Towards an approach for analysing external representations created during sensemaking using generative grammar

During sensemaking, users often create external representations to help them make sense of what they know, and what they need to know. In doing so, they necessarily adopt or construct some form of representational language using the tools at hand. By describing such languages implicit in representations we believe that we are better able to describe and differentiate what users do and better able to describe and differentiate interfaces that might support them. Drawing on approaches to the analysis of language, and in particular, Mann and Thompson’s Rhetorical Structure Theory, we analyse the representations that users create to expose their underlying ‘visual grammar’. We do this in the context of a user study involving evidential reasoning. Participants were asked to address an adapted version of IEEE VAST 2011 mini challenge 3 (interpret a potential terrorist plot implicit in a set of news reports). We show how our approach enables the unpacking of the heterogeneous and embedded nature of user-generated representations and allows us to show how visual grammars evolve and become more complex over time in response to evolving sensemaking needs

Should causal models always be Markovian? The case of multi-causal forks in medicine

The development of causal modelling since the 1950s has been accompanied by a number of controversies, the most striking of which concerns the Markov condition. Reichenbach's conjunctive forks did satisfy the Markov condition, while Salmon's interactive forks did not. Subsequently some experts in the field have argued that adequate causal models should always satisfy the Markov condition, while others have claimed that non-Markovian causal models are needed in some cases. This paper argues for the second position by considering the multi-causal forks, which are widespread in contemporary medicine (Section 2). A non-Markovian causal model for such forks is introduced and shown to be mathematically tractable (Sections 6, 7, and 8). The paper also gives a general discussion of the controversy about the Markov condition (Section 1), and of the related controversy about probabilistic causality (Sections 3, 4, and 5

Pre-emption cases may support, not undermine, the counterfactual theory of causation

Pre-emption cases have been taken by almost everyone to imply the unviability of the simple counterfactual theory of causation. Yet there is ample motivation from scientific practice to endorse a simple version of the theory if we can. There is a way in which a simple counterfactual theory, at least if understood contrastively, can be supported even while acknowledging that intuition goes firmly against it in pre-emption cases – or rather, only in some of those cases. For I present several new pre-emption cases in which causal intuition does not go against the counterfactual theory, a fact that has been verified experimentally. I suggest an account of framing effects that can square the circle. Crucially, this account offers hope of theoretical salvation – but only to the counterfactual theory of causation, not to others. Again, there is (admittedly only preliminary) experimental support for this account

Computer supported argument maps as a policy memory

This paper investigates to what extent Computer Supported Argument Visualisation can be designed to encourage debate and deliberation by citizens on public issues. Such argument maps use icons and arrows to represent the structure of a series of related viewpoints, reducing the amount of text necessary to convey the ideas, thereby clarifying the issue under consideration. Argument maps have the potential to provide a readily accessible medium by which citizens can follow and join in public debates on policy issues. In this paper we describe our approach, type of maps we have chosen to use and then demonstrate the potential of a collection of maps to form a ‘policy memory’ to support policy development. Our case study is the development of the ‘Smoking in Public Places’ policy in the Scottish Parliament. Our overall aim is to engage citizens in democratic decision-making leading to better policy-making and a more engaged citizenry

The intelligence game: Assessing Delphi groups and structured question formats

In 2010, the US Intelligence Advanced Research Projects Activity (IARPA) announced a 4-year forecasting "tournament". Five collaborative research teams are attempting to outperform a baseline opinion pool in predicting hundreds of geopolitical, econ