Events
Access event
All events are open to anyone who is interested in the data quality topic.
In 2024, the group meets via zoom on the second Thursday (12-1pm AET) every two months starting in February.
If you are not yet a member of this interest group, please contact Mingfang Wu or Catherine Brady for how to join an event or how to join the group's mailing list to receive calendar invite of future events.
Recording of some presentations are available from the ARDC Youtube Channel.
Next event
Past events
April 11, 2024
Presentation title: Foundations of the Australian Companion Animal Registry of Cancers (ACARCinom): Ensuring Excellence through Quality, Standards, and Terminology (Slides, Presentation recording)
Speaker: Prof Chiara Palmieri (School of Veterinary Science, The University of Queensland)
February 8, 2024
Presentation title: Quality in FAIR: is your dataset/ repository ‘Barely FAIR’, ‘Human FAIR’, ‘Machine-Actionable FAIR’ and ‘WorldFAIR’ (Slides, Presentation recording)
Speaker: Dr. Lesley Wybore (NCI/AuScope/ARDC)
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December 7, 2023
Presentation title: Data Architecture Checklist (Slides, Presentation recording)
Speaker: Dr. Muhammad Ali (ARDC)
October 5, 2023
Presentation title: Leveraging data, analytics, and technology to build a valuable business asset (Presentation Recording)
Speaker: Dr. Prashanth H Southekal, DBP Institute, Calgary, Canada
July 6, 2023
Presentation title: Training Dataset for Machine Learning - quality considerations (Presentation Recording)
Speaker: Caitlin Adams and Madeleine Seehaber, FrontierSI
June 1, 2023
Presentation title: Role of data quality and data quality information in data search, access and reuse: Perspectives of researchers and data practitioners (slides)
Speaker: Dr. Mingfang Wu, ARDC
April 6, 2023
Presentation title: White Bandicoot - towards standards for automated data repository quality assessment (Presentation recording)
Speaker: Prof Dogie Boyle, University of Melbourne
February 2, 2023
Presentation title: FAIR Principles assessment of high-value geoscience datasets (slides, Presentation recording)
Speaker: Dr. Mark Rattenbury
December 1, 2022
Presentation title: Initial global metadata standards for processing of Earth Observation data over aquatic ecosystems (slides, Presentation recording)
Speaker: Dr. Arnold Dekke
November 3, 2022
Presentation title: Data Quality & Monetization (Slides, Presentation recording)
Speaker: Gnana Bharathy (ARDC)
October 6, 2022
Presentation title: CoreTrustSeal Requirements and Data Quality (Slides, Presentation recording)
Speaker: Richard Ferrers (ARDC)
September 1, 2022
Presentation title: Data quality and data governance (Slides, Presentation recording)
Speaker: Robin Burgess (ARDC)
July 7, 2022
Presentation title: Data quality assessment for both academic and commercial datasets.
Abstract: Our clients face pressures to deliver changes in their business that result in tangible gains from large investments, and there is little room for error in the current economic climate. We are often asked to provide factual data discovery with expert analysis to inform the size, scope, risk and return that may be possible from a data transformation and make recommendation that rely on our reputation. One of the key actions we take is to assess the quality of the data we receive from our discovery tools, and provide a view on the confidence of our recommendations. We continually refine the quality criteria for our work and what quality thresholds are required to make these recommendations. The result is that we provide our clients with an honest appraisal and subsequently they can make a wise judgement on how to proceed. We would like to share our learning with the group, dig into a little bit of detail around what data we collect and where we look for quality issues, and look at how we should be defining a common data quality standard for domains of research for both academic and commercial data, given the increasing desire to commercialise research.
Speaker: Benjamin Wu (NetApp) and Elia Machalias (Datalynx ) (Slides, Presentation recording)
April 7, 2022
Presentation Title: The Geoscience Australia Laboratory - today’s quality is tomorrow’s reputation (Slides, Presentation Recording)
Presenter: Dr. Keith Sircombe (Geoscience Australia)
March 3, 2022
Presentation Title: Data Quality Assessment Framework (NZ) (Slides, Presentation Recording)
Presenter: Liz Kolster (Department of Transport, NZ; Subject Matter Expert from Standard NZ to the ISO 19157-1 revision)
Blurb:
- What is the purpose of the “Data Quality Assessment Framework”?
The DQAF is an exemplar operational model for data quality management which describes the essential relationship between the business domain governance group and the enterprise data management team. At the highest level, the framework requires governance activities to support data investment and change management, such as preparation of data improvement plans and consideration of necessary communications with all stakeholders for involvement and informing.
- What is the goal of the "Data Quality Assessment Framework”?
" A data quality assessment framework will set forth an exemplar process to assess data quality along with useful tools and templates. This approach seeks to connect data quality measurement to relevant data requirements and improve compatibility of data quality evaluation and reporting across the data system." [excerpt from NZ Government Chief Data Steward, Data Strategy and Roadmap (2021)]
February 3, 2022
Dr. Ivana Ivanova (Curtin University, Group Chair of the OGC Data Quality DWG) presents: ISO 19157 collection of standards for Data Quality (Slides)
Mingfang Wu/Lesley Wyborn/Natalia Atkins report on the ESIP session on the session “Enhancing the Guidelines for sharing and reusing dataset information quality”
December 2, 2021
Arthur Chapman presented: Data Quality and Biodiversity DQ Standards (Slides, Presentation Recording).
April 1, 2021
This meeting is a joint meeting between the Australian/New Zealand Data Quality IG and the ESIP Information Quality Cluster.
Presentation 1:
Title: Data quality reporting at Integrated Marine Observing System (IMOS): Strengthening the Foundations that Underpin IMOS Slides Presentation recording
Presenter: Dr. Paul van Ruth (IMOS)
Presentation 2:
Title: Introducing Community Guidelines for FAIR data quality information Slides Presentation recording
Presenter: Dr. Ge Peng (Earth System Science Center/NASA MSFC Impact, The University of Alabama in Huntsville)
Presentation 3:
Title: Activity highlights from the ESIP Information Quality Cluster Slides Presentation recording
Presenter: David Moroni (Data Stewardship Team Lead, NASA Jet Propulsion Laboratory)
March 4, 2021
Title: Data quality framework for grains related trial research (title to be confirmed)
Presenter: Dr. Nathan Robinson (Federation University) (Presentation recording, slides)
Bird-of-Feather session "Developing community guidelines for consistently curating and representing dataset quality information", at the eResearch Australasia Conference 2020 .
Scheduled
meetings
meetings
The group meets on the first Thursday (12-1pm AET) each month via Zoom.
This document has an agenda for upcoming meetings and notes from past meetings.
Report from the Australia/New Zealand Data Quality Workshop
27 July, 2020
The Australian Data Quality Interest Group organised the Australia/New Zealand Data Quality Workshop on 6 July. This workshop aimed to discuss and gather community practices and requirements for data quality strategies and implementation plans across multiple research domains. The outcomes and path forward are summarised in these slides.
On behalf of the interest group, Dr. Ivana Ivanova (Curtin University) reported on this workshop output to the International Earth Science Information Partners (ESIP) Data Quality workshop. (Here are the recordings of the ESIP workshop presentation: Session 1, Session 2 and the notes are here).
Some issues and requirements identified from our Australian/NZ workshop, for example, a lack of organisational strategy for evaluating dataset quality, need for ‘common quality language’, guidelines on managing data provenance, etc. resonated with discussions from the international ESIP workshop. This manifests the issues we discussed are not alone to Australia/NZ, but apply to wider communities, and thus we should work together to face challenges.
The diagram below shows an idea on a community consensus on digital dataset lifecycle stages and associated information terminology. In this diagram, data quality dimensions (science, product, stewardship and services) are mapped to stages of dataset lifecycle, the mapping helps to clarify what types of data quality are talked about, whose responsibility and stakeholders in managing or reporting to data quality at different stage of dataset lifecycle.
The pathway forward is to develop community guidelines for consistently curating and representing dataset quality information, as stated in a proposal from the ESIP workshop to “develop community guidelines to help science data centers, repositories, data producers, publishers, data managers, stewards, and funders, etc., to consistently capture and present the quality information of their datasets in machine and human readable formats, allowing for the maximum reuse and value of their datasets. This effort requires a community-wide, cross-disciplinary effort to set a solid foundation for a wide implementation.”
