Evaluation

A dialogue session should enable participative peer learning through thoughtful, question-led exploration.

A genuine conversation is one where each person is prepared to be surprised. — Theodore Zeldin

The Shared Journey in the dialogue submission we are looking for:

Question: Anchors the session in a clear, meaningful, discussion-worthy prompt.
Intent: States why this conversation matters now for the data visualisation community.
Facilitation: Describes how you will guide the discussion without turning it into a talk or workshop.
Structure: Outlines a light conversational architecture that supports flow and inclusion.
Participation: Invites active peer exchange rather than passive listening.
Discovery: Aims for shared understanding and new insight, not predetermined answers.

Dialogue Evaluation Rubric

Your submission will be reviewed by our Editorial Team and a group of experienced facilitators. We aim to have a rough consensus amongst the multiple evaluators for each proposal. The evaluation rubric below is how each one of them will be looking at the proposal.

Criteria	Strong	Maybe	Weak
Question Clarity	Anchored in a sharp, meaningful, and discussion-worthy question that invites multiple perspectives.	Clear question but somewhat broad or predictable.	Topic is vague, generic, or framed as a presentation rather than a question.
Facilitation Design	Thoughtful conversational architecture with clear flow, inclusion methods, and time structure.	Basic facilitation plan described but lacks depth or clarity in flow.	No clear facilitation strategy; risks becoming a talk or unstructured conversation.
Participant Engagement	Actively designed for balanced peer exchange and equitable participation.	Some participatory elements mentioned but not fully structured.	Primarily passive or dominated by facilitator; limited peer interaction.
Depth of Exploration	Designed to move beyond opinions into nuance, tension, and shared insight.	Likely to generate discussion but may remain surface-level.	Likely to remain anecdotal or opinion-driven without deeper exploration.
Openness & Curiosity	Embraces uncertainty and collective discovery without predetermined conclusions.	Some openness but subtly oriented toward fixed outcomes.	Clearly solution-driven or framed around promoting a viewpoint.
Community Relevance	Clearly articulates why this dialogue matters now for the data visualisation community.	Some relevance stated but impact not strongly justified.	Limited clarity on why this conversation benefits the community.