Investing activities
3.3 Financing activities
4 Disclosure of non-cash activities
5 Preparation methods
5.1 Direct method
5.2 Indirect method
5.2.1 Rules (operating activities)
5.2.2 Rules (financing activities)
6 See also
7 Notes and references
Purpose[edit]
Statement of Cash Flow - Simple Example
for the period 1 Jan 2006 to 31 Dec 2006
Cash flow from operations $4,000
Cash flow from investing ($1,000)
Cash flow from financing ($2,000)
Net cash flow $1,000
Parentheses indicate negative values
The cash flow statement was previously known as the flow of funds statement.[2] The cash flow statement reflects a firm's liquidity.
The statement of financial position is a snapshot of a firm's financial resources and obligations at a single point in time, and the income statement summarizes a firm's financial transactions over an interval of time. These two financial statements reflect the accrual basis accounting used by firms to match revenues with the expenses associated with generating those revenues. The cash flow statement includes only inflows and outflows of cash and cash equivalents; it excludes transactions that do not directly affect cash receipts and payments. These non-cash transactions include depreciation or write-offs on bad debts or credit losses to name a few.[3] The cash flow statement is a cash basis report on three types of financial activities: operating activities, investing activities, and financing activities. Non-cash activities are usually reported in footnotes.
The cash flow statement is intended to[4]
provide information on a firm's liquidity and solvency and its ability to change cash flows in future circumstances
provide additional information for evaluating changes in assets, liabilities and equity
improve the comparability of different firms' operating performance by eliminating the effects of different accounting methods
indicate the amount, timing and probability of future cash flows
The cash flow statement has been adopted as a standard financial statement because it eliminates allocations, which might be derived from different accounting methods, such as various timeframes for depreciating fixed assets.[5]
History and variations[edit]
Cash basis financial statements were very common before accrual basis financial statements. The "flow of funds" statements of the past were cash flow statements.
In 1863, the Dowlais Iron Company had recovered from a business slump, but had no cash to invest for a new blast furnace, despite having made a profit. To explain why there were no funds to invest, the manager made a new financial statement that was called a comparison balance sheet, which showed that the company was holding too much inventory. This new financial statement was the genesis of cash flow statement that is used today.[6]
In the United States in 1973, the Financial Accounting Standards Board (FASB) defined rules that made it mandatory under Generally Accepted Accounting Principles (US GAAP) to report sources and uses of funds, but the definition of "funds" was not clear. Net working capital might be cash or might be the difference between current assets and current liabilities. From the late 1970 to the mid-1980s, the FASB discussed the usefulness of predicting future cash flows.[7] In 1987, FASB Statement No. 95 (FAS 95) mandated that firms provide cash flow statements.[8] In 1992, the International Accounting Standards Board issued International Accounting Standard 7 (IAS 7), Cash Flow Statement, which became effective in 1994, mandating that firms provide cash flow statements.[9]
US GAAP and IAS 7 rules for cash flow statements are similar, but some of the differences are:
IAS 7 requires that the cash flow statement include changes in both cash and cash equivalents. US GAAP permits using cash alone or cash and cash equivalents.[5]
IAS 7 permits bank borrowings (overdraft) in certain countries to be included in cash equivalents rather than being considered a part of financing activities.[10]
IAS 7 allows interest paid to be included in operating activities or financing activities. US GAAP requires that interest paid be included in operating activities.[11]
US GAAP (FAS 95) requires that when the direct method is used to present the operating activities of the cash flow statement, a supplemental schedule must also present a cash flow statement using the indirect method. The IASC strongly recommends the direct method but allows either method. The IASC considers the indirect method less clear to users of financial statements. Cash flow statements are most commonly prepared using the indirect method, which is not especially useful in projecting future cash flows.
Cash flow activities[edit]
The cash flow statement is partitioned into three segments, namely:
cash flow resulting from operating activities;
cash flow resulting from investing activities;
cash flow resulting from financing activities.
The money coming into the business is called cash inflow, and money going out from the business is called cash outflow.
Operating activities[edit]
Operating activities include the production, sales and delivery of the company's product as well as collecting payment from its customers. This could include purchasing raw materials, building inventory, advertising, and shipping the product.
Under IAS 7, operating cash flows include:[11]
Receipts for the sale of loans, debt or equity instruments in a trading portfolio
Interest received on loans
Payments to suppliers for goods and services
Payments to employees or on behalf of employees
Interest payments (alternatively, this can be reported under financing activities in IAS 7)
buying Merchandise
Items which are added back to [or subtracted from, as appropriate] the net income figure (which is found on the Income Statement) to arrive at cash flows from operations generally include:
Depreciation (loss of tangible asset value over time)
Deferred tax
Amortization (loss of intangible asset value over time)
Any gains or losses associated with the sale of a non-current asset, because associated cash flows do not belong in the operating section (unrealized gains/losses are also added back from the income statement).
Dividends received
Investing activities[edit]
Examples of Investing activities are
Purchase or Sale of an asset (assets can be land, building, equipment, marketable securities, etc.)
Loans made to suppliers or received from customers
Payments related to mergers and acquisition.
Financing activities[edit]
Financing activities include the inflow of cash from investors such as banks and shareholders, as well as the outflow of cash to shareholders as dividends as the company generates income. Other activities which impact the long-term liabilities and equity of the company are also listed in the financing activities section of the cash flow statement.
Under IAS 7,
Payments of dividends
Payments for repurchase of company shares
For non-profit organizations, receipts of donor-restricted cash that is limited to long-term purposes
Items under the financing activities section include:
Dividends paid
Sale or repurchase of the company's stock
Net borrowings
Repayment of debt principal, including capital leases
Disclosure of non-cash activities[edit]
Under IAS 7, non-cash investing and financing activities are disclosed in footnotes to the financial statements. Under US General Accepted Accounting Principles (GAAP), non-cash activities may be disclosed in a footnote or within the cash flow statement itself. Non-cash financing activities may include[11]
Leasing to purchase an asset
Converting debt to equity
Exchanging non-cash assets or liabilities for other non-cash assets or liabilities
Issuing share
Payment of dividend taxes in exchange for assets
Preparation methods[edit]
The direct method of preparing a cash flow statement results in a more easily understood report.[12] The indirect method is almost universally used, because FAS 95 requires a supplementary report similar to the indirect method if a company chooses to use the direct method.
Direct method[edit]
The direct method for creating a cash flow statement reports major classes of gross cash receipts and payments. Under IAS 7, dividends received may be reported under operating activities or under investing activities. If taxes paid are directly linked to operating activities, they are reported under operating activities; if the taxes are directly linked to investing activities or financing activities, they are reported under investing or financing activities. Generally Accepted Accounting Principles (GAAP) vary from International Financial Reporting Standards in that under GAAP rules, dividends received from a company's investing activities is reported as an "operating activity," not an "investing activity."[13]
Sample cash flow statement using the direct method[14]
Cash flows from (used in) operating activities
Cash receipts from customers 9,500
Cash paid to suppliers and employees (2,000)
Cash generated from operations (sum) 7,500
Interest paid (2,000)
Income taxes paid (3,000)
Net cash flows from operating activities 2,500
Cash flows from (used in) investing activities
Proceeds from the sale of equipment 7,500
Dividends received 3,000
Net cash flows from investing activities 10,500
Cash flows from (used in) financing activities
Dividends paid (2,500)
Net cash flows used in financing activities (2,500)
.
Net increase in cash and cash equivalents 10,500
Cash and cash equivalents, beginning of year 1,000
Cash and cash equivalents, end of year $11,500
Indirect method[edit]
The indirect method uses net-income as a starting point, makes adjustments for all transactions for non-cash items, then adjusts from all cash-based transactions. An increase in an asset account is subtracted from net income, and an increase in a liability account is added back to net income. This method converts accrual-basis net income (or loss) into cash flow by using a series of additions and deductions.[15]
Rules (operating activities)[edit]
*Non-cash expenses must be added back to NI. Such expenses may be represented on the balance sheet as decreases in long term asset accounts. Thus decreases in fixed assets increase NI.
To Find Cash Flows
from Operating Activities
using the Balance Sheet and Net Income
For Increases in
Net Inc Adj
Current Assets (Non-Cash) Decrease
Current Liabilities Increase
For All Non-Cash...
*Expenses (Decreases in Fixed Assets) Increase
The following rules can be followed to calculate Cash Flows from Operating Activities when given only a two-year comparative balance sheet and the Net Income figure. Cash Flows from Operating Activities can be found by adjusting Net Income relative to the change in beginning and ending balances of Current Assets, Current Liabilities, and sometimes Long Term Assets. When comparing the change in long term assets over a year, the accountant must be certain that these changes were caused entirely by their devaluation rather than purchases or sales (i.e. they must be operating items not providing or using cash) or if they are nonoperating items.[16]
Decrease in non-cash current assets are added to net income
Increase in non-cash current asset are subtracted from net income
Increase in current liabilities are added to net income
Decrease in current liabilities are subtracted from net income
Expenses with no cash outflows are added back to net income (depreciation and/or amortization expense are the only operating items that have no effect on cash flows in the period)
Revenues with no cash inflows are subtracted from net income
Non operating losses are added back to net income
Non operating gains are subtracted from net income
The intricacies of this procedure might be seen as,
Net Cash Flows from Operating Activities = Net Income + Rule Items {\displaystyle {\text{Net Cash Flows from Operating Activities}}={\text{Net Income}}+{\text{Rule Items}}}
For example, consider a company that has a net income of $100 this year, and its A/R increased by $25 since the beginning of the year. If the balances of all other current assets, long term assets and current liabilities did not change over the year, the cash flows could be determined by the rules above as $100 – $25 = Cash Flows from Operating Activities = $75. The logic is that, if the company made $100 that year (net income), and they are using the accrual accounting system (not cash based) then any income they generated that year which has not yet been paid for in cash should be subtracted from the net income figure in order to find cash flows from operating activities. And the increase in A/R meant that $25 of sales occurred on credit and have not yet been paid for in cash.
In the case of finding Cash Flows when there is a change in a fixed asset account, say the Buildings and Equipment account decreases, the change is added back to Net Income. The reasoning behind this is that because Net Income is calculated by, Net Income = Rev - Cogs - Depreciation Exp - Other Exp then the Net Income figure will be decreased by the building's depreciation that year. This depreciation is not associated with an exchange of cash, therefore the depreciation is added back into net income to remove the non-cash activity.
Rules (financing activities)[edit]
Finding the Cash Flows from Financing Activities is much more intuitive and needs little explanation. Generally, the things to account for are financing activities:
Include as outflows, reductions of long term notes payable (as would represent the cash repayment of debt on the balance sheet)
Or as inflows, the issuance of new notes payable
Include as outflows, all dividends paid by the entity to outside parties
Or as inflows, dividend payments received from outside parties
Include as outflows, the purchase of notes stocks or bonds
Or as inflows, the receipt of payments on such financing vehicles.[citation needed]
In the case of more advanced accounting situations, such as when dealing with subsidiaries, the accountant must
Exclude intra-company dividend payments.
Exclude intra-company bond interest.[citation needed]
A traditional equation for this might look something like,
Net Cash Flows from Financing Activities = [ Dividends received from 3 r d parties ] − [ Dividends paid to 3 r d parties ] − [ Dividends paid to NCI but not intracompany dividend payments ] {\displaystyle {\begin{alignedat}{2}{\text{Net Cash Flows from Financing Activities}}=&\left[{\text{Dividends received from }}3^{\rm {rd}}{\text{ parties}}\right]\\&-\left[{\text{Dividends paid to }}3^{\rm {rd}}{\text{ parties}}\right]\\&-[{\text{Dividends paid to NCI but not}}\\&{\text{intracompany dividend payments}}]\end{alignedat}}}
Example: cash flow of XYZ:[17][18][19]
XYZ co. Ltd. Cash Flow Statement
(all numbers in millions of Rs.)
Period ending 31 Mar 2010 31 Mar 2009 31 Mar 2008
Net income 21,538 24,589 17,046
Operating activities, cash flows provided by or used in:
Depreciation and amortization 2,790 2,592 2,747
Adjustments to net income 4,617 621 2,910
Decrease (increase) in accounts receivable 12,503 17,236 --
Increase (decrease) in liabilities (A/P, taxes payable) 131,622 19,822 37,856
Decrease (increase) in inventories -- -- --
Increase (decrease) in other operating activities (173,057) (33,061) (62,963)
Net cash flow from operating activities 13 31,799 (2,404)
Investing activities, cash flows provided by or used in:
Capital expenditures (4,035) (3,724) (3,011)
Investments (201,777) (71,710) (75,649)
Other cash flows from investing activities 1,606 17,009 (571)
Net cash flows from investing activities (204,206) (58,425) (79,231)
Financing activities, cash flows provided by or used in:
Dividends paid (9,826) (9,188) (8,375)
Sale (repurchase) of stock (5,327) (12,090) 133
Increase (decrease) in debt 101,122 26,651 21,204
Other cash flows from financing activities 120,461 27,910 70,349
Net cash flows from financing activities 206,430 33,283 83,311
Effect of exchange rate changes 645 (1,840) 731
Net increase (decrease) in cash and cash equivalents 2,882 4,817 2,407
See also[edit]
Cash flow
Income statement
Balance sheet
statement of changes in equity
Notes and references[edit]
^ Jump up to: a b Helfert, Erich A. "The Nature of Financial Statements: The Cash Flow Statement". Financial Analysis - Tools and Techniques - A Guide for Managers.
Jump up ^ Bodie, Zane; Alex Kane; Alan J. Marcus (2004). Essentials of Investments, 5th ed. McGraw-Hill Irwin. p. 455. ISBN 0-07-251077-3.
Jump up ^ Epstein, Barry J.; Eva K. Jermakowicz (2007). Interpretation and Application of International Financial Reporting Standards. John Wiley & Sons. pp. 91–97. ISBN 978-0-471-79823-1.
Jump up ^ Epstein, pp.90-91.
^ Jump up to: a b Epstein, p. 91.
Jump up ^ Watanabe, Izumi: The evolution of Income Accounting in Eighteenth and Nineteenth Century Britain, Osaka University of Economics, Vol.57, No. 5, January 2007, p.27-30 [1]
Jump up ^ Epstein, p. 90.
Jump up ^ Bodie, p.454.
Jump up ^ Epstein, p. 88
Jump up ^ Epstein, p. 92.
^ Jump up to: a b c Epstein, p. 93.
Jump up ^ Epstein, p. 95.
Jump up ^ http://smallbusiness.chron.com/operating-activity-dividends-gaap-38254.html
Jump up ^ Epstein, p. 101
Jump up ^ Epstein, p. 94.
Jump up ^ Wild, John Paul. Fundamental Accounting Principles (18th ed.). New York: McGraw-Hill Companies. pp. 630–633. ISBN 0-07-299653-6.
Jump up ^ Yahoo finance report on Citigroup
Jump up ^ Citigroup finance report
Jump up ^ Bodie, p. 455.
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values: {\displaystyle \begin{alignat}{2}\text{Net Cash Flows from Financing Activities} = & \left[\text{Dividends received from }3^{{\rm rd}}\text{ parties}\right]\\   & -\left[\text{Dividends paid to }3^{{\rm rd}}\text{ parties}\right]\\ & - [\text{Dividends paid to NCI but not} \\ & \text{intracompany dividend payments}] \end{alignat}}

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