Advances in Spatial Machine Learning: Workshop Framework
This is an internal framework for the organisers of the Advances in Spatial Machine Learning workshop series. It sets out the character and principles that should be preserved across editions. Edition-specific details may vary, but organisers should use this document as a shared point of reference when planning the programme and inviting participants.
Purpose
The workshop brings together a deliberately limited group of researchers working on spatial machine learning, particularly in environmental and geographical applications. It is a place to discuss open questions, unresolved methodological problems, and work in progress – not primarily to present completed results.
The workshop should help participants to:
- identify challenges and priorities in spatial machine learning
- compare perspectives across methods, applications, and research groups
- discuss good practice in validation, documentation, and reproducibility
- develop ideas for collaboration, future research, and funding
Format
A typical edition lasts two days and brings together roughly fifteen invited participants. To provide some continuity across editions, the workshop should preferably be scheduled between February and early April. The group should remain small enough for everyone to take part in the full programme and for informal conversations to continue between sessions. The number of participants and the balance of topics may vary, but the deliberately limited scale is central to the workshop’s character.
Sessions should combine brief contributions, such as presentations, demonstrations, or other starting points, with substantial time for discussion and brainstorming. Each session should have a clear topic or motivating question and someone to help guide the conversation, while leaving enough flexibility for useful ideas to develop.
The workshop should be informal, low-key, and intellectually open. It should be prepared well enough to support productive discussion, but not so tightly programmed that questions and connections emerging during the event have no room.
The organisers should agree with participants what may be shared outside the workshop. In particular, it should be clear whether discussions are private, whether notes are taken, and whether materials or a summary may be circulated afterwards. Any public output should be agreed separately with the people involved.
Principles for participation
The workshop is invitation-only. Participants should be selected for their connection to spatial machine learning or a related field and for the perspectives they can contribute. The group should include a useful mix of methods, applications, institutions, and career stages.
Participants are expected to:
- contribute actively and listen carefully
- engage with questions beyond their own research
- be willing to discuss preliminary ideas, uncertainty, failed approaches, and disagreement
The organisers should aim for an atmosphere in which participants can do this without the pressure to present polished results.
Practical principles
The workshop should have no registration fee, if possible. Participants are normally expected to cover their own travel and accommodation, with limited support where resources for a particular edition allow.
The venue should provide one comfortable room for the whole group, suitable facilities for discussion and basic presentations, practical arrangements for breaks and meals, and reasonable accessibility. Organisers should communicate the edition-specific arrangements clearly to invited participants.
Outcomes
The workshop has no required formal deliverable. It may lead to a better-defined set of challenges and research priorities, shared ideas about validation and reproducibility, new or strengthened collaborations, and ideas for future research, publications, software, or funding.