Discourse Modeling

Discourse Modeling
Description	Implement Discourse Graph schema in Semantic MediaWiki. Query Discourse Graph contents through SMW sparql endpoint. Visualize and publish Discourse Graph contents.
Related Topics	Discourse Graphs, SPARQL
Projects	Federated knowledge synthesis, Making Discourse Graphs Indexable & Discoverable
Discord Channel	#discourse-modeling
Facilitator	Karola Kirsanow
Members	Kyle MacLaury, Sam Klein, Konrad Hinsen, Karola Kirsanow, Peter Murray-Rust

What are we discussing?

It could be really valuable to try to prototype a "computable" synthesis of the knowledge in this workshop here in the wiki. One test of the "computability" would be to make it visualizable.

Could have applications to the semantic climate setting that Peter Murray-Rust is working on.

Now you're playing with templates

• {{ Source}} template : URL, publisher, publisher-url, date, author, title

Sj, 2022-11-12. Discourse modeling templates. Synthesis Infrastructures wiki.

• Claim :
• Axiom (?) :

Potential Actions

• Implement the Discourse Graph schema within the workshop's Semantic MediaWiki instance
  • Making Discourse Graphs Indexable & Discoverable is a sub-project relevant to this group
• Incorporate models/algorithms into Semantic MediaWiki
• Access discourse and knowledge representations in the SMW instance
• Compute with the returned data
  • potentially using models/algorithms from the wiki
• Visualize the results of the computation
• Publish the visualizations back to the SMW instance
• Assess suitability of Discourse Graphs for federation (Federated Knowledge Synthesis)

Modules

Technical aspects of the project

• Semantic MediaWiki
  • Front End
    • Embed CloudObjects from Wolfram Cloud
    • User chooses model and specifies input parameters
    • User applies model to input parameters
      • Call API that executes
  • rdf database
    • SPARQL endpoint
• Wolfram Cloud
  • Use SPARQLExecute to call the SPARQL endpoint
  • Apply Model to query results
  • Publish visualizations as CloudObjects
  • Publish API that executes model/algorithm

Workshop Goals

1. Implement the Discourse Graph schema within the workshop's Semantic MediaWiki instance
   1. create templates for nodes
   2. understand how to type relationships
   3. prototype naming conventions
2. Create a few example Discourse Graphs, drawing on content and conversations generated during the workshop
3. Make the Discourse Graphs contained on the wiki visualizable and queryable through the Semantic Mediawiki SPARQL endpoint, as described above
4. Document our process and create a guide to making wiki-supported Discourse Graphs

Progress as of Day 1

• We aligned on a workplan that largely harmonizes with the goals formulated before the workshop and integrates as many objectives from Making Discourse Graphs Indexable & Discoverable and Federated knowledge synthesis as feasible.
  • We want to bootstrap a simple entrypoint into Discourse Graph construction, complete with example graphs, from a more familiar wiki environment.
  • We hope to design a system that is compatible with later efforts at DG federation.
  • We discussed the approaches to naming and conflict resolution employed by an agora and everything2.
• We decided to focus first on the problems of naming and schemas; beginning with designing templates for nodes and a wiki-friendly implementation of relations.
  • We discussed the relative advantages and constraints of MW v SMW.
  • We aligned on the criticality of naming to enable effective querying
  • We decided that we should also develop names for frequent queries.
• We sketched a system for capturing and transforming conversations on this wiki into graphs, putting the "discourse" back into "Discourse Graphs"
  • We made a first pass at designing templates for sources, evidence, claims, and questions
  • We discussed for the page relations enabled by SMW could be used to create DG edges.

Observations & Open Problems

• We immediately realized that we had seen very few Discourse Graphs "in the wild": the model makes intuitive sense in single player and small-group mode in Roam & Obsidian, but how gracefully will it scale to massively multiplayer synthesis?
  • There are at least two possible models here: public-first writing in online mode (wiki, Roam) and local-first writing +push, probably via git. UX and conflict resolution will differ in these models.
• How to design with a federated future in mind?
  • What does it mean for distinct graphs to share nodes? to "live" in adjacent namespaces?
• The challenge of using a wiki like git: simultaneous editing seems more cumbersome
• If creating templates is a large part of the work, more powerful text editing & transformation capabilities (e.g. sed, pandoc) seem in order
• Need to create a consistent way of sharing and editing templates - how do template changes propagate in a future federated system?
• Will graph visualization scale in a useful manner? How will traversal work?
• The relationship between naming and clustering: how do we name groups of related hypotheses? A family of experiments?
  

Relevant Projects and Ideas

• Agora
• everything2
• Cosma
• Obsidian
• Roam
• Logseq
• Zettlr
• Tana
• Kumu
• The Discourse Graph Starter pack

Example Discourse

Why do we expect increased concentrations of atmospheric carbon dioxide to change the climate?

Example Discourse Graphs

• Joel Chan's working notes
• CIViC (Clinical Interpretation of Variance in Cancer]

Discord

joelchan86#discourse graphs22-11-10 15:55:39

we think the problem now is user-friendly tools and workfows that can create discourse graph structures, and have seen some exciting progress across a bunch of new user-facing "personal wikis". but bridging from personal to communal is still a challenge, partially bc of tooling.

this is why i'm excited about the Discourse Modeling idea, which i sort of understand as a way to try to instantiate something like Discourse Graphs into a wiki (bc wikis have a lot more in-built affordances for collaboration, such as edit histories, talk pages, etc.), which may hopefully lead to a lower barrier to entry for collaborative discourse graphing.

a high hope is that we can develop a process that is easy enough to understand and implement that can then be applied to discourse graphing the IPCC or similarly large body of research on a focused, contentious, interdisciplinary topic.

other examples include: - effects of masks on community transmission (can't do decisive RCTs, need to synthesize) - effects of social media on political (dys)function: (existing crowdsourced lit review here, in traditional narrative form: https://docs.google.com/document/d/1vVAtMCQnz8WVxtSNQev_e1cGmY9rnY96ecYuAj6C548/edit#)