A	Active Control System (ACS) A Global Positioning System infrastructure development program for relative GPS applications in the Province. With the location of several permanent GPS base stations dispersed throughout the province, and a central Provincial Master Active Control Station, relative GPS users may perform data capture to within 1 centimetre to 5 metres with respect to NAD83 and CVD28 anywhere in the province. The Active Control System sets an open-architecture standard for data capture, requiring users to conform to non-proprietary non-GPS vendor restricted data formats. The ACS is designed to reduce users' georeferencing costs as well as to permit data sharing and multiple use of captured data. Activity An individual action (unit of work) performed in the Enterprise. An activity is either continuous in nature (a function) or discontinuous (a process). Activity model A structured, graphical representation of the activities performed in a business area, and the interrelationships between them. Application A collection of computer hardware, computer programs, databases, procedures and knowledge workers that work together to perform a related group of services or business processes. Application architecture A graphical representation of a system showing the process, data, hardware, software, and communications components of the system across a business value chain. Application custodian A Senior Manager for a business area responsible for application requirements, design, implementation, and training. Builds automated applications to enable information entry, retrieval, and updating by staff. Application driven See Process Driven. Application system See Application. Associative entity type An entity type that describes the relationship or a pair of entity types that have a many-to-many relationship or cardinality. See also Relationship. Attribute An inherent property, characteristic, or fact that describes an entity or object. A fact that has the same format, interpretation, and domain for all occurrences of an entity type. An attribute is a conceptual representation of a type of fact that is implemented as a field in a record or data element in a database file. Attribute definition A meaningful, concise definition of the attribute (type) that answers the question "What does it mean to assign a value to this attribute?" Attribute name The descriptive name given to an attribute type. Attribute type A named collection of observable, recordable facts of the same kind. An attribute may consist of two types; key and non-key. The key consists of one or more attributes that uniquely identify an instance of an entity type.
B	Best practice The documented strategies and tactics employed by organizations to define the most efficient, effective methods to evolve and utilize their revenue and business opportunities in the delivery of their services. Business activity An individual activity or unit of work performed in the business. An activity can be either continuous in nature (function) or discontinuous (process). Business application model A graphical illustration of the conceptual application systems, both manual and automated, including their dependencies, required to perform the processes of an organization. Business area A subset of the Enterprise bounded by the selected types of activities. Business data A subset of the Enterprise data bounded by the selected types of activities that acquire and use it. Business process model A graphic and descriptive representation of business processes or value chains that cut across functions and organizations. The model may be expressed in different levels of detail, including decomposition into successive lower levels of activities. Business process reengineering The process of analyzing, redefining, and redesigning business activities to eliminate or minimize activities that add cost and to maximize activities that add value. Business requirements data model A structured representation and corresponding definitions of the kinds of Information required for the business to operate, comprised of Entity types and the relationships between them. Sometimes this includes attributes, Sometimes not, depending on the System Development Lifecycle and modelling standards followed. It provides the architectural context for the Development of the Enterprise Logical Data Model. Also referred to as Business Area Information Model. See also Conceptual Data Model Business rule A statement expressing a policy or condition that governs business actions and establishes data integrity guidelines. A business rule statement must always be true.
C	Cardinality The number of occurrences that may exist between occurrences of two related entity types. The cardinalities between a related pair of entity types are: one to one, one to many, or many to many. See also Relationship CASE Acronym for Computer-Aided Systems Engineering. The application of automated technologies to business and information modelling and software engineering. Chief Information Officer (CIO) A Senior Manager who ensures the organization uses information management and information technology (IM/IT) efficiently, within government guidelines. Defines the IM/IT infrastructure for the organization. See also Ministry Chief Information Officer. CIO Acronym for Chief Information Officer. Completeness A characteristic of information quality measuring the degree to which all required data is known. (1) Fact completeness is a measure of data definitions quality expressed as a percentage of the attributes about an entity type that need to be known to assure that they are defined in the model and implemented in the database. (2)Value completeness is a measure of data content quality expressed as a percentage of the columns or fields of a table or file that should have values in them, in fact do so. Concatenated primary key See Primary Key. Conceptual data model A model developed in the earlier phases of the system development process. It is primarily created to scope the data requirements and then capture the business view of the data. No technical details regarding the data structure are introduced at this level. Details of the entities in terms of most of its actual atomic data contents (the as “attributes”) and the relationships between the entities are captured in this model. Concurrency A characteristic of information quality measuring the degree to which the timing of equivalence of data is stored in redundant or distributed database files. The measure of data concurrency may describe minimum, maximum, and average information float time from which data is available in one data source and when it becomes available in another data source. Or it may consist of the relative percent of data from a data source that is propagated to the target within a specified time frame. Constraint A business rule that places a restriction on business actions and therefore restrictions on the resulting data. Corporate application A computer application that affects corporate data or is designated at the planning stage as a corporate application, thus requiring the highest levels of quality assurance in its development. Corporate business model A model that captures the overall structure of organizational data, while being independent of any data base management system or other implementation consideration. The model includes the business rules and constraints that define how the data are used. Corporate data The data that is of a permanent or lasting nature and is critical to the operation of the organization, potentially used by many staff or by different program areas. Because corporate data is relied on to be accurate, meaningful, and available, it is managed rigorously according to standards for definition, collection, accuracy, entry, use, update, and disposal. See Enterprise data. Corporate data model The consolidation of all individual system data models of a given type (conceptual, logical, or physical) that an enterprise has. Individual system data models my have common entities reflecting data sharing within the enterprise. Each type of data models is consolidated independently to the corresponding corporate data model. Data sharing and re-use of data model portions is promoted through such corporate data models. Corporate database The electronic collection of observable recordable facts that should conform to an Enterprise Data Standard. See also Enterprise Data Standard. Corporate function model A structured representation and corresponding definitions of the kinds of activities performed by the Enterprise. See also function, function decomposition diagram, process and process model. Corporate resource An Enterprise source of supply or support. (people, money, materials, facilitates, information) Critical success factor A situation that must go right for an Enterprise Goal to be achieved. Failure of a CSF results in failure to achieve the affected Goal(s). CRUD matrix A CRUD Matrix is produced during the analysis of how a given entity is used by a business process. The business processes are placed on one axes of the matrix and entities on the other axis. CRUD is short for Create, Retrieve, Update, Delete. By analysing function to data relationships, missing business functions or data elements are uncovered as well as redundancies. Also referred to as Entity/process matrix. Currency A characteristic of information quality measuring the degree to which data represents reality from the required point in time.
D	Data The data that is an individual fact or multiple facts, or a value, or a set of values, but is not significant to a business in and of itself. Data is the raw material stored in a structured manner that, given context, turns into information. See also Information. Data acquisition The process of receiving data from internal or external sources. Data administration A high-level function that is responsible for the overall management of data resources in an organization, including maintaining corporate-wide definitions and standards. This may include: identifying opportunities for data sharing and integration, ensuring data security (as part of the data architecture), reducing data redundancies between program areas, promoting and enforcing the use of standards, etc. (Modern Data Management, 4th edition, 1994.D34) Data administrator A technical expert with a corporate role, providing information management leadership, data modelling expertise, and custodianship of the corporate data models. Promotes consistency in scope, meaning, and handling of data across the entire organization. Data application See Application System. Data architecture A framework for organizing the interrelationships of data, (based on an organization’s missions, functions, goals, objectives, and strategies), providing the basis for incremental, ordered design and development of systems based on successively more detailed levels of data modelling. Data cleansing The process to correct data errors in a collection of data in order to bring the level of quality to an acceptable level to meet the information customers' needs. Data custodian A Senior Manager for a business area responsible for data requirements, standards, access rules, business training, etc. Defines the business value, scope, standards and services of the organization’s data within the context of their mandate. Data custodianship The role that hold the functional responsibility for collection and maintenance of data. This includes responsibility for its integrity, completeness, quality, security and currency. Data definition The specification of the meaning, domain values, and business integrity rules for an entity type or attribute type. Data definition includes name, definition, and relationships, as well as domain value definition and business rules that govern business actions that are reflected in data. This term is synonymous with the term metadata. Data Definition Language (DDL) The language used to describe database schemas or designs. Data dictionary A repository of information (metadata) defining and describing the data resource. A repository containing metadata. An active data dictionary, such as a catalog, is one that is capable of interacting with and controlling the environment about which it stores information or metadata. An integrated data dictionary is one that is capable of controlling the data and process environments. A passive data dictionary is one that is capable of storing metadata or data about the data resource, but is not capable of interacting with or controlling computerized environment external to the data dictionary. See also Repository. Data domain The set of allowable values for a data item (attribute). Data driven A method of application development that focuses on data as an enterprise resource and automates activities as a part of an integrated business value chain. Data element The smallest unit of named data that has meaning to a knowledge worker. A data element is the implementation of an attribute. Also referred to as data item and field. Data flow diagram A graphic representation of the "flow" of data through business functions or processes. It illustrates the processes, data stores, external entities, data flows, and their relationships. Data format The specification of a data item's structure as it is physically stored. For example, character, numeric, date, binary. Data integration The process of blending data items from various distinct sources to create a larger and more comprehensive body of knowledge. Data integrity A property of data in which all assertions (accurate, current, consistent, complete) hold. Data item See Attribute. Data length The maximum number of characters or numbers that may be stored in a field (attribute). Data management The activities of strategic data planning, data element standardization, information management control, data synchronization, data sharing, and database development. Active data management increases system effectiveness and improves the accuracy and timeliness of data to derive maximum business benefit. (Core Policy Manual (Ch. 12): 12.3.2 iii Data Management) Data manager A business expert with detailed knowledge of the data structure, content, and appropriate use of the business information. Data Manipulation Language (DML) The language used to access data in one or more databases. Data mart A subset of enterprise data along with software to extract data from a data warehouse or operational data store, summarize and store it, and to analyze and present information to support trend analysis and tactical decisions and processes. The scope can be that of a complete data subject or of a particular business area or line of business. A data mart architecture, whether subject or business area, must be an enterprise-consistent architecture. See also Data Warehouse, Operational Data Store. Data mining The process of analyzing large volumes of data using pattern recognition or knowledge discovery techniques to identify meaningful trends and relationships represented in data in large databases. Data model A graphical (Entity Relationship Diagram or ERD) and textual (data dictionary) representation of the business data deemed of interest to an organization. It is a representation of data objects that can be shared and reused across application systems, organizational boundaries, and different functional areas.  See also Entity Relationship Diagram. Data model types The scope and usage of the data models categorize them and determine the levels of details and abstraction required by these categories. Data modelling tasks are spread longitudinally along the system development process in its various phases and as one proceeds along these phases: (a) Conceptual Data Model, (b) Logical Data Models, and (c) Physical Data Model are developed in that order. Data modelling The task in which data models are developed. Usually both the IT people and the data users from the business work jointly on this task. This ensures that the user’s perception and needs are appropriately understood and accounted for within the data models. Data object See Entity Type. Data planning The process of planning for the acquisition of data for loading into operational systems or for preparing for analysis. Data quality The state of completeness, validity, consistency, timeliness and accuracy that makes data appropriate for a specific use. Data reengineering The process of analyzing, standardizing, and transforming data from unarchitected or nonstandardized files or databases into an enterprise-standardized information architecture. Data requirement The definition of data required to support business processes. Data standard A uniform definition for a data item which establishes rules, principles and measures for the collection, storage, use and interpretation of the data. See also Enterprise Data Standard. Data steward See Data Custodian. Data store A place in a system where data is stored. This includes manual files, machine-readable files, data tables, and databases. A data store on a logical data flow diagram is related to on or more entity types in the data model. Data structure The logical arrangement of data as used by a system for data management; a representation of a data model in computer form. Data transformation The process of defining and applying algorithms to change data from one form or domain value set to another form or domain value set in a target data architecture to improve its value and usability for the information stakeholders. Data type An attribute of a data element or field that specifies the DBMS type of physical values, such as numeric, alphanumeric. Data usage The guideline that pertain to how a data item or data set should be used in support of business function. Data usage contact A technical database resource or sophisticated business user who understands the business data and how it has been physically implemented. Manipulates and queries physical database content to support operational information needs. May also define user views for repeated queries. A primary resource for the Data Manager. Data warehouse A collection of software and data organized to collect, cleanse, transform and store data from a variety of sources, and analyze and present information to support decision-making, tactical and strategic business processes. Database A collection of interrelated data, often with controlled redundancy, organized according to a schema to serve one or more applications; the data are stored so that they can be used by different programs without concern for the data structure or organization. A common approach is used to add new data and to modify and retrieve existing data. Database administration The function of managing the physical aspects of the data resource, including physical database design to implement the conceptual data model; and database integrity, performance, and security. Database administrator A technical expert with detailed knowledge of database management, design, optimization and operation. Develops physical data structures in consultation with the Data Administrator, systems development and maintenance teams. Implements physical data structures on appropriate platforms. DDL Acronym for Data Definition Language. Decomposition A process by which something is broken in to its constituent parts. Derived data The data that is created or calculated from other data within the database or system. DFD Acronym for Data Flow Diagram. Discipline authority A business expert or specialist who fully understands the business relevance of the data standards within their scope of work. They must actively use their knowledge in support of the broad scope of business and established data standards. Interprets the meaning and appropriate use of detailed data standards to meet organizational needs. A primary resource for the Data Manager. DML Acronym for Data Manipulation Language. Document An original or official paper relied on as the basis, proof, or support of something. Domain A set of business validation rules, format constraints and other properties that apply to a group of attributes, e.g. a list of values, or range, or any combination of these. Attributes in the same domain are subject to a common set of validation tasks.
E	E-commerce Acronym for electronic commerce. The conducting of business transactions over the Internet. EIS Acronym for Executive Information System. Elementary process The lowest level activity breakdown in a process hierarchy The data input must be transformed by the activity in the elementary process into a different data output. Encyclopedia See Repository. Enterprise An organization with autonomous control over its own approach to Information Resource Management. Enterprise activity model A structured, graphical representation of the activities performed in an enterprise and the interrelationship among them. Enterprise architecture The set of descriptive representations (i.e. models) that are relevant for describing an Enterprise such that is can be produced to management’s requirements (quality) and maintained over the period of its useful life (change). See also Framework for Enterprise Architecture. Enterprise data The data of an organization or corporation that is owned by the enterprise and managed by a business area. Characteristics of enterprise data are that it is essential to run the business and/or it is shared by more than one organizational unit within the enterprise. Enterprise data standard The definition of how facts are to be referred to, how they are to be represented, what they will mean , and the rules governing their informational use throughout the enterprise. Enterprise data standards are an outgrowth of logical data modelling. Enterprise information model A structured representation of the kinds of information required for the enterprise to operate, generally used to support development of an IRM strategy. Enterprise information model reflects entity types and the relationships between them, but does not include any attribute types. It provides an architectural context for developing logical data models. Also referred to as a Corporate Conceptual Data Model. Enterprise repository See Repository. Entity An object about which the business wishes to collect information; a person, place, thing, event or concept of importance to the enterprise that is singular, exclusive, and uniquely identifiable. The metadata for an entity is entity name, entity definition, unique identifier. Entity definition A concise definition of the nature of the entity (type). Entity Relationship Diagram (ERD) A graphical representation of data and it’s interrelationships. Entity subtype A specialized subset of occurrences of a more general entity type, having one or more different attributes or relationships not inherent in the other occurrences of the generalized entity type. Entity supertype A generalized entity type in which some occurrences belong to a distinct, or specialized subtype. Entity type A classification of the types of real-world objects (such as person, place, thing, concept, or events of interest to the enterprise) that have common characteristics. Sometimes the term entity is used as a short name. Entity/process matrix A matrix that shows the relationship of the processes, identified in the business process model, with the entity types identified in the information model. The matrix illustrates which processes create, update, reference or delete the entity types. Also referred to as CRUD Matrix. ERD Acronym for Entity Relationship Diagram. Event An essential business condition, a state or a requirement that exists which the target business system/area must respond to or deal with in order to carry on business operations to successfully support its key business objectives, goals, mission, direction and vision. Executive Information System (EIS) A graphical application that supports executive processes, decisions, and information requirements. Presents highly summarized data with drill-down capability, and access to key external data.
F	Field A data element or data item in a data structure or record. Framework for enterprise architecture A comprehensive classification scheme for descriptive representations, i.e. “models”, of an enterprise. Function An enterprise activity that is continuous in nature having no discernible way to distinguish among the starting and stopping of individual instances of its execution, e.g. manage human resources, manage information resources, etc. A function describes what activities the business does or needs to do, not how it does it. Functional decomposition diagram A hierarchical, graphical representation of high level functions and the lower level functions they are decomposed into. Functional dependency The degree to which an attribute is an inherent characteristic of an entity type. If an attribute is an inherent characteristic of an entity type, that attribute is fully functionally dependent on any candidate key of the entity type.
G	Generalization The process of aggregating similar types of objects together in a less specialized type based upon common attributes and behaviours. Identification of a common supertype of two or more specialized (sub)types. Geodetic control A system of 50,000 monuments dispersed throughout the Province which are accurately georeferenced to allow for subsequent georeferencing by various land applications. The monuments' coordinates (latitudes, longitudes and elevations) define the NAD83 and CVD28 standards for the Province in accordance with national and international standards. Geographic data The data which records the shape and location of a feature as well as associated characteristics, which define and describe the feature. For example, areas of woodland can be located according to co-ordinate grid system references, and its attribute data such as constituent tree type, seasonality or average height can also be recorded. See Spatial Data. Georeferencing The process of delimiting a given object, either physical (e.g.. a lake) or conceptual (e.g.. an administrative region), in terms of its spatial relationship to the land; the geographic reference thus established consists of points, lines, areas or volumes defined in terms of some coordinate system (usually latitude and longitude, or UTM northings and eastings, and elevation). Explicit georeferencing may be direct or indirect. Direct georeferencing may be achieved by linking to geodetic control monuments that define the Geodetic Reference System (system of latitudes, longitudes and elevations) on the ground. Indirect georeferencing may be achieved by linking to objects or features previously directly georeferenced. Map matching is an example of indirect georeferencing. Implicit georeferencing may utilize a land addressing system that is different from a mathematical coordinate system. Municipal street addresses, highway kilometre posts, and administrative zones are examples of land data tagging that do not conform to the NAD83 standard, yet data sets that employ such implicit georeferencing methods are seen to fall within the LIMF purview. Presentation of georeferenced map data should utilize the NTS and BCGS map series definitions. Geospatial data The data that is referenced to geographic locations on the earth's surface by a system of geographic coordinates. Global Positioning System (GPS) A satellite-based radio-navigation system launched by the United States Department of Defence for military purposes and made available for civilian access. Though a complex system, GPS allows users to achieve accuracies ranging from millimetres to 100 metres, depending on equipment and procedures utilized. Relative GPS techniques, whereby two or more GPS receivers are used in differencing mode, are usually needed to achieve the millimetres to 25 metres accuracy.
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I	IM Acronym for Information Management Information The data in context. The meaning given to data or the interpretation of data based on its context. The finished product as a result of the interpretation of data. Information architecture A "blueprint' of an enterprise expressed in terms of a business process model, showing what the enterprise does, an enterprise information model, showing what information resources are required; and a business information model, showing the relationship of the processes and information. Information engineering A cohesive framework of interconnected beliefs and practices that facilitates achievement of optimum reliability, shareability and usefulness of information throughout the Enterprise as a whole. (This is a style of Information Resource Management - the Enterprise function responsible for ensuring optimum quality, shareability and accessibility of data, and efficient use of computer and communications technology.) Information Management (IM) Information Management is the function of managing information as an enterprise resource, including planning, organizing and staffing, and leading, directing, and controlling information. This includes managing data as enterprise knowledge, managing technology as the enterprise technical infrastructure, and managing applications across business needs. Information model A high-level graphical representation of the information resource requirements of an organization showing the information classes and their relationships. Information producer The role of individuals in which they originate, capture, create or maintain data or knowledge as part of their job function or as part of the process they perform. Information producers create actual information content and are accountable for its accuracy and completeness to meet all information stakeholders' needs. Information quality The degree to which information consistently meets the requirements and expectations of the knowledge workers performing their jobs. Information Resource Management (IRM) Information Resource Management is the concept that information is a major corporate resource and must be managed using the same basic principles used to manage other assets. This includes the effective management and control of data/information as a shared resource to improve the availability, accessibility and utilization of data/information within government, a ministry or a program. Data administration and records management are key functions of information resource management. (Core Policy Manual (Ch. 12): 12.3.2 iii Data Management) Information system A collection of manual and automated components that manages a specific data set or information resource. Information value The measure of importance of information expressed in tangible metrics. Information has realized and potential value. Realized value is actual value derived from information applied by knowledge workers in the accomplishment of the business processes. Potential value is the future value of information that could be realized if applied to business processes in which the information is not currently used. IRM Acronym for Information Resource Management.
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K	Knowledge The information context; understanding the significance of information. Knowledge worker The role of individuals in which they use information in any form as part of their job function or in the course of performing a process, whether operational or strategic. Also referred to as information consumer, or customer. Accountable for work results created as a result of use of information and for adhering to any policies governing the security, privacy, and confidentiality of the information used.
L	Legacy system A system that is developed without using an enterprise data architecture approach. Local corporate data The data that has meaning in the context of a local office program only (e.g. in an organization that has multiple region, district, or field offices). The staff who create Local Corporate data have defined a repeatable process (i.e., the collection process is defined enough for a person to redo the same thing and get the same results), but since it is not fully defined and published, other groups, sections, or offices in the organization will not be able to use it properly. Similar information with different definitions or interpretations may exist elsewhere. Because of the different definitions or collection standards, when different offices try to share the data there will be formatting and translation problems; therefore requiring significant effort before each sharing attempt can actually take place. What sets Local data apart from Non-corporate data is the staff judgement that the data is vital to the organization’s (local) business, and is permanent (i.e. has lasting value). Logical data model A logical view of the conceptual data model. Data Architecture theories such as the “normalization” are applied to transform the conceptual data model into the logical data model that moves the data modelling further towards the ultimate prescription for the data architecture to be implemented. Relationships get absorbed as “attributes” known as foreign keys or pointers within appropriate logical model entities. This may be explicit or implied in the logical data model. As long as the resulting physical data model includes the necessary foreign key columns and joins, the inclusion of foreign-keys in the logical data model is a matter of convenience. Logical Data Model does not have any specific restrictions and/or requirements imposed by the Database Management System (DBMS) to be used for creating the actual database.
M	Metadata The information about data that enables intelligent, efficient access and management of data from creation through long term use. One of the primary purposes of organizing the metadata is to be able to describe and communicate business and technical information to persons within the organization. Methodology A formalized collection of tools, procedures, and techniques to solve a specific problem or perform a given function. Ministry chief information officer A Chief Information Officer within the context of a ministry. See also Chief Information Officer. Ministry executive A member of the organization’s executive, responsible for developing the policy framework within their division’s line(s) of business. Defines the strategic value and scope of the organization’s data and overall business services within the full context of their organization. Model A graphical representation of the thing that is to be made, modified, or understood. Some of such things cannot be actually observed and felt until they are built while some others cannot be easily understood without the models. A preliminary design work that serves as a plan from which a final product is to be made. Models are used to understand, design, and then construct complicated things or concepts such as buildings, machines, and computers, programs that run on the computers, aircrafts, processes, and theories.
N	Non-corporate data The data that is either not vital to the interests of the organization, or not stored for a long enough time period, to make it valuable. Non-corporate data is generally defined and collected in a completely ad-hoc manner with no common standards; therefore the quality of the data depends completely on the person who defines and collects it. Examples of Non-corporate data are meeting notices, informal agendas, personal calendars, information on scraps of paper, temporary files, or temporary spreadsheets. Non-corporate data is still useful, but not relied on for making critical decisions or providing specific information (the intent is quick results). Note that the boundary between corporate and non-corporate data will often be a human decision. See also Corporate Data. Normalization A method used to eliminate redundancy in data definitions, especially for entity relationship models. Different levels of normalization are defined with a set of qualifying constraints for the definitions. The most common normal forms are referred to as first though fifth normal forms.
O	Occurrence A specific instance of an entity type. ODS Acronym for Operational Data Store. OLAP Acronym for On-line Analytical Processing. OLTP Acronym for On-line Transaction Processing. On-line Analytical Processing (OLAP) A software technology that transforms data into multidimensional views that supports multidimensional data interaction, exploration, and analysis. Operational data The data at a detailed level used to support daily activities of an enterprise. Operational Data Store (ODS) A collection of operation or bases data that is extracted from operation databases and standardized, cleansed, consolidated, transformed, and loaded into an enterprise data architecture. An ODS is used to support data mining of operational data, or as the store for base data that is summarized for a data warehouse. The ODS may also be used to audit the data warehouse to assure summarized and derived data is calculated properly. The ODS may further become the enterprise shared operational database, allowing operational systems that are being reengineered to use the ODS as there operation databases. Optionality - attribute type An attribute of an entity that is optional. A row of the corresponding table in the physical implementation can exist even if the value for the column corresponding to such attribute is 'null' i.e. it has not been assigned a value. Note that for a row of a table to exist all its non-null columns (corresponding to the attributes that are not optional) must have a value. Optionality - relationship The state of a data relationship between two data entities as being optional, e.g. An employee may or may not have a spouse.
P	Package implementation model A structured, graphical representation of the implemented business solution provided via a packaged software. This is the physical implementation model as opposed to the business model for which it represent the physical solution. Package solution data model A structured, graphical representation of the data that is to be used and/or created by a packaged software solution. Note that this data model is usually not available to the purchaser of the software solution which makes it difficult to integrate the corresponding system with other systems used by the business. Physical database design The mapping of conceptual or logical database design data groupings into physical database areas, files, records, elements, fields , and keys while adhering to the physical constraints of the hardware, DBMS software, and communications network to provide physical data integrity while meeting the performance and security constraints of the services to be performed against the database. Process driven A method of application development that focuses on automation of processes and establishing the applications own data standards and is not focused on data as an enterprise resource . The process driven approach is known to inhibit the acquisition and sharing of enterprise data. Process model The graphical representation of processes, including a hierarchy of relationships between them. Process models capture the essence of the system being configured and developed. A given process may be used in the delivery of more that one function Process modelling The task in which process models are developed. Usually both the IT people and the system users from the business work jointly on this task. This ensures that the user’s perception and needs are appropriately understood and accounted for within the process models. Project A temporary endeavour undertaken to create a unique product or service. Project manager The individual responsible for managing the project. Project sponsor The individual for whom the project is being undertaken.
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R	Referential integrity The integrity constraints that govern the relationship of an occurrence of one entity type or file to one or more occurrences of another entity type or file. Referential integrity defines constraints for creating, updating, or deleting occurrences of either or both entity types or files. Relationship The manner in which two entity types are associated with each other. Relationships may be one to one, one to many, or many to many as determined by the meaning of the participating entities and by business rules. Relationships expresses cardinality (the number of occurrences of one entity related to an occurrence of the second entity, and optionality (whether an occurrence of one entity type is a requirement given an occurrence of the second entity type). Relationship name A verb or verb phrase that describes the business meaning of the relationship between the two information assets.   Relationship type See Relationship. Repository An automated tool that facilitates the capture, maintenance and utilization of information about the enterprise. The repository is where Enterprise data standards are recorded, and is used to track their utilization throughout the enterprise.
S	SAIF Acronym for Spatial Archive and Interchange Format. SAIF one of two Canadian National Standards for Geomatics data interchange. Designed by the Government of British Columbia, SAIF is a specification for data which includes an object-oriented data model. SAIF uses an OO model to define schemas for spatial, temporal and conventional attribute data. SAIF uses a language - Class Syntax Notation (CSN) - for describing both geographical and non-geographical data and employs a specification for the binary exchange format. The SAIF format is augmented by Profile specifications which provide detailed instructions regarding modelling and encoding data in the SAIF format and by a SAIF/Toolkit (under development) which is provided to assist vendors in the development of software for encoding and decoding digital data to and from SAIF and their respective vendor-specific data formats. SDLC Acronym for System Development Life Cycle. Spatial modelling The analytical procedures applied with a GIS. There are three categories of spatial modelling functions that can be applied to geographic features within a GIS: 1, geometric models, such as calculating the Euclidean distance between features, generating buffers, calculating areas and perimeters; 2, coincidence models, such as overlays; and 3, adjacency models (pathfinding, redistricting, and allocation). All three model categories support operations on spatial data such as points, lines, polygons, tins, and grids. Subject area Subject Area is a business classification of data that the enterprise must manage across business functions and organizations, as used in high-level information modeling. Typical subject area categories are human resource, financial, materials and products, facilities and tangible assets, and information. Subtype See Entity Subtype. Supertype See Entity Supertype. System Development Life Cycle (SDLC) The methodology of processes for developing new application systems. Generally, the phases are requirements definition, analysis, design, testing, implementation, and maintenance.
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Z	Zachman framework See Framework for Enterprise Architecture