Data Steward
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Data Steward
A data steward is an oversight or data governance role within an organization, and is responsible for ensuring the quality and fitness for purpose of the organization's data assets, including the metadata for those data assets. A data steward may share some responsibilities with a data custodian, such as the awareness, accessibility, release, appropriate use, security and management of data. A data steward would also participate in the development and implementation of data assets. A data steward may seek to improve the quality and fitness for purpose of other data assets their organization depends upon but is not responsible for. Data stewards have a specialist role that utilizes an organization's data governance processes, policies, guidelines and responsibilities for administering an organizations' entire data in compliance with policy and/or regulatory obligations. The overall objective of a data steward is the data quality of the data assets, datasets, data records and data ...
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Data Governance
Data governance is a term used on both a macro and a micro level. The former is a political concept and forms part of international relations and Internet governance; the latter is a data management concept and forms part of corporate data governance. Macro level On the macro level, data governance refers to the governing of cross-border data flows by countries, and hence is more precisely called ''international data governance''. This new field consists of "norms, principles and rules governing various types of data." Micro level Here the focus is on an individual company. Here data governance is a data management concept concerning the capability that enables an organization to ensure that high data quality exists throughout the complete lifecycle of the data, and data controls are implemented that support business objectives. The key focus areas of data governance include availability, usability, consistency, data integrity and data security, standard compliance and inc ...
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TU Delft Library
The TU Delft Library is the main library of the Delft University of Technology (TU Delft), located in Delft, Netherlands. It was designed by the Dutch architecture firm Mecanoo and built in 1997. It is the largest technical scientific library in the Netherlands. Building The library was designed in the early years of Mecanoo, whose founding members, Erick van Egeraat, Henk Döll, Francine Houben, Roelf Steenhuis and Chris de Weijer, were graduates of TU Delft. An example of a building that acts as landscape, the library is partially underground with a 15% sloped plane and a grass-covered green roof on top. Protruding from the artificial hill there is a steel cone which acts as a source of daylight and is meant to symbolize technical engineering. Although a successful exterior element, the cone was more unsatisfactory in the interior and received some criticism in architectural reviews. A series of columns distribute heat and light throughout the interior. The green roof system ...
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Knowledge Representation
Knowledge representation and reasoning (KRR, KR&R, KR²) is the field of artificial intelligence (AI) dedicated to representing information about the world in a form that a computer system can use to solve complex tasks such as diagnosing a medical condition or having a dialog in a natural language. Knowledge representation incorporates findings from psychology about how humans solve problems and represent knowledge in order to design formalisms that will make complex systems easier to design and build. Knowledge representation and reasoning also incorporates findings from logic to automate various kinds of ''reasoning'', such as the application of rules or the relations of sets and subsets. Examples of knowledge representation formalisms include semantic nets, systems architecture, frames, rules, and ontologies. Examples of automated reasoning engines include inference engines, theorem provers, and classifiers. History The earliest work in computerized knowledge rep ...
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Information Technology Governance
Information technology (IT) governance is a subset discipline of corporate governance, focused on information technology (IT) and its performance and risk management. The interest in IT governance is due to the ongoing need within organizations to focus value creation efforts on an organization's strategic objectives and to better manage the performance of those responsible for creating this value in the best interest of all stakeholders. It has evolved from The Principles of Scientific Management, Total Quality Management and ISO 9001 Quality management system. Historically, board-level executives deferred key IT decisions to the company's IT management and business leaders. Short-term goals of those responsible for managing IT can be in conflict with the best interests of other stakeholders unless proper oversight is established. IT governance systematically involves everyone: board members, executive management, staff, customers, communities, investors and regulators. An ...
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Data Management
Data management comprises all disciplines related to handling data as a valuable resource. Concept The concept of data management arose in the 1980s as technology moved from sequential processing (first punched cards, then magnetic tape) to random access storage. Since it was now possible to store a discrete fact and quickly access it using random access disk technology, those suggesting that data management was more important than business process management used arguments such as "a customer's home address is stored in 75 (or some other large number) places in our computer systems." However, during this period, random access processing was not competitively fast, so those suggesting "process management" was more important than "data management" used batch processing time as their primary argument. As application software evolved into real-time, interactive usage, it became obvious that both management processes were important. If the data was not well defined, the data ...
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Ralph Kimball
Ralph Kimball (born July 18, 1944) is an author on the subject of data warehousing and business intelligence. He is one of the original architects of data warehousing and is known for long-term convictions that data warehouses must be designed to be understandable and fast. His bottom-up methodology, also known as dimensional modeling or the Kimball methodology, is one of the two main data warehousing methodologies alongside Bill Inmon. He is the principal author of the best-selling books ''The Data Warehouse Toolkit'', ''The Data Warehouse Lifecycle Toolkit'', ''The Data Warehouse ETL Toolkit'' and ''The Kimball Group Reader'', published by Wiley and Sons. Career After receiving a Ph.D. in 1973 from Stanford University in electrical engineering (specializing in man-machine systems), Ralph joined the Xerox Palo Alto Research Center (PARC). At PARC Ralph was a principal designer of the Xerox Star Workstation, the first commercial product to use mice, icons and windows. Kimball the ...
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ISO/IEC 11179
The ISO/IEC 11179 Metadata Registry (MDR) standard is an international ISO/IEC standard for representing metadata for an organization in a metadata registry. It documents the standardization and registration of metadata to make data understandable and shareable. Intended purpose Organizations exchange data between computer systems precisely using enterprise application integration technologies. Completed transactions are often transferred to separate data warehouse and business rules systems with structures designed to support data for analysis. A de facto standard model for data integration platforms is the Common Warehouse Metamodel (CWM). Data integration is often also solved as a problem of data, rather than metadata, with the use of so-called master data. ISO/IEC 11179 claims that it is a standard for metadata-driven exchange of data in an heterogeneous environment, based on exact definitions of data. Structure of an ISO/IEC 11179 metadata registry The ISO/IEC 11179 mo ...
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Representation Term
A representation term is a word, or a combination of words, that semantically represent the data type (value domain) of a data element. A representation term is commonly referred to as a ''class word'' by those familiar with data dictionaries. ISO/IEC 11179-5:2005 defines ''representation term'' as a ''designation of an instance of a representation class'' As used in ISO/IEC 11179, the representation term is that part of a data element name that provides a semantic pointer to the underlying data type. A ''Representation class'' is a class of representations. This ''representation class'' provides a way to classify or group data elements. A ''Representation Term'' may be thought of as an attribute of a data element in a metadata registry that classifies the data element according to the type of data stored in the data element. Representation terms are typically "approved" by the organization or standards body using them. For example, the UN publishes its approved list as part ...
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Data Element Definition
In metadata, a data element definition is a human readable phrase or sentence associated with a data element within a data dictionary that describes the meaning or semantics of a data element. Data element definitions are critical for external users of any data system. Good definitions can dramatically ease the process of mapping one set of data into another set of data. This is a core feature of distributed computing and intelligent agent development. There are several guidelines that should be followed when creating high-quality data element definitions. Properties of clear definitions A good definition is: # Precise - The definition should use words that have a precise meaning. Try to avoid words that have multiple meanings or multiple word senses. The definition should use the shortest description. The definition should not use the term you are trying to define in the definition itself. This is known as a circular definition. # Distinct - The definition should differentia ...
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Data Element
In metadata, the term data element is an atomic unit of data that has precise meaning or precise semantics. A data element has: # An identification such as a data element name # A clear data element definition # One or more representation terms # Optional enumerated values Code (metadata) # A list of synonyms to data elements in other metadata registries Synonym ring Data elements usage can be discovered by inspection of software applications or application data files through a process of manual or automated Application Discovery and Understanding. Once data elements are discovered they can be registered in a metadata registry. In telecommunication, the term data element has the following components: #A named unit of data that, in some contexts, is considered indivisible and in other contexts may consist of data items. #A named identifier of each of the entities and their attributes that are represented in a database. #A basic unit of information built on standard structures ...
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Data Curation
Data curation is the organization and integration of data collected from various sources. It involves annotation, publication and presentation of the data such that the value of the data is maintained over time, and the data remains available for reuse and preservation. Data curation includes "all the processes needed for principled and controlled data creation, maintenance, and management, together with the capacity to add value to data". In science, data curation may indicate the process of extraction of important information from scientific texts, such as research articles by experts, to be converted into an electronic format, such as an entry of a biological database. In the modern era of big data, the curation of data has become more prominent, particularly for software processing high volume and complex data systems. The term is also used in historical occasions and the humanities, where increasing cultural and scholarly data from digital humanities projects requires the expe ...
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Metadata Registry
A metadata registry is a central location in an organization where metadata definitions are stored and maintained in a controlled method. A metadata repository is the database where metadata is stored. The registry also adds relationships with related metadata types. A metadata engine collects, stores and analyzes information about data and metadata (data about data) in use within a domain. Use of metadata registries Metadata registries are used whenever data must be used consistently within an organization or group of organizations. Examples of these situations include: * Organizations that transmit data using structures such as XML, Web Services or EDI * Organizations that need consistent definitions of data across time, between databases, between organizations or between processes, for example when an organization builds a data warehouse * Organizations that are attempting to break down "silos" of information captured within applications or proprietary file formats Central ...
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