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(1) This standard defines the requirements for the quality of data and information of the (2) Authority for this document is established by the Information Governance Policy. (3) This standard applies to all staff with responsibility for creating, managing and using data at RMIT, including temporary employees, contractors, visitors and third parties globally who manage (4) High-quality data supports University strategy and enables quality insights and decision-making, driven by data that is trusted. (5) This standard provides the requirements for data quality as well as data quality dimensions and measures to support establishing and maintaining high-quality data at RMIT. (6) This standard should be used in conjunction with the Data Quality Guideline and supporting tools, which provide staff with further guidance on assessing and improving data quality and implementing this standard in practice. (7) Data created, managed and used at RMIT must be of high quality. Data will be considered high quality when it is fit for its intended purpose and meets the requirements of all stakeholders. (8) Data must meet stakeholder requirements for validity, completeness, accuracy, consistency, timeliness and uniqueness, in accordance with the data quality dimensions in this standard. (9) The level of data quality should be defined, assessed and measured so that it can be improved. (10) Data that does not meet the expected level of quality must be improved at the source, ie., at the point of data entry, creation or collection. Data that cannot be improved at the source must be corrected prior to use, for purposes such as reporting and analytics. (11) RMIT is required to ensure that the information it collects, uses, and discloses is accurate, complete, and up-to-date in accordance with relevant Victorian and Australian Privacy laws, specifically the Victorian Information Privacy Principles – IPP3 and the Australian Privacy Principle – APP10 regarding data quality. (12) The following data quality dimensions are most relevant to the Data Quality Standard
Section 1 - Purpose
Section 2 - Authority
Section 3 - Scope
Section 4 - Standard
Overview
Requirements
Data Quality Dimensions and Measures
* Adapted from DAMA-DMBOK : data management body of knowledge
Earley, S., Henderson, D. & Data Management Association, 2017. DAMA-DMBOK : data management body of knowledge / DAMA International ; senior editor, Deborah Henderson ; editor, Susan Earley ; production editor, Laura Sebastian-Coleman ; bibliography researcher, Elena Sykora ; collaboration tool manager, Eva Smith. 2nd ed., Bradley Beach, New Jersey: Technics Publications.