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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.


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.


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
  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".
  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. "Why is Business Semantics the New Hot Topic?". Retrieved 23 November 2008.
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Resource Description Framework


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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 (f.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 m ...more...

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. 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 Mana ...more...

List of academic fields


Mind map of top level disciplines and professions The following outline is provided as an overview of and topical guide to academic disciplines: An academic discipline or field of study is a branch of knowledge that is taught and researched as part of higher education . A scholar's discipline is commonly defined and recognized by the university faculties and learned societies to which he or she belongs and the academic journals in which he or she publishes research . However, no formal criteria exist for defining an academic discipline. Disciplines vary between well-established ones that exist in almost all universities and have well-defined rosters of journals and conferences and nascent ones supported by only a few universities and publications. A discipline may have branches, and these are often 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...

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. Data is oft ...more...



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 550 customers, including Comcast , Deutsche Bank , Erie Insurance Group , Johnson & Johnson , and the US Army . Also, six of the top ten global banks are MarkLogic customers. According to Forrester Research , MarkLogic is among the NoSQL databases vendors with the strongest offerings in the market and regularly appears in Gartner Leaders Quadrant in the Magic Quadrant for Operational Database Management Systems. History MarkLogic was first named Cerisent and was founded in 2001 by Christopher Lindblad, who was the Chief Architect of the Ultraseek search engine at Infoseek , and Paul Pedersen, a professor of computer science at Cornell Univ ...more...



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 strength index Researc ...more...



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 If both provid ...more...

Oracle Spatial and Graph


Oracle Spatial and Graph , formerly Oracle Spatial, forms a separately-licensed option component of the Oracle Database . The spatial features in Oracle Spatial and Graph aid users in managing geographic and location-data in a native type within an Oracle database, potentially supporting a wide range of applications — from automated mapping , facilities management , and geographic information systems ( AM/FM/GIS ), to wireless location services and location-enabled e-business . The graph features in Oracle Spatial and Graph include Oracle Network Data Model (NDM) graphs used in traditional network applications in major transportation , telcos, utilities and energy organizations and RDF semantic graphs used in social networks and social interactions and in linking disparate data sets to address requirements from the research, health sciences, finance, media and intelligence communities. Components The geospatial feature of Oracle Spatial and Graph provides a SQL schema and functions that facilitate the storage ...more...

Software development


Software development is the process of computer programming , documenting , testing , and bug fixing involved in creating and maintaining applications and frameworks resulting in a software product . 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. Therefore, software development may include research, new development, prototyping, modification, reuse, re-engineering, maintenance, or any other activities that result in software products. 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 software to automate a ...more...

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 20 ...more...

Ontology engineering


Ontology engineering in computer science and information science is a field which studies the methods and methodologies for building ontologies : formal representations of a set of concepts within a domain and the relationships between those concepts. A large-scale representation of abstract concepts such as actions, time, physical objects and beliefs would be an example of ontological engineering. Ontology engineering is one of the areas of applied ontology , and can be seen as an application of philosophical ontology . Core ideas and objectives of ontology engineering are also central in conceptual modeling . Overview “ Ontology engineering aims at making explicit the knowledge contained within software applications, and within enterprises and business procedures for a particular domain. Ontology engineering offers a direction towards solving the inter-operability problems brought about by semantic obstacles, i.e. the obstacles related to the definitions of business terms and software classes. Ontology eng ...more...

Machine-Readable Documents


Machine-readable documents are documents whose content can be readily processed by computers . Such documents are distinguished from machine-readable data by virtue of having sufficient structure to provide the necessary context to support the business processes for which they are created. Definition Data without context (language use) is meaningless and lacks the four essential characteristics of trustworthy business records specified in ISO 15489 Information and documentation -- Records management : Reliability Authenticity Integrity Usability The vast bulk of information is unstructured data and, from a business perspective, that means it is "immature", i.e., Level 1 (chaotic) of the Capability Maturity Model . Such immaturity fosters inefficiency, diminishes quality, and limits effectiveness. Unstructured information is also ill-suited for records management functions, provides inadequate evidence for legal purposes, drives up the cost of discovery in litigation , and makes access and usage needlessly cum ...more...

Middleware (distributed applications)


Middleware in the context of distributed applications is software that provides services beyond those provided by the operating system to enable the various components of a distributed system to communicate and manage data. Middleware supports and simplifies complex distributed applications . It includes web servers , application servers , messaging and similar tools that support application development and delivery. Middleware is especially integral to modern information technology based on XML , SOAP , Web services , and service-oriented architecture . Middleware often enables interoperability between applications that run on different operating systems, by supplying services so the application can exchange data in a standards-based way. Middleware sits "in the middle" between application software that may be working on different operating systems . It is similar to the middle layer of a three-tier single system architecture, except that it is stretched across multiple systems or applications. Examples incl ...more...

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). 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, the CIMI XML Schema , the CIMI Primer and the CIMI Uses Cases whitepaper: Cloud Infrastructure Management Interface (CIMI) Model and RESTful HTTP-based Protocol CIMI XML Schema CIMI Primer CIMI Use ...more...

Business Process Execution Language


The Web Services Business Process Execution Language ( WS-BPEL ), commonly known as BPEL ( Business Process Execution Language ), is an OASIS standard executable language for specifying actions within business processes with web services . Processes in BPEL export and import information by using web service interfaces exclusively. Overview One can describe Web-service interactions in two ways: as executable business processes and as abstract business processes. An executable business process: models an actual behavior of a participant in a business interaction. An abstract business process: is a partially specified process that is not intended to be executed. Contrary to Executable Processes, an Abstract Process may hide some of the required concrete operational details. Abstract Processes serve a descriptive role, with more than one possible use case , including observable behavior and/or process template . WS-BPEL aims to model the behavior of processes, via a language for the specification of both Executa ...more...



SQL (  (   listen ) S-Q-L, "sequel"; Structured Query Language ) is a domain-specific language used in programming and designed for managing data held in a relational database management system (RDBMS), or for stream processing in a relational data stream management system (RDSMS). In comparison to older read/write APIs like ISAM or VSAM , SQL offers two main advantages: first, it introduced the concept of accessing many records with one single command; and second, it eliminates the need to specify how to reach a record, e.g. with or without an index. Originally based upon relational algebra and tuple relational calculus , SQL consists of many types of statements, which may be informally classed as sublanguages , commonly: a data query language (DQL), a data definition language (DDL), a data control language (DCL), and a data manipulation language (DML) . The scope of SQL includes data query, data manipulation (insert, update and delete), data definition ( schema creation and modification), and data a ...more...

Data lake


A data lake is a method of storing data within a system or repository, in its natural format, that facilitates the collocation of data in various schemata and structural forms, usually object blobs or files. The idea of data lake is to have a single store of all data in the enterprise ranging from raw data (which implies exact copy of source system data) to transformed data which is used for various tasks including reporting , visualization , analytics and machine learning . The data lake includes structured data from relational databases (rows and columns), semi-structured data (CSV, logs, XML, JSON), unstructured data (emails, documents, PDFs) and even binary data (images, audio, video) thus creating a centralized data store accommodating all forms of data. A data swamp is a deteriorated data lake, that is inaccessible to its intended users and provides little value. Background James Dixon, then chief technology officer at Pentaho allegedly coined the term to contrast it with data mart , which is a smalle ...more...

Bernhard Thalheim


Bernhard Karl Thalheim (born 1952) is a German computer scientist and Professor of Information Systems Engineering at the University of Kiel who is known for conceptual modeling and its theoretical foundational contributions. Biography Born in Radebeul near Dresden , Germany, Thalheim received his M.Sc. in Mathematics and Computer science in 1975 at the Dresden University of Technology , his PhD in Discrete mathematics in 1979 at the Lomonosov Moscow State University , and his Habilitation in Theoretical computer science in 1985 at the Dresden University of Technology . From 1986 to 1989 Thalheim was an Associate Professor at the Dresden University of Technology. In 1989 he moved to the University of Rostock , where he was Professor until 1993. From 1993 to 2003 he was Dean and Full Professor at the Brandenburg Technical University , and since 2003 he is Professor at the Christian-Albrechts-Universität of Kiel. Thalheim has been Visiting Professor at the Kuwait University ; at the University of Klagenfurt , A ...more...

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