Data Quality DWG

Chair(s):

Beare, Matt (Beare, Matthew) - Group Chair,
Henzen, Christin (Technische Universität Dresden) - Group Chair,
Ivánová, Ivana (Curtin University) - Group Chair,
Maso Pau, Joan (Universitat Autònoma de Barcelona (CREAF)) - Group Chair,
Meek, Sam (Helyx secure information systems ltd) - Group Chair

Group Description:

The mission of the DQ DWG to establish a forum for describing an interoperable framework or model for OGC quality measures and services to enable access and sharing of high quality geospatial information, improve data analysis and ultimately influence policy decisions.

The WG will attempt to define a framework and a grammar for the certification and communication of spatial DQ. This method to describe and communicate data quality measures will reference, but not be limited by, a number of categories, such as spatio-temporal accuracy and resolution, completeness, consistency and integrity, semantic interoperability and lineage. One of the major roles of DQ DWG is to participate in ISO/TC211 and OGC in the development of standards for data quality and the review other related standard.


OGC Workshop: Towards FAIR Quality Measures for Spatial Data - 8 December 2021

Following our successful premier at June’21 OGC Member meeting we invite you to another edition of the public and open Data Quality Workshop.

This edition’s topic is ‘FAIR data quality measures’ and the motivation for this topic, among others, comes from the newly set-up ISO standards development project, in which many OGC members participate: ISO/AWI 19157-3 Geographic information – Data quality – Part 3: Data quality measure register’. ISO 19157-3 is a joint ISO/TC211 and OGC project and our ultimate aim is to set-up a machine-actionable register of data quality measures.

During this workshop we would like to explore various perspectives on data quality measures as we feel that what ISO/TC211 recognizes currently in ISO 19157: 2013 is too ‘geoinfo-centric’ and we need to include wider geospatial perspective with their own measures. Moreover, many standard data quality measures used for expressing the quality of geographic information (such as those defined in ISO 19157: 2013 Geographic information – Data quality) are not accessible for automatic consumptions. As a result, they are either overlooked and new measures are defined, or providers tend to create their own online measure registries and these, although claim to be ISO 19157 compliant, often introduce own interpretations.

We are convinced that a machine-actionable quality measures register will enable FAIR (Findable, Accessible, Interoperable and Reusable) quality measures. This ultimately contributes to the FAIRness of the quality information related to spatial datasets (the topic of our previous edition of OGC Data Quality Workshop - see below), and, thereby, to the overall aim of making location FAIR, which is the very mission of the OGC.

The Open Geospatial Consortium’s Data Quality Domain Working Group and the group of international domain experts invite participation in the Workshop to be held virtually on 8 December 2021 as part of the 121th OGC Member Meeting.

Participants can register via this link with 2112tc_invited 100% discount code to ensure that as OGC non-members get in for free. OGC members have free registration by default.

This 3-hour community workshop is open for members and non-members of OGC alike and the registration is free. The results will contribute to efforts towards establishing a standard compliant and trusted data quality measures register.

The workshop will be presented in three parts: starting with setting the scene and introducing the motivation towards FAIR data quality measures for spatial data. We will then continue with highlighting some examples of measures from selected domains, and conclude the workshop with exploring options to move forward.

Part I: Setting the scene – Justification for FAIR data quality measures (30 min)
We will introduce motivation and the context for this workshop: the rationale behind initiative towards FAIR data quality measures. We will also demonstrate a past, painful experience to justify this effort and outline a use-case where FAIR data quality measures are paramount.

Part II: Community perspectives – domain-specific examples of data quality measures and their use (90 min)
Lightning talks will be presented by an expert panel of data scientists, stewards, practitioners, and data producers.

Part III: Discussion &Hands-on session (60 min)
This part of the workshop will explore capabilities if OGC Definition Server to host register of standard data quality measures, and highlight potential challenges therein.

Schedule of Meeting*:

Time (in EST)

Activity

15:30 – 15:40

Introduction – Ivana Ivánová (Curtin University)

15:40 – 16:00

Setting the scene – justification for machine-actionable DQ measures Joan Masó (CREAF)

16:00 – 16:45

Lightning talks part 1 – domain-specific examples of data quality measures and their use:

·       Spatial data on the Web: Linda van den Brink (Geonovum)

·       Meterorology: Christina Lief (WMO Expert Team on Data Requirements for Climate Services, lead)

16:45 – 17:00

Break

17:00 – 17:30

Lightning talks part 2 – domain-specific examples of data quality measures and their use:

·       Remote Sensing Training Data: Peng Yue (Wuhan University)

·       Earth Observation Calibration/Validation: Jasmine Muir (FrontierSI/SmartSat CRC; AquaWatch)

17:30 – 18:00

Hands-on session Demo of OGC’s Definition Server: Rob Atkinson (OGC)

18:00 – 18:30

Discussion, Wrap-up & Next Steps

 * Please note that presentation titles are tentative - final agenda will be confirmed shortly before the meeting


 

Quality Makes Data FAIR Workshop - 15 June 2021

 

1.   Do we need FAIR data quality?

2.   What quality information is FAIR?

3.   A quest for use-cases that need decent practice for FAIR geospatial quality.

Development of the community guidelines for sharing and reusing quality Information of individual Earth Science datasets is currently under way. These guidelines aim at directing data producers, stewards, scientist and users to provide and use quality information which is findable, accessible, interoperable and reusable – FAIR. At this stage of guidelines’ development process, we wanted to hear from the geospatial community about their use cases to ensure that the guidelines are in line with the user communities and their applications (especially any non-traditional applications or those related to novel and disruptive ideas and activities). 

The Open Geospatial Consortium’s Data Quality Domain Working Group and the group of international domain experts held the Quality Makes Data FAIR Workshop virtually on 15 June 2021 as part of the 119th OGC Member Meeting.

This 3-hour community workshop was open for members and non-members of OGC alike. The results will contribute to progressing the development of the ‘International Community Guidelines for Sharing and Reusing Quality Information of Individual Earth Science Datasets’.

Background

Since Sept 2020, international interdisciplinary domain experts have been working voluntarily towards defining community guidelines for making quality information findable, accessible, interoperable and reusable (FAIR). The objective of this community effort is to develop the ‘International Community Guidelines for Sharing and Reusing Quality Information of Individual Earth Science Datasets’. To provide some context to this effort, here is a link to a 'call-to-action' paper: https://datascience.codata.org/articles/10.5334/dsj-2021-019/.

To help with the development of the guidelines, we are starting to collect several use cases. The purpose of the collection of use cases is threefold: 1. to justify the need for a best practice in describing quality information to ensure and proper use of data, 2. to collect examples from multiple application domains on the use of FAIR quality information, and 3. to provide the community with implementation examples of the guidelines. The result of this effort will inform the guidelines wherever applicable. Together with the guidelines, this collection will be open and curated by the community.

The guidelines cover all Earth Science datasets. However, input of the geospatial data community is essential to include a variety of perspectives and build on current understanding of what spatial data quality means in different domains. Such input can help identify essential data quality information and how it should be conveyed to users to avoid misunderstanding of geospatial data, information, service and products among users.

OGC Quality Makes Data FAIR Workshop

The workshophs started with setting the scene and introducing the community effort in developing community guidelines for FAIR quality information about geospatial datasets and we continued with highlighting some known use-cases for the need of such guidelines. Presentations from the Workshop are available, as listed below.

 

Title

Creator

Data Quality Workshop - context & agenda 

Ivana Ivánová 

Global Community Effort on Sharing Dataset Quality Information

Carlo Lacagnina 

Data Quality in Earth Sciences - the GeoKur approach 

Christin Henzen 

Wind energy production vulnerability: a quality driven selection 

Carlo Lacagnina 

Quality aspects in urban planning in Sweden

Torsten Svärd 

Quality Considerations for SampleML-AI/ML 

Peng Yue 

The role of provenance in FAIR data standards for Location-Based Services

Mark Abrams & Kumar Navulur & Leif Haglund 

The power of two calibration points …

Mark Abrams & Kumar Navulur 

Trust in Earth Observation Data 

Jasmine Muir 

Providing Quality Geospatial Information For Natural World 

Kerstin Lehnert and Lesley Wyborn 

Data Quality & Citizen Science 

Jessie Oliver 

Quality Pays 

Scott Simmons 

Data Quality Workshop recording 

Co-chairs: Ivana Ivánová, Joan Masó, Matt Beare, Sam Meek