Business semantics management

Business Semantics Management [1] [2] (BSM) encompasses the technology, methodology, organization, and culture that brings business stakeholders together to collaboratively realize the reconciliation of their heterogeneous metadata; and consequently the application of the derived business semantics patterns to establish semantic alignment[3] between the underlying data structures.

BSM is established by two complementary process cycles each grouping a number of activities. The first cycle is the semantic reconciliation cycle, and the second cycle is the semantic application cycle. The two cycles are tied together by the unification process. This double process cycle is iteratively applied until an optimal balance of differences and commonalities between stakeholders are reached that meets the semantic integration requirements. This approach is based on research on community-based ontology engineering ([1][2]) that is validated in European projects, government and industry.

Semantic Reconciliation

Semantic reconciliation is a process cycle constituted of four subsequent activities: scope, create, refine, and articulate. First, the community is scoped: user roles and affordances are appointed. Next, relevant facts are collected from documentation such as, e.g., natural language descriptions, (legacy) logical schemas, or other metadata and consequently decomposing this scope in elicitation contexts. The deliverable of scoping is an initial upper common ontology that organizes the key upper common patterns that are shared and accepted by the community. These upper common patterns define the current semantic interoperability requirements of the community. Once the community is scoped, all stakeholders syntactically refine and semantically articulate these upper common patterns.

Unification

During unification, a new proposal for the next version of the upper common ontology is produced, aligning relevant parts from the common and divergent stakeholder perspectives. If the semantic reconciliation results in a number of reusable language-neutral and context-independent patterns for constructing business semantics that are articulated with informal meaning descriptions, then the unification is worthwhile.

Semantic Application

Semantic application is a process cycle constituted of two subsequent activities: select and commit where the scoped information systems are committed to selected consolidated business semantic patterns. This is done by first selecting relevant patterns from the pattern base. Next, the interpretation of this selection is semantically constrained. Finally, the various scoped sources and services are mapped on (read: committed to) this selection. The selection and axiomatization of this selection should approximate the intended business semantics. This can be verified by automatically verbalization into natural language, and validation of the unlocked data. Validation or deprecation of the commitments may result in another iteration of the semantic reconciliation cycle.

Business semantics

Business semantics [1] are the information concepts that live in the organization, understandable for both business and IT. Business Semantics describe the business concepts as they are used and needed by the business instead of describing the information from a technical point of view.

One important aspect of business semantics is that they are shared between many disparate data sources. Many data sources share the same semantics but have different syntax, or format to describe the same concepts.

The way these business semantics are described is less important. Several approaches can be used such as UML, object-role modeling, XML, etc. This corresponds to Robert Meersman’s statement that semantics are "a (set of) mapping(s) from your representation language to agreed concepts (objects, relationships, behavior) in the real-world".[4] In the construction of information systems, semantics have always been crucial. In previous approaches, these semantics were left implicit (i.e. In the mind of reader or writer), hidden away in the implementation itself (e.g., in a database table or column code) or informally captured in textual documentation.[5] According to Dave McComb, "The scale and scope of our systems and the amount of information we now have to deal with are straining that model."[6]

Nowadays, information systems need to interact in a more open manner, and it becomes crucial to formally represent and apply the semantics these systems are concerned with.

Application

Business semantics management empowers all stakeholders in the organization by a consistent and aligned definition of the important information assets of the organization.

The available business semantics can be leveraged in the so-called business/social layer of the organization. They can for example be coupled to a content management application to provide the business with a consistent business vocabulary or enable better navigation or classification of information, leveraged by enterprise search engines to make richer semantic-web-ready websites, etc..

Business semantics can also be used to increase operational efficiency in the technical/operation layer of the organization. It provides an abstracted way to access and deliver data in a more efficient manner. In that respect, it is similar to Enterprise Information Integration (EII) with the added benefit that the shared models are not described in technical terms but in a way that is easily understood by the business.

Collibra is the first organization to commercialize the idea behind business semantics management. Collibra's approach to Business Semantics Management is based on DOGMA, a research project at the Vrije Universiteit Brussel.

See also
References
  1. De Leenheer, Pieter (2010). "Business Semantics Management: A Case Study for Competency-centric HRM". Elsevier.
  2. De Leenheer, Pieter (2009). "On community-based Ontology Evolution. PhD thesis, Vrije Universiteit Brussel".
  3. "Information Management Resources - Information Management" (PDF).
  4. Sheth, Amit (1997). "Data Semantics: what, where and how?". Proceedings of the 6th IFIP Working Conference on Data Semantics (DS-6). Chapman and Hall. pp. 601–610.
  5. Morgan, Tony (2005). "Expressing Business Semantics" (PDF). Presentation at the European Semantic Web Conference (2005).
  6. DMReview.com. "Why is Business Semantics the New Hot Topic?". Retrieved 23 November 2008.
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Symantec

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Symantec

Symantec Corporation (commonly known as Symantec) is an American software company headquartered in Mountain View, California, United States. The company provides cybersecurity software and services. Symantec is a Fortune 500 company and a member of the S&P 500 stock-market index. The company also has development centers in Pune, Chennai and Bengaluru (India). On October 9, 2014, Symantec declared it would split into two independent publicly traded companies by the end of 2015. One company would focus on security, the other on information management. On January 29, 2016, Symantec sold its information-management subsidiary, named Veritas Technologies (which Symantec had acquired in 2004)[4] to The Carlyle Group.[5] The name "Symantec" is a portmanteau of the words "syntax" and "semantics" with "technology".[6] History 1982 to 1989 Founded in 1982 by Gary Hendrix with a National Science Foundation grant, Symantec was originally focused on artificial intelligence-related projects, including a database p ...more...

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Data governance

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Data governance

Data governance is the capability that enables an organization to ensure that high data quality exists throughout the complete lifecycle of the data. The key focus areas of data governance include availability, usability, consistency[1], data integrity and data security and includes establishing processes to ensure effective data management throughout the enterprise such as accountability for the adverse effects of poor data quality and ensuring that the data which an enterprise has can be used by the entire organization. A data steward is a role that ensures that data governance processes are followed, guidelines enforced, and recommends improvements to data governance processes. Overview Data governance encompasses the people, processes, and information technology required to create a consistent and proper handling of an organization's data across the business enterprise. It provides all data management practices with the necessary foundation, strategy, and structure needed to ensure that data is managed ...more...

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Event-driven process chain

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Event-driven process chain

Example of a more complex EPC diagram (in German). An event-driven process chain (EPC) is a type of flowchart used for business process modelling. EPCs can be used for configuring an enterprise resource planning (ERP) implementation,[1] and for business process improvement. Usage for control of work share with instances of autonomous workflows in workflow management is possible, but not yet implemented. The event-driven process chain method was developed within the framework of Architecture of Integrated Information Systems (ARIS) by August-Wilhelm Scheer at the Institut für Wirtschaftsinformatik, Universität des Saarlandes (Institute for Business Information Systems at the University of Saarland) in the early 1990s.[2] Overview Businesses use event-driven process chain diagrams to lay out business process workflows, originally in conjunction with SAP R/3 modeling, but now more widely. It is used by many companies for modeling, analyzing, and redesigning business processes. The event-driven process chain ...more...

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Dublin Core

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Dublin Core

The Dublin Core Schema is a small set of vocabulary terms that can be used to describe digital resources (video, images, web pages, etc.), as well as physical resources such as books or CDs, and objects like artworks.[1] The full set of Dublin Core metadata terms can be found on the Dublin Core Metadata Initiative (DCMI) website.[2] The original set of 15 classic[3] metadata terms, known as the Dublin Core Metadata Element Set (DCMES),[4] is endorsed in the following standards documents: IETF RFC 5013[5] ISO Standard 15836-2009[6] NISO Standard Z39.85[7] Dublin Core metadata may be used for multiple purposes, from simple resource description to combining metadata vocabularies of different metadata standards, to providing interoperability for metadata vocabularies in the linked data cloud and Semantic Web implementations. Background "Dublin" refers to Dublin, Ohio, USA where the schema originated during the 1995 invitational OCLC/NCSA Metadata Workshop,[8] hosted by the OCLC (Online Computer Library ...more...

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Software development

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Software development

Software development is the process of conceiving, specifying, designing, programming, documenting, testing, and bug fixing involved in creating and maintaining applications, frameworks, or other software components. Software development is a process of writing and maintaining the source code, but in a broader sense, it includes all that is involved between the conception of the desired software through to the final manifestation of the software, sometimes in a planned and structured process.[1] Therefore, software development may include research, new development, prototyping, modification, reuse, re-engineering, maintenance, or any other activities that result in software products.[2] Software can be developed for a variety of purposes, the three most common being to meet specific needs of a specific client/business (the case with custom software), to meet a perceived need of some set of potential users (the case with commercial and open source software), or for personal use (e.g. a scientist may write sof ...more...

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Entity–relationship model

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Entity–relationship model

An entity–relationship model (ER model for short) describes interrelated things of interest in a specific domain of knowledge. A basic ER model is composed of entity types (which classify the things of interest) and specifies relationships that can exist between instances of those entity types. An entity–relationship diagram for an MMORPG using Chen's notation. In software engineering, an ER model is commonly formed to represent things that a business needs to remember in order to perform business processes. Consequently, the ER model becomes an abstract data model, that defines a data or information structure which can be implemented in a database, typically a relational database. Entity–relationship modeling was developed for database design by Peter Chen and published in a 1976 paper.[1] However, variants of the idea existed previously.[2] Some ER models show super and subtype entities connected by generalization-specialization relationships,[3] and an ER model can be used also in the specification of ...more...

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Smart products

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Smart products

Recent innovations in mobile and sensor technologies allow for creating a digital representation of almost any physical entity and its parameters over time at any place. RFID technologies, for instance, are used to ground digital representations, which are used to track and geo-reference physical entities. In general, physical worlds and digital representations become tightly interconnected, so that manipulations in either would have effect on the other. Integration of information and communication technologies into products anywhere and anytime enable new forms of mobile marketing in respect to situated marketing communication, dynamic pricing models and dynamic product differentiation models. As Fano and Gershman state: "Technology enables service providers to make the location of their customers the location of their business".[1] Smart products are specializations of hybrid products with physical realizations of product categories and digital product descriptions that provide the following characteristi ...more...

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Metadata registry

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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. 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 to the charter of any metadata management programme is the process of creating trusting relationships with stakeholders and that definitions and structures ...more...

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Apache ServiceMix

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Apache ServiceMix

Apache ServiceMix is an enterprise-class open-source distributed enterprise service bus (ESB) based on the service-oriented architecture (SOA) model. It is a project of the Apache Software Foundation and was built on the semantics and application programming interfaces of the Java Business Integration (JBI) specification JSR 208. The software is distributed under the Apache License. The productized and supported release of ServiceMix 4 is from JBoss and called Fuse ESB. Fabric8 is a free Apache 2.0 Licensed upstream community for the JBoss Fuse product from Red Hat. The current version of ServiceMix fully supports the OSGi framework. ServiceMix is lightweight and easily embeddable, has integrated Spring Framework support and can be run at the edge of the network (inside a client or server), as a standalone ESB provider or as a service within another ESB. ServiceMix is compatible with Java SE or a Java EE application server. ServiceMix uses ActiveMQ to provide remoting, clustering, reliability and distribut ...more...

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Data model

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Data model

A data model (or datamodel[1][2][3][4][5]) is a set of tables, linked by relationships and is an abstract model that organizes elements of data and standardizes how they relate to one another and to properties of the real world entities. For instance, a data model may specify that the data element representing a car be composed of a number of other elements which, in turn, represent the color and size of the car and define its owner. The term data model is used in two distinct but closely related senses. Sometimes it refers to an abstract formalization of the objects and relationships found in a particular application domain, for example the customers, products, and orders found in a manufacturing organization. At other times it refers to a set of concepts used in defining such formalizations: for example concepts such as entities, attributes, relations, or tables. So the "data model" of a banking application may be defined using the entity-relationship "data model". This article uses the term in both senses ...more...

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Resource Description Framework

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Resource Description Framework

The Resource Description Framework (RDF) is a family of World Wide Web Consortium (W3C) specifications[1] originally designed as a metadata data model. It has come to be used as a general method for conceptual description or modeling of information that is implemented in web resources, using a variety of syntax notations and data serialization formats. It is also used in knowledge management applications. RDF was adopted as a W3C recommendation in 1999. The RDF 1.0 specification was published in 2004, the RDF 1.1 specification in 2014. Overview The RDF data model[2] is similar to classical conceptual modeling approaches (such as entity–relationship or class diagrams). It is based on the idea of making statements about resources (in particular web resources) in expressions of the form subject–predicate–object, known as triples. The subject denotes the resource, and the predicate denotes traits or aspects of the resource, and expresses a relationship between the subject and the object. For example, one way ...more...

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WS-Policy

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WS-Policy

WS-Policy is a specification that allows web services to use XML to advertise their policies (on security, quality of service, etc.) and for web service consumers to specify their policy requirements. WS-Policy is a W3C recommendation as of September 2007. WS-Policy represents a set of specifications that describe the capabilities and constraints of the security (and other business) policies on intermediaries and end points (for example, required security tokens, supported encryption algorithms, and privacy rules) and how to associate policies with services and end points. Policy Assertion Assertions can either be requirements put upon a web service or an advertisement of the policies of a web service. Operator tags Two "operators" (XML tags) are used to make statements about policy combinations: wsp:ExactlyOne - asserts that only one child node must be satisfied. wsp:All - asserts that all child nodes must be satisfied. Logically, an empty wsp:All tag makes no assertions. Policy Intersection I ...more...

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Ontology (information science)

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Ontology (information science)

In computer science and information science, an ontology encompasses a representation, formal naming, and definition of the categories, properties, and relations between the concepts, data, and entities that substantiate one, many, or all domains. Every field creates ontologies to limit complexity and organize information into data and knowledge. As new ontologies are made, their use hopefully improves problem solving within that domain. Translating research papers within every field is a problem made easier when experts from different countries maintain a controlled vocabulary of jargon between each of their languages.[1] Since Google started an initiative called Knowledge Graph, a substantial amount of research has gone on using the phrase knowledge graph as a generalized term. Although there is no clear definition for the term knowledge graph, it is often used as synonym for ontology.[2] Etymology The compound word ontology combines onto-, from the Greek ὄν, on (gen. ὄντος, ontos), i.e. "being; that wh ...more...

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IDEF0

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IDEF0

IDEF0 Diagram Example IDEF0, a compound acronym ("Icam DEFinition for Function Modeling", where ICAM is an acronym for "Integrated Computer Aided Manufacturing"), is a function modeling methodology for describing manufacturing functions, which offers a functional modeling language for the analysis, development, reengineering, and integration of information systems; business processes; or software engineering analysis.[1] IDEF0 is part of the IDEF family of modeling languages in the field of software engineering, and is built on the functional modeling language Structured Analysis and Design Technique (SADT). Overview The IDEF0 Functional Modeling method is designed to model the decisions, actions, and activities of an organization or system.[2] It was derived from the established graphic modeling language Structured Analysis and Design Technique (SADT) developed by Douglas T. Ross and SofTech, Inc. In its original form, IDEF0 includes both a definition of a graphical modeling language (syntax and semantic ...more...

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Misuse case

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Misuse case

Example of the Misuse case principle, which could be used in thinking about capturing security requirements. Misuse Case is a business process modeling tool used in the software development industry. The term Misuse Case or mis-use case is derived from and is the inverse of use case.[1] The term was first used in the 1990s by Guttorm Sindre of the Norwegian University of Science and Technology, and Andreas L. Opdahl of the University of Bergen, Norway. It describes the process of executing a malicious act against a system, while use case can be used to describe any action taken by the system .[2] Overview Use cases specify required behaviour of software and other products under development, and are essentially structured stories or scenarios detailing the normal behavior and usage of the software. A Misuse Case on the other hand highlights something that should not happen (i.e. a Negative Scenario) and the threats hence identified, help in defining new requirements, which are expressed as new Use Cases. T ...more...

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Semantic data model

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Semantic data model

Semantic data models.[1] A semantic data model in software engineering has various meanings: It is a conceptual data model in which semantic information is included. This means that the model describes the meaning of its instances. Such a semantic data model is an abstraction that defines how the stored symbols (the instance data) relate to the real world.[1] It is a conceptual data model that includes the capability to express information that enables parties to the information exchange to interpret meaning (semantics) from the instances, without the need to know the meta-model. Such semantic models are fact-oriented (as opposed to object-oriented). Facts are typically expressed by binary relations between data elements, whereas higher order relations are expressed as collections of binary relations. Typically binary relations have the form of triples: Object-RelationType-Object. For example: the Eiffel Tower Paris. Typically the instance data of semantic data models explicitly include the kinds of ...more...

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Formal methods

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Formal methods

In computer science, specifically software engineering and hardware engineering, formal methods are a particular kind of mathematically based techniques for the specification, development and verification of software and hardware systems.[1] The use of formal methods for software and hardware design is motivated by the expectation that, as in other engineering disciplines, performing appropriate mathematical analysis can contribute to the reliability and robustness of a design.[2] Formal methods are best described as the application of a fairly broad variety of theoretical computer science fundamentals, in particular logic calculi, formal languages, automata theory, discrete event dynamic system and program semantics, but also type systems and algebraic data types to problems in software and hardware specification and verification.[3] Taxonomy Formal methods can be used at a number of levels: Level 0: Formal specification may be undertaken and then a program developed from this informally. This has been d ...more...

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HL7 Services Aware Interoperability Framework

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HL7 Services Aware Interoperability Framework

This article documents the effort of the Health Level Seven(HL7)[1] community and specifically the HL7 Architecture Board [2] (ArB) to develop an interoperability framework that would support services, messages, and Clinical Document Architecture(CDA) ISO 10871. HL7 provides a framework and standards for the exchange, integration, sharing, and retrieval of electronic health information. SAIF Overview The HL7 Services-Aware Interoperability Framework Canonical Definition (SAIF-CD) [3] provides consistency between all artifacts, and enables a standardized approach to enterprise architecture (EA) development and implementation, and a way to measure the consistency. SAIF is a way of thinking about producing specifications that explicitly describe the governance, conformance, compliance, and behavioral semantics that are needed to achieve computable semantic working interoperability. The intended information transmission technology might use a messaging, document exchange, or services approach. SAIF is the fr ...more...

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Database

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Database

An example of output from an SQL database query. A database is an organized collection of data, stored and accessed electronically. Database designers typically organize the data to model aspects of reality in a way that supports processes requiring information, such as (for example) modelling the availability of rooms in hotels in a way that supports finding a hotel with vacancies. A database-management system (DBMS) is a computer-software application that interacts with end-users, other applications, and the database itself to capture and analyze data. (Sometimes a DBMS is loosely referred to as a "database".) A general-purpose DBMS allows the definition, creation, querying, update, and administration of databases. A database is generally stored in a DBMS-specific format which is not portable, but different DBMSs can share data by using standards such as SQL and ODBC or JDBC. Computer scientists may classify database-management systems according to the database models that they support. Relational databa ...more...

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Semantic spectrum

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Semantic spectrum

The semantic spectrum (sometimes referred to as the ontology spectrum or the smart data continuum or semantic precision) is a series of increasingly precise or rather semantically expressive definitions for data elements in knowledge representations, especially for machine use. At the low end of the spectrum is a simple binding of a single word or phrase and its definition. At the high end is a full ontology that specifies relationships between data elements using precise URIs for relationships and properties. With increased specificity comes increased precision and the ability to use tools to automatically integrate systems but also increased cost to build and maintain a metadata registry. Some steps in the semantic spectrum include the following: glossary: A simple list of terms and their definitions. A glossary focuses on creating a complete list of the terminology of domain-specific terms and acronyms. It is useful for creating clear and unambiguous definitions for terms and because it can be create ...more...

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Enterprise service bus

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Enterprise service bus

All customer services communicate in the same way with the ESB: the ESB translates a message to the correct message type and sends the message to the correct consumer service. An enterprise service bus (ESB) implements a communication system between mutually interacting software applications in a service-oriented architecture (SOA). It implements a software architecture as depicted in the picture. As it implements a distributed computing architecture, it implements a special variant of the more general client-server model, wherein, in general, any application using ESB can behave as server or client in turns. ESB promotes agility and flexibility with regard to high-level protocol communication between applications. The primary goal of the high-level protocol communication is enterprise application integration (EAI) of heterogeneous and complex service or application landscapes (a view from the network level). Overview The concept is analogous to the bus concept found in computer hardware architecture combi ...more...

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Value object

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Value object

In computer science, a value object is a small object that represents a simple entity whose equality is not based on identity: i.e. two value objects are equal when they have the same value, not necessarily being the same object.[1][2] Examples of value objects are objects representing an amount of money or a date range. Being small, one can have multiple copies of the same value object that represent the same entity: it is often simpler to create a new object rather than rely on a single instance and use references to it.[2] Value objects should be immutable:[3] this is required for the implicit contract that two value objects created equal, should remain equal. It is also useful for value objects to be immutable, as client code cannot put the value object in an invalid state or introduce buggy behaviour after instantiation.[4] Value objects are among the building blocks of DDD. Value objects in C# In C# a class is a reference type while a struct (concept derived from the struct in C language) is a val ...more...

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IDEF1X

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IDEF1X

Example of an IDEF1X diagram. Integration DEFinition for information modeling (IDEF1X) is a data modeling language for the development of semantic data models. IDEF1X is used to produce a graphical information model which represents the structure and semantics of information within an environment or system.[1] IDEF1X permits the construction of semantic data models which may serve to support the management of data as a resource, the integration of information systems, and the building of computer databases. This standard is part of the IDEF family of modeling languages in the field of software engineering. Overview A data modeling technique is used to model data in a standard, consistent and predictable manner in order to manage it as a resource. It can be used in projects requiring a standard means of defining and analyzing the data resources within an organization. Such projects include the incorporation of a data modeling technique into a methodology, managing data as a resource, integrating informatio ...more...

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OpenL Tablets

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OpenL Tablets

OpenL Tablets is a business rule management system (BRMS) and a business rules engine (BRE) based on table representation of rules. Engine implements optimized sequential algorithm. OpenL includes such table types as decision table, decision tree, spreadsheet-like calculator. History The OpenL Tablets project was started as an in-house development project in 2003 and later in 2006 was uploaded to SourceForge.[1] Initially it was a Open Source business rule engine for Java. Starting from version 5 it became a BRMS. Technology OpenL Tablets engine is specially designed for business rules and uses table rules presentation. Table format enforces rules to be structured and format itself is close to tables found in various business documents. OpenL Tablets is based on OpenL framework for creating custom languages running on Java VM. The engine is designed to allow pluggable language implementations. Currently, it uses 2 languages: table structure for rules format and java-like for code snippets in rules. Java- ...more...

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List of web service specifications

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List of web service specifications

There are a variety of specifications associated with web services. These specifications are in varying degrees of maturity and are maintained or supported by various standards bodies and entities. These specifications are the basic web services framework established by first-generation standards represented by WSDL, SOAP, and UDDI.[1] Specifications may complement, overlap, and compete with each other. Web service specifications are occasionally referred to collectively as "WS-*", though there is not a single managed set of specifications that this consistently refers to, nor a recognized owning body across them all. “WS-“is a prefix used to indicate specifications associated with web services and there exist many WS* standards including WS-Addressing, WS-Discovery, WS-Federation, WS-Policy, WS-Security, and WS-Trust.[2] This page includes many of the specifications that might be considered a part of "WS-*". Web service standards listings These sites contain documents and links about the different Web Ser ...more...

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Data flow diagram

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Data flow diagram

Data flow diagram example.[1] A data flow diagram (DFD) is a graphical representation of the "flow" of data through an information system, modelling its process aspects. A DFD is often used as a preliminary step to create an overview of the system without going into great detail, which can later be elaborated.[2] DFDs can also be used for the visualization of data processing (structured design). A DFD shows what kind of information will be input to and output from the system, how the data will advance through the system, and where the data will be stored. It does not show information about process timing or whether processes will operate in sequence or in parallel, unlike a traditional structured flowchart which focuses on control flow, or a UML activity workflow diagram, which presents both control and data flows as a unified model. History In the 1970s, Larry Constantine, the original developer of structured design, proposed data flow diagrams as a practical technique based on Martin and Estrin's "Dat ...more...

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Process modeling

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Process modeling

The term process model is used in various contexts. For example, in business process modeling the enterprise process model is often referred to as the business process model. Abstraction level for processes[1] Overview Process models are processes of the same nature that are classified together into a model. Thus, a process model is a description of a process at the type level. Since the process model is at the type level, a process is an instantiation of it. The same process model is used repeatedly for the development of many applications and thus, has many instantiations. One possible use of a process model is to prescribe how things must/should/could be done in contrast to the process itself which is really what happens. A process model is roughly an anticipation of what the process will look like. What the process shall be will be determined during actual system development.[2] The goals of a process model are to be: Descriptive Track what actually happens during a process Take the point of ...more...

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RSI

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RSI

RSI may refer to: Business RADARSAT International, a provider of data and information derived from a Canadian remote-sensing Earth observation satellite program overseen by the Canadian Space Agency Relative strength index, a technical indicator used in the analysis of financial markets RSI Corporation, RadioFrequency Safety International, a safety firm specializing in OSHA/FCC radio frequency (RF) compliance Relational Semantics, Inc, a U.S. software company specializing in case management systems for state judiciaries Science and technology RSI register, a 64-bit processor register of x86 CPUs Records Series Identifiers, a method used in records management for applying retention and follow-up information for electronic documents Review of Scientific Instruments, a scientific journal Repetitive strain injury, a disorder affecting muscles, tendons and nerves from repetitive movements, forceful exertions, vibrations, mechanical compression, or sustained/awkward positions. Relative strengt ...more...



Dawn Raid Entertainment

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Dawn Raid Entertainment

Dawn Raid Entertainment is a record label based in Papatoetoe, South Auckland, in New Zealand. It has signed many New Zealand Hip-hop and R&B artists such as Savage, Adeaze, Aaradhna, The Deceptikonz, Devolo and Ill Semantics. The founders of Dawn Raid Entertainment announced the closure of the recording label on 19 April 2007 due to liquidation.[1] The label is back in business as of June 2007, due to new owners.[2][3] Savage, Mareko, The Deceptikonz, Horsemen Family, Sweet & Irie and more new artists are to be announced. In 2008 the police seized all assets of their competitor, Killer Beez-control Colourway Records. In its peak it was home to many gold and platinum-selling New Zealand hip hop and R&B artists. History School friends Danny "Brotha D" Leaosavai'i and Andy Murnane founded Dawn Raid Entertainment in 1999. They started selling T-shirts at a market in Ōtara to raise capital. In 2007, the label went into liquidation for a few months.[4] Sponsorship In May 2004, Dawn Raid became ...more...

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DbMotion

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DbMotion

dbMotion is a vendor of health Interoperability solutions for connected healthcare that enable healthcare organizations to meaningfully integrate and leverage their information assets. Overview dbMotion facilitates interoperability and health information exchange (HIE) for health information networks and integrated healthcare delivery systems. The service-oriented architecture (SOA) based dbMotionTM Solution gives caregivers and information systems secure access to an integrated patient record composed from a patient's medical data maintained at facilities that are otherwise unconnected or have no common technology through which to share data, without requiring the replacement of existing information systems. dbMotion can interoperate with multiple different vendor products[1] and the architecture’s modularity allows for multiple approaches to sharing medical information e.g. centralized, distributed/federated or any hybrid format. dbMotion can dovetail the clinical vocabulary, or semantics, from disparate ...more...

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Metadata

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Metadata

In the 2010s, metadata typically refers to digital forms, but traditional card catalogues contain metadata, with cards holding information about books in a library (author, title, subject, etc.). Metadata is "data [information] that provides information about other data".[1] Many distinct types of metadata exist, among these descriptive metadata, structural metadata, administrative metadata[2], reference metadata and statistical metadata[3] 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. [4] Administrative metadata provides information to help manage a resource, such as when and how it was created, file type and other technical informa ...more...

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Extended Semantic Web Conference

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Extended Semantic Web Conference

The Extended Semantic Web Conference (abbreviated as ESWC), formerly known as the European Semantic Web Conference, is a yearly international academic conference on the topic of the Semantic Web. The event began in 2004 as the European Semantic Web Symposium. The goal of the event is "to bring together researchers and practitioners dealing with different aspects of semantics on the Web".[1] Topics covered at the conference include linked data, machine learning, natural language processing and information retrieval, ontologies, reasoning, semantic data management, services, processes, and cloud computing, social Web and Web science, in-use and industrial, digital libraries and cultural heritage, and e-government.[2] List of conferences Past and future ESWC conferences include:[3] Year Conference City Country 2016 ESWC2016 Anissaras, Crete Greece 2013 ESWC2013 Montpellier France 2012 ESWC2012 Heraklion Greece 2011 ESWC2011 Heraklion Greece 2010 ESWC2010 Heraklion ...more...

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Open Cloud Computing Interface

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Open Cloud Computing Interface

The Open Cloud Computing Interface (OCCI) is a set of specifications delivered through the Open Grid Forum,[1][2] for cloud computing service providers. OCCI has a set of implementations that act as proofs of concept. It builds upon World Wide Web fundamentals by using the Representational State Transfer (REST) approach for interacting with services. Scope The aim of the Open Cloud Computing Interface is the development of an open specification and API for cloud offerings. The focus was on Infrastructure-as-a-Service (IaaS) based offerings but the interface can be extended to support Platform and Software as a Service offerings[3] as well. IaaS is one of three primary segments of the cloud computing industry in which compute, storage and network resources are provided as services. The API is based on a review of existing service-provider functionality and a set of use cases contributed by the working group.[4] OCCI is a boundary API that acts as a service front-end to an IaaS provider’s internal infrastruc ...more...

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Ronald Stamper

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Ronald Stamper

Ronald K. (Ron) Stamper (born 1934) is a British computer scientist, formerly a researcher in the LSE and Emeritus Professor at the University of Twente, known for his pioneering work in Organisational semiotics, and the creation of the MEASUR methodology and the SEDITA framework. Biography Born in West Bridgford, United Kingdom, Stamper obtained his MA in Mathematics and Statistics at Oxford University in 1959.[1] Stamper started his career in industry, first in hospital administration and later in the steel industry. He starting applying operational research methods with the use of computers, and evolved into the management of information systems development. In need of more experts, he developed one of the first courses in systems analysis in the UK. In 1969 he moved into the academic world, starting at the London School of Economics as Senior Lecturer and Principal Investigator. From 1988 to 1999 he was Professor of Information Management at the University of Twente at its Faculty of Technology and Man ...more...

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Artifact-centric business process model

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Artifact-centric business process model

Artifact-centric business process model represents an operational model of business processes in which the changes and evolution of business data, or business entities, are considered as the main driver of the processes. The artifact-centric approach, also called activity-centric or process-centric business process modeling, focuses on describing how business data is change/updated, by a particular action or task, throughout the process. Overview In general, a process model describes activities conducted in order to achieve business goals, informational structures, and organizational resources. Workflows, as a typical process modeling approach, often emphasize the sequencing of activities (i.e., control flows), but ignore the informational perspective or treat it only within the context of single activities. Without a complete view of the informational context, business actors often focus on what should be done instead of what can be done, hindering operational innovations. Business process modeling is a f ...more...

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Production system (computer science)

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Production system (computer science)

A production system (or production rule system) is a computer program typically used to provide some form of artificial intelligence, which consists primarily of a set of rules about behavior. These rules, termed productions, are a basic representation found useful in automated planning, expert systems and action selection. A production system provides the mechanism necessary to execute productions in order to achieve some goal for the system. Productions consist of two parts: a sensory precondition (or "IF" statement) and an action (or "THEN"). If a production's precondition matches the current state of the world, then the production is said to be triggered. If a production's action is executed, it is said to have fired. A production system also contains a database, sometimes called working memory, which maintains data about current state or knowledge, and a rule interpreter. The rule interpreter must provide a mechanism for prioritizing productions when more than one is triggered. Basic operation Rule i ...more...

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Cowboy coding

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Cowboy coding

Cowboy coding is software development where programmers have autonomy over the development process. This includes control of the project's schedule, languages, algorithms, tools, frameworks and coding style. A cowboy coder can be a lone developer or part of a group of developers working with minimal process or discipline. Usually it occurs when there is little participation by business users, or fanned by management that controls only non-development aspects of the project, such as the broad targets, timelines, scope, and visuals (the "what", but not the "how"). "Cowboy coding" commonly sees usage as a derogatory term when contrasted with more structured software development methodologies. Disadvantages In cowboy coding, the lack of formal software project management methodologies may be indicative (though not necessarily) of a project's small size or experimental nature.[1] Software projects with these attributes may exhibit: Lack of release structure Lack of estimation or implementation planning might ...more...

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Outline of databases

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Outline of databases

The following outline is provided as an overview of and topical guide to databases: Database – organized collection of data, today typically in digital form. The data are typically organized to model relevant aspects of reality (for example, the availability of rooms in hotels), in a way that supports processes requiring this information (for example, finding a hotel with vacancies). What type of things are databases? Databases can be described as all of the following: Information – sequence of symbols that can be interpreted as a message. Information can be recorded as signs, or transmitted as signals. Data – values of qualitative or quantitative variables, belonging to a set of items. Data in computing (or data processing) are often represented by a combination of items organized in rows and multiple variables organized in columns. Data are typically the results of measurements and can be visualised using graphs or images. Computer data – information in a form suitable for use with a computer. Dat ...more...

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List of academic fields

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List of academic fields

Mind map of top level disciplines and professions The following outline is provided as an overview of an topical guide to academic disciplines: An academic discipline or field of study is known as a branch of knowledge. It is taught as an accredited part of higher education. A scholar's discipline is commonly defined and recognized by a university faculties. That person will be accredited by learned societies to which he or she belongs along with the academic journals in which he or she publishes. However, no formal criteria exist for defining an academic discipline. Disciplines varies between universities and programs. These discipline will have well-defined rosters of journals and conferences supported by a few universities and publications. A discipline may have branches, that are called sub-disciplines. There is no consensus on how some academic disciplines should be classified (e.g., whether anthropology and linguistics are disciplines of social sciences or fields within the humanities). More general ...more...

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Peyman Faratin

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Peyman Faratin

Peyman Faratin (born September 16, 1965) is an Iranian/American computer scientist, and the founder of Robust Links, an Internet company building algorithms for creating and processing a knowledge graph. Background Peyman completed his PhD in computer science under the supervision of Prof. Nicholas R. Jennings and Prof. Carles Sierra. He made significant contributions in the area of artificial intelligence, particularly to automated negotiation in multi-agent systems. He was then a research scientist at MIT's Computer Science and Artificial Intelligence (CSAIL) laboratory, working with David D. Clark in the Advanced Network Architecture group. Peyman has over eighteen years of experience in design and implementation of online marketplaces. He graduated from University of London (EECS department) in 2000 completing his doctoral thesis on algorithms for online bargaining and auction mechanisms, with application to business process management and supply chain management in telecommunication domains. Between 2 ...more...

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Cloud Infrastructure Management Interface

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Cloud Infrastructure Management Interface

Cloud Infrastructure Management Interface (CIMI) is an open standard API specification for managing cloud infrastructure. CIMI's goal is to enable users to manage cloud infrastructure in a simple way by standardizing interactions between cloud environments to achieve interoperable cloud infrastructure management between service providers and their consumers and developers. CIMI 1.1 was registered as an International Standard in August 2014 by the Joint Technical Committee 1 (JTC 1) of the International Organization for Standardization (ISO) and the International Electrotechnical Commission (IEC). [1] Overview The CIMI standard is defined and published by the Distributed Management Task Force (DMTF). It includes the Cloud Infrastructure Management Interface (CIMI) Model and RESTful HTTP-based Protocol specification,[2] the CIMI XML Schema, the CIMI Primer and the CIMI Uses Cases whitepaper:[3] Cloud Infrastructure Management Interface (CIMI) Model and RESTful HTTP-based Protocol The Cloud Infrastructure ...more...

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Amit Sheth

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Amit Sheth

Dr. Amit Sheth is a computer scientist at Wright State University in Dayton, Ohio. He is the Lexis Nexis Ohio Eminent Scholar for Advanced Data Management and Analysis. [1] Up to June 2017, Sheth's work has been cited by 37,304 publications.[2] He has an h-index of 95,[2] which puts him among the top 100 computer scientists with the highest h-index.[3] Prior to founding the Kno.e.sis Center, he served as the director of the Large Scale Distributed Information Systems Lab at the University of Georgia in Athens, Georgia. Education Sheth received his bachelor's in engineering from the Birla Institute of Technology and Science in computer science in 1981. He received his M.S. and Ph.D. in computer science from the Ohio State University in 1983 and 1985, respectively. Research Semantic interoperability/integration and semantic web Sheth has investigated, demonstrated, and advocated for the comprehensive use of metadata. He explored syntactical, structural, and semantic metadata; recently, he has pioneered onto ...more...

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Greenplum

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Greenplum

Greenplum was a big data analytics company headquartered in San Mateo, California. Greenplum was acquired by EMC Corporation in July 2010.[1] Starting in 2012 its database management system software became known as the Pivotal Greenplum Database sold through Pivotal Software and is currently actively developed by the Greenplum Database open source community and Pivotal. Company Greenplum, the company, was founded in September 2003 by Scott Yara and Luke Lonergan. It was a merger of two smaller companies: Metapa (founded in August 2000 near Los Angeles)[2] and Didera in Fairfax, Virginia.[3] Investors included SoundView Ventures, Hudson Ventures and Royal Wulff Ventures. A total of US$20 million in funding was announced at the merger.[4] Greenplum, based in San Mateo, California, released its database management system software based on PostgreSQL in April 2005 calling it Bizgres.[5] Rounds of venture capital of about US$15 million each were invested in March 2006 and February 2007.[6] In July 2006 a partne ...more...

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List of computing and IT abbreviations

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List of computing and IT abbreviations

This is a list of computing and IT acronyms and abbreviations. 0–9 #!—Shebang /.—Slashdot 1GL—First-Generation Programming Language 1NF—First Normal Form 10B2—10BASE-2 10B5—10BASE-5 10B-F—10BASE-F 10B-FB—10BASE-FB 10B-FL—10BASE-FL 10B-FP—10BASE-FP 10B-T—10BASE-T 100B-FX—100BASE-FX 100B-T—100BASE-T 100B-TX—100BASE-TX 100BVG—100BASE-VG 286—Intel 80286 processor 2B1Q—2 Binary 1 Quaternary 2FA—Two-factor authentication 2GL—Second-Generation Programming Language 2NF—Second Normal Form 3GL—Third-Generation Programming Language 3GPP—3rd Generation Partnership Project—'3G comms 3GPP2—3rd Generation Partnership Project 2 3NF—Third Normal Form 386—Intel 80386 processor 486—Intel 80486 processor 4B5BLF—4 Byte 5 Byte Local Fiber 4GL—Fourth-Generation Programming Language 4NF—Fourth Normal Form 5GL—Fifth-Generation Programming Language 5NF—Fifth Normal Form 6NF—Sixth Normal Form 8B10BLF—8 Byte 10 Byte Local Fiber 802.11—Wireless LAN A AAA—Authe ...more...

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Model-driven engineering

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Model-driven engineering

Model-driven engineering (MDE) is a software development methodology that focuses on creating and exploiting domain models, which are conceptual models of all the topics related to a specific problem. Hence, it highlights and aims at abstract representations of the knowledge and activities that govern a particular application domain, rather than the computing (i.e. algorithmic) concepts. Overview The MDE approach is meant to increase productivity by maximizing compatibility between systems (via reuse of standardized models), simplifying the process of design (via models of recurring design patterns in the application domain), and promoting communication between individuals and teams working on the system (via a standardization of the terminology and the best practices used in the application domain). A modeling paradigm for MDE is considered effective if its models make sense from the point of view of a user that is familiar with the domain, and if they can serve as a basis for implementing systems. The mo ...more...

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Designation of workers by collar color

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Designation of workers by collar color

Groups of working individuals are typically classified based on the colors of their collars worn at work; these can commonly reflect one's occupation or sometimes gender.[1] White-collar workers are named for the white-collared shirts that were fashionable among office workers in the early and mid-20th century. Blue-collar workers are referred to as such because in the early 20th century, they usually wore sturdy, inexpensive clothing that didn't show dirt easily, such as blue denim or cambric shirts. Various other "collar" descriptions exist as well. White collar The term "white-collar worker" was coined in the 1930s by Upton Sinclair, an American writer who referenced the word in connection to clerical, administrative and managerial functions during the 1930s.[2] A white-collar worker is a salaried professional, typically referring to general office workers and management. However, in certain developed countries like the United States, the United Kingdom, and Canada, a person is assumed to be a white-coll ...more...

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Data stream management system

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Data stream management system

A data stream management system (DSMS) is a computer software system to manage continuous data streams. It is similar to a database management system (DBMS), which is, however, designed for static data in conventional databases. A DSMS also offers a flexible query processing so that the information need can be expressed using queries. However, in contrast to a DBMS, a DSMS executes a continuous query that is not only performed once, but is permanently installed. Therefore, the query is continuously executed until it is explicitly uninstalled. Since most DSMS are data-driven, a continuous query produces new results as long as new data arrive at the system. This basic concept is similar to Complex event processing so that both technologies are partially coalescing. Functional principle One important feature of a DSMS is the possibility to handle potentially infinite and rapidly changing data streams by offering flexible processing at the same time, although there are only limited resources such as main memory ...more...

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MarkLogic

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MarkLogic

MarkLogic Corporation is an American software business that develops and provides an enterprise NoSQL database, also named MarkLogic. The company was founded in 2001 and is based in San Carlos, California. MarkLogic is a privately held company with over 500 employees and has offices throughout the United States, Europe, Asia, and Australia. MarkLogic has over 1,000 customers, including Chevron, JPMorgan Chase, Erie Insurance Group, Johnson & Johnson, and the US Army.[1] Also, six of the top ten global banks are MarkLogic customers. According to Forrester Research, MarkLogic is one of the nine leading NoSQL databases vendors in the market[2] and appears in several Gartner Magic Quadrant reports for Operational Database Management Systems.[3] In 2017, Gartner ranked MarkLogic as a 'Visionary' in the Data Warehouse market.[4] History MarkLogic was first named Cerisent and was founded in 2001[5] by Christopher Lindblad,[6] who was the Chief Architect of the Ultraseek search engine at Infoseek, and Paul P ...more...

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SMW

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SMW

SMW is an abbreviation that may stand for "Smoky Mountain Wrestling", a professional wrestling promotion based in Knoxville, Tennessee "Springfield's Most Wanted", a television special related to The Simpsons Strategic Missile Wing, US Air Force designation, e.g. 705th Strategic Missile Wing or 705th SMW Semantic MediaWiki, a software extension to MediaWiki Super Mario World, a video game for the Super Nintendo Entertainment System ...more...



Microservices

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Microservices

A Microservice is a software development technique—a variant of the service-oriented architecture (SOA) architectural style that structures an application as a collection of loosely coupled services. In a microservices architecture, services are fine-grained and the protocols are lightweight. The benefit of decomposing an application into different smaller services is that it improves modularity and makes the application easier to understand, develop, test, and more resilient to architecture erosion.[1] It also parallelizes development by enabling small autonomous teams to develop, deploy and scale their respective services independently.[2] It also allows the architecture of an individual service to emerge through continuous refactoring.[3] Microservices-based architectures enable continuous delivery and deployment.[1][4] Details There is no industry consensus yet regarding the properties of microservices, and an official definition is missing as well. Some of the defining characteristics that are frequent ...more...

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