16 June | AGILE Workshop: Uncertain Geodata: Bias, Missingness & GeoAI

Uncertain Geodata: Bias, Missingness & GeoAI Workshop

Artificial Intelligence methods are now a familiar part of the landscape of GIScience, but it remains vital that researchers deeply understand their datasets. Biases, missing data, and uncertainty are routine characteristics of geospatial data, presenting both opportunities and risks for insight. Understanding and handling these features appropriately is an essential skill for GIS researchers, whether working with GeoAI or more traditional  analytic approaches.

New at AGILE this year, the Uncertain Geodata workshop will bring together researchers to address issues of data quality in its broadest sense. We intend to set an agenda for data quality issues in GIscience, gather perspectives from experts and practitioners, and share skills to improve our collective expertise on this timely issue. The programme will feature a panel discussion with leading researchers including Professors Ana Basiri and Chris Brunsdon, as well as an opportunity to contribute perspectives to a collaborative summary and comment article to be published following the workshop (all contributors will be acknowledged).

We also invite short contributed talks (5-10 minutes) accompanied by an extended abstract or short paper (1 to 3 pages). Each accepted contribution will be published with a DOI in a collection of the workshop proceedings on Zenodo. We welcome research directly addressing issues of data quality, as well as talks that highlight an interesting or surprising data quality aspect of work with a different primary focus. If your AGILE conference paper encountered a data quirk or challenge that you couldn’t fit into your main talk – this is the venue for it.

Call for abstracts

We particularly welcome talks on topics including (but not limited to):

  • Biased Data and Adjustment/Correction methods
  • Missing Data and Imputation methods
  • Data Quality in GeoAI Training Data
  • Uncertainty and Communicating Uncertainty
  • Propagation of Data Deficiencies into Applications and Outputs
  • Reproducibility, Generalisability, and Open Science
  • Ethics of Using Flawed Data and/or Imputation
  • Further Issues in Data Quality

Submission details

Tbc

Important Dates

  • Submission deadline: 10 April 2026
  • Notification to authors: 24 April 2026
  • Workshop: 16 June 2026

Workshop Programme (Provisional)

Introduction – Dr James Ackland

Open Panel – featuring Prof. Ana Basiri, Prof. Chris Brunsdon and others

Coffee break

Contributed Short Talks – see Call for Abstracts

Collaborative Working Groups – opportunity to contribute to summary and comment article

Closing Remarks – Dr James Ackland