https://www.dagstuhl.de/22432

23. – 28. Oktober 2022, Dagstuhl-Seminar 22432

Towards a Unified Model of Scholarly Argumentation

Organisatoren

Khalid Al-Khatib (University of Groningen, NL)
Anita de Waard (Elsevier – Jericho, US)
Iryna Gurevych (TU Darmstadt, DE)
Yufang Hou (IBM Research – Dublin, IE)

Auskunft zu diesem Dagstuhl-Seminar erteilen

Jutka Gasiorowski zu administrativen Fragen

Marsha Kleinbauer zu wissenschaftlichen Fragen

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Motivation

Argumentation is prevalent in scientific discourse and critical to scientific progress. Recent efforts have attempted to identify and model argumentative structures in the scientific literature, but from a diversity of perspectives:

  • The scientific literature is a canonical domain in work on computational accounts of argumentation which attempt to model relations between spans and clauses encoding rhetorical structures (e.g., premises and conclusions) or community debate (e.g., supports or attacks).
  • Another thread of research, sometimes applied to bioinformatics, focuses on scientific claims and their relation to reported evidence. Much of this work adopts a corpus perspective, aligning claims across documents, using citations to construct claim-evidence networks that summarize the state of knowledge in a field.
  • Mainly within the health sciences, argumentative structures are being exploited to automate the production of systematic reviews, by identifying key actionable knowledge elements from collections of clinical reviews, case studies, and the scientific literature.

Despite this abundance of interest and the clear practical importance of the work, we lack consensus on how scientific argumentation should be formalized. It remains unclear whether formalisms popular in non-scientific domains can be adapted for scientific discourse – or even whether a single formalism can adequately support argumentation research in literatures as diverse as biology, chemistry, materials science, and medical science. This manifests in a dearth of shared reference corpora needed to advance research into computational treatments of scientific argumentation, and no consensus on a model for defining argumentative components in scholarly text.

The purpose of this Dagstuhl Seminar is threefold:

  1. Lay the groundwork for a nascent, multidisciplinary community devoted to building and maintaining principles, tools, and models to identify key components in scholarly argumentation;
  2. Develop a foundational model for argumentation in science and healthcare, in order to
  3. Enable robust advances in argument technology for scholarly and medical discourse.

Prior to the seminar, participants will be invited to contribute to the seminar preparation, e.g., by submitting reference material, submitting any corpora and formal descriptions suitable for use in an annotation exercise, or by attending tutorial sessions.

The seminar itself is scheduled to take place over five days, and has the following objectives:

  • Knowledge baselining. We will foster a shared understanding of the problem space through a series of keynotes and panel discussions on theory, models, tools, and available corpora.
  • Model discussion. Participants will discuss the models introduced during baselining, examining their adequacy, generality, and possibilities for unification under a generalized model.
  • Pilot annotation. Breakout groups will apply these models to sample texts, investigating ease of annotation, completeness, and approaches to assessing reliability.
  • Application discussion. Building on insights acquired during the seminar, we will discuss the amenability of available models to automated argument mining in various scientific domains and the appropriate success metrics.
  • Synthesis. We will draft main conclusions and recommendations to the broader community, identify lingering open questions, and discuss future workshops and shared tasks.

Motivation text license
  Creative Commons BY 4.0
  Anita de Waard, Iryna Gurevych, Yufang Hou, and Khalid Al-Khatib

Classification

  • Artificial Intelligence
  • Computation And Language
  • Machine Learning

Keywords

  • Argument mining
  • Argument modeling
  • Scholarly discourse

Dokumentation

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Publikationen

Es besteht weiterhin die Möglichkeit, eine umfassende Kollektion begutachteter Arbeiten in der Reihe Dagstuhl Follow-Ups zu publizieren.