Terms A - C
| Term | Definition | Source |
|---|---|---|
| Accessibility | The ease with which data or information can be retrieved, used and understood. | NSW Government Standard for Data Quality Reporting |
| Accuracy | The degree to which the data or information correctly describes what they were designed to measure, monitor, or report, i.e., the consistency of data with reality. | NSW Government Standard for Data Quality Reporting |
| Administrative data | Data or information created or collected through:
Administrative data is often collected as a by-product of operations rather than for analytical purposes. | NSW Government Standard for Data Quality Reporting |
| Agency | A Public Service agency as defined by the Government Sector Employment Act – see also Schedule 1 of the GSE Act. | |
| Aggregate data | Data that has been combined or de-identified, for example so that it no longer identifies specific individuals or locations. | Digital.NSW – Managing Data & Information |
| Artificial intelligence | Artificial Intelligence, or AI, is intelligent technology, programs and the use of advanced computing algorithms that can augment decision making by identifying meaningful patterns in data. | NSW Government AI Strategy |
| Artificial Intelligence, machine learning and predictive analysis | The design, management and implementation of processes to enable machines to learn from experience, through processing large amounts of data and recognising patterns in the data, to automate activities or make predictions about the future. | NSW Information Management Framework (IMF) |
| Business system | Organised collection of hardware, software, supplies, policies, procedures and people, which stores, processes and provides access to an organisation’s business information. | ISO 23081-2.2009 Part 2, Clause 3.3 |
| Closed data | Closed data is restricted and may be sensitive or highly sensitive data. It can only be accessed by a particular business unit (its owner or custodian), or a subset of approved individuals or organisations for the authorised purpose for which they hold the data. Closed data is generally not released outside of the organisation, and in some cases it is not released outside of the business unit. | NSW Data Leadership Group |
| Cluster | The nine groups into which NSW Government departments, agencies, and state owned corporations are organised to enhance coordination and provision of related services and policy development (This reflects the Machinery of Government changes effective 1st July 2019). | NSW Government Departments and agencies |
| Coherence | The degree to which data or information can be compared with itself and other information over time. | NSW Government Standard for Data Quality Reporting |
| Comparable | Information that can be compared, is similar, is worthy of comparison. Comparability refers to the extent to which differences between statistics for different places or times can be attributed to real differences between the things being measured | NSW Government Standard for Data Quality Reporting |
| Creative Commons | Licensing framework used to facilitate open data practices. NSW Government Open Data Policy supports Creative Commons licensing for government data and information. | Creative Commons Australia |
| Custodian | See “Data Custodian” in Terms D-F | |
| Customer | A customer of NSW Government is anyone who lives, works, visits or invests in NSW. Customers include people and businesses who want to or are required to interact with Government, including people serving custodial sentences. The principles of customer service can be applied in the regulatory environment. | |
| Cyber security | Measures used to protect the confidentiality, integrity and availability of systems and information. | NSW Cyber Security Policy |
Terms D - F
| Term | Definition | Source |
|---|---|---|
| Data | Data is a broad term, the definition of which is heavily impacted by context. Data generally refers to facts and figures that can be represented as numbers, text, graphics, sound or video, as well as how these are interpreted. Data can also take different forms e.g. digital, and can pertain to a range of topics or areas e.g. people, systems and the environment. Data can further be broken down by type or purpose, for example transactional and operational data. | NSW Data & Information Custodian Policy |
| Data analytics | The process of manipulating data in different ways with the goal of discovering insights. | Digital.NSW – Managing Data & Information |
| Data asset | A data asset is a structured collection of data developed for a broad purpose. An enduring data asset (or enduring linked data asset) is a subset of this category, denoting the linkage of a larger range of data that is designed for potentially many purposes and users. An example of this is the NSW Human Services Data Set. A data asset could also include models, methodologies and algorithms. | |
| Data breach | An incident that results in unauthorised access to modification or disruption of data, applications, services, networks and/or devices by bypassing their underlying security mechanisms. | NSW Cyber Security Policy – Glossary |
| A data breach occurs when there is a failure that has caused or has the potential to cause unauthorised access to your Agency’s data. Although malware, hacking and data theft are usually the first examples of data breaches that come to mind, many breaches are a result of simple human or technical errors rather than malicious intent. | Information and Privacy Commission NSW | |
| Data custodian | The agency, body or position designated with the custody of a specified dataset or information asset. The custodian is responsible for:
This term is often used interchangeably with ‘Data Owner’. | NSW Data & Information Custodianship Policy, Appendix: A |
| Data ethics | An evaluation of data practices with the potential to adversely impact on people and society – in collection, sharing and use. | The Open Data Institute (ODI) |
| Data governance | Implementation of a set of policies, processes, structures, roles and responsibilities to ensure that an agency’s data is managed effectively and that it can meet its current and future business requirements. | NSW Data Governance Toolkit |
| Data life cycle | A data life cycle illustrates the stages of data management required over time, from the time of planning and creation to the time that data is either archived or destroyed. | |
| Data management | Data management refers to the activities involved with managing data across the full lifecycle so that it is protected from unauthorised use and inappropriate deletion. Data needs to be appropriately managed from procurement or service design through to creation and final disposal. This includes protection of personal, health and sensitive information, and the prevention of deletion until enabled by legal authorisation. | NSW Data Governance Toolkit |
| Data owner | This term is often used interchangeably with ‘Data Custodian’. | Information Data Management Framework (IDMF): Appendix B: Terminology |
| Data quality | Data quality is generally accepted as meaning “fitness for purpose”. The Australian Bureau of Statistics (ABS) Data Quality Framework contains seven characteristics of quality:
Data quality is evaluated in terms of how well the characteristics of the data meet the needs or objectives of a user. | NSW Government Standard for Data Quality Reporting |
| Data security | What is considered a secure data storage, process, transmission or technology | |
| Data set (or dataset) | A dataset is an identifiable collection of government-held information or data and associated metadata. | |
| Data sharing | The exchange of data between entities. Restrictions and controls imposed are contingent upon the data’s sensitivity and privacy impact. | |
| De-identified data | Data that no longer contains, or never included, identifiers about a person, such that their identity is no longer apparent or reasonably ascertainable from the data. Re-identification also needs to be either impossible, or extremely difficult. | Adapted from the IPC |
| Five Safes Framework | The Five Safes Framework was originally developed in the United Kingdom at the Office of National Statistics. The Framework consists of five elements which define independent but related aspects of disclosure risk:
The Five Safes Framework has formed the basis of data protection legislation, policy and guidance for Commonwealth and State jurisdictions: Australian Bureau of Statistics (ABS) Australian Institute of Health and Welfare (AIHW) Office of the National Data Commissioner (ONDC) New South Wales (NSW): Data.NSW |
Terms G - L
| Term | Definition | Source |
|---|---|---|
| Health information | As defined in section 6 of the Health Records and Information Privacy Act 2002 (NSW) (HRIP Act): (a) personal information that is information or an opinion about— (i) the physical or mental health or a disability (at any time) of an individual, or (ii) an individual’s express wishes about the future provision of health services to him or her, or (iii) a health service provided, or to be provided, to an individual, or (b) other personal information collected to provide, or in providing, a health service, or (c) other personal information about an individual collected in connection with the donation, or intended donation, of an individual’s body parts, organs or body substances, or (d) other personal information that is genetic information about an individual arising from a health service provided to the individual in a form that is or could be predictive of the health (at any time) of the individual or of a genetic relative of the individual, or (e) healthcare identifiers, but does not include health information, or a class of health information or health information contained in a class of documents, that is prescribed as exempt health information for the purposes of this Act generally or for the purposes of specified provisions of this Act. | Health Records and Information Privacy Act 2002 (NSW) (HRIP Act), section 6 |
| Indigenous data | Indigenous data is information or knowledge, in any format or medium, which is about and may affect Indigenous peoples both collectively and individually. | |
| Indigenous data governance | Indigenous Data Governance is the right of Indigenous peoples to autonomously decide what, how and why Indigenous Data are collected, accessed and used. It ensures that data on or about Indigenous peoples reflects their priorities, values, cultures, worldviews and diversity. | |
| Indigenous data sovereignty | Indigenous Data Sovereignty is a global movement concerned with the right of Indigenous peoples to govern the creation, collection, ownership and application of their data | |
| Information | Knowledge concerning objects such as facts, events, things, processes or ideas including concepts that within a certain context have a particular meaning. Information is data that has been processed into a form (physical, oral or electronic) that is meaningful to the recipient. This definition is included by not limited to:
| Information Data Management Framework (IDMF): Appendix B: Terminology |
| Information security | The protection of information and information systems from unauthorised access, use, disclosure, disruption, modification or destruction in order to provide confidentiality, integrity and availability. | NSW Cyber Security Policy - Glossary |
| Infrastructure data | Data or information relating to the planning, design, construction, operation and maintenance of infrastructure. | Information Data Management Framework: Appendix B: Terminology |
| Insights | Meaningful and actionable findings emerging from processed data, that can be leveraged to optimise decision-making processes. | |
| Institutional environment | A reporting quality relating to the institutional and oranisational factors which may have a significant influence on the effectiveness and credibility of the agency producing the data or information. | NSW Government Standard for Data Quality Reporting |
| Internet of Things (IoT) | The Internet of Things (IoT) refers to physical devices that are connected to the internet, collecting and sharing data. It is the global network of infrastructure, vehicles, wearable devices, home appliances, medical technologies and other objects that are embedded with electronics, software, sensors and actuators, enabling these ‘things’ to share and exchange data to perform their functions more efficiently and effectively (from NSW IoT Policy Guidance, p.1). | NSW IoT Policy Guidance |
| Interpretability | A reporting quality relating to the degree to which data or information can be understood, explained and used. | NSW Government Standard for Data Quality Reporting |
Terms M - Q
| Term | Definition | Source |
|---|---|---|
| Master data | Master data (or reference data) refers to the consistent set of identifiers and attributes that an organisation relies on to provide context for business transactions (e.g., information on customers, employees, locations, products and services). | NSW Data Governance Toolkit |
| Memorandum of Understanding (MoU) | A written agreement between two or more parties that defines the working relationship, expectations and responsibilities. MoUs are not usually legally binding on the parties. They are commonly used to clarify arrangements between non-corporate Commonwealth entities. | Australian Government, Department of Finance |
| Metadata | Data or information that describes, defines and adds meaning to other data, to support its interpretation. | |
| Open data | Open data is the proactive or on demand release of data or insights for public use, in any form and through any channel, with approval from the data custodian/owner prior to its release. It is provided by Governments for general use to support public sector accountability, encourage innovation and to achieve broad community benefits.
| NSW Data Leadership Group |
| Operational data | Any data which captures business activities. This can include compliance and administrative data. | |
Personal information (or personally identifiable information) | Information or an opinion (including information or an opinion forming part of a database and whether or not recorded in a material form) about an individual whose identity is apparent or can reasonably be ascertained from the information or opinion. | Privacy and Personal Information Protection Act 1998 (NSW) (PPIP Act), section 4 |
| Personal Information Factor (PIF) tool | The PIF tool is used to assess the risk of identifying an individual if they are not known to be in the datasets. If an individual is known to be in a dataset, the PIF tool provides a measure of the information that could be gained about them by accessing the dataset. The PIF outputs a score showing the distribution of ‘Row Information Gain’ (RIG) values for records in the data set. The highest value RIG defines the PIF for the data set. | More information: Personal Information Factor (PIF) tool |
| Platform | A system or group of technologies. | |
| Quality assurance checks | A system or series of activities for ensuring the maintenance of proper standards especially periodic interrogation and sampling of the product. | NSW Government Standard for Data Quality Reporting |
Terms R - Z
| Term | Definition | Source |
|---|---|---|
| Record | Any document or other source of information compiled, recorded or stored in written form or on film, or by electronic process, or in any other manner or by any other means. | State Records Act 1998 |
Any source of information created, received and maintained as evidence of the transaction of business. Examples include email approvals, outward correspondence, financial transactions in SAP. This information can be structured in business systems or reside in unstructured repositories. | ||
| Relevance | A reporting quality relating to how well data or information meets the needs of the user in terms of the concept(s) measured and the population(s) presented. | NSW Government Standard for Data Quality Reporting |
| Semi-structured data | Semi-structured data typically contains tags or labels that are used to identify separate data elements for example:
| Infrastructure Data Management Framework (IDMF) |
| Sensitive data or information | Per the NSW Government Information Classification, Labelling and Handling Guidelines (2020), sensitive information includes:
| NSW Government Information Classification, Labelling and Handling Guidelines (2020) |
| Sensor | A device which detects or measures a physical property and records, indicates or otherwise responds, including converting that detection into data. Examples of sensor detection/data include in relation to temperature, motion, pressure, light, smoke, and other environmental inputs. | |
| Shared data | Shared data is sensitive data that may be shared across government, or with trusted third parties. It may refer to a subset of data relevant to a specific purpose or recipient, with other parts of the wider dataset classified as Open or Closed data. Shared data usually contains sensitive information so that it needs approval from the data custodian/owner for an agreed, authorised purpose that benefits community outcomes, and with access controls in place in some scenarios.
| NSW Data Leadership Group |
| Spend category | A spend category is the logical grouping of similar expenditure items or services that have been clearly defined on an organisational level. For example, “information technology” may be considered a spend category covering both IT software and hardware. | |
| Structured data | Structured data is comprised of clearly defined data types stored in accordance with a pre-defined schema or model. The most common example of structured data would be data stored in a relational database. Structured data for infrastructure includes geometrical and non-geometrical spatial data. | Infrastructure Data Management Framework (IDMF) |
| Systems | Software, hardware, data, communications, networks and includes specialised systems such as industrial and automation control systems, telephone switching and PABX systems, building management systems and internet connected devices | NSW Cyber Security Policy - Glossary |
| Time Series | A record of activity where data is measured at regular intervals over a period of time (e.g., a monthly unemployment rate). Time series assist understanding of the current situation, enabling the most recent data observations to be placed in a meaningful historical perspective. | NSW Government Standard for Data Quality Reporting |
| Timeliness | A reporting quality relating to: • the time taken between the occurrence of the characteristics/events being measured and the release of the data or information output; and • whether the data or information output is sufficiently up-to-date for the user's purpose. | NSW Government Standard for Data Quality Reporting |
| Transactional data | Transactional data describe an internal or external event or transaction that takes place as an organisation conducts its business. Examples include purchase orders and product sales. These data are typically grouped into transactional records, which include associated master and reference data. | Definitions of Data Categories |
| Unstructured data | Unstructured data is comprised of data that has no pre-defined format or organisation and is usually not as easily searchable. It is most often categorised as qualitative data and can include formats like audio, video and social media postings. This kind of data typically resides in different databases/locations to structured data, and is difficult to process and analyse using conventional tools and methods such as organisation in relational databases. Finding insights from unstructured data is therefore complex and requires advanced analytics such as artificial intelligence/AI and a high level of technical expertise. | Infrastructure Data Management Framework |
| User | End consumer of a Data or Information resource; those who use Data or Information for reference, or as input to solve problems and/or make decisions. | NSW Data & Information Custodianship Policy |
Change requests
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Last updated 12 Jul 2024