Micro-entries: Encouraging Deeper Evaluation of Mental Models Over Time for Interactive Data Systems

Many interactive data systems combine visual representations of data with embedded algorithmic support for automation and data exploration. To effectively support transparent and explainable data systems, it is important for researchers and designers to know how users understand the system. We discuss the evaluation of users' mental models of system logic. Mental models are challenging to capture and analyze. While common evaluation methods aim to approximate the user's final mental model after a period of system usage, user understanding continuously evolves as users interact with a system over time. In this paper, we review many common mental model measurement techniques, discuss tradeoffs, and recommend methods for deeper, more meaningful evaluation of mental models when using interactive data analysis and visualization systems. We present guidelines for evaluating mental models over time that reveal the evolution of specific model updates and how they may map to the particular use of interface features and data queries. By asking users to describe what they know and how they know it, researchers can collect structured, time-ordered insight into a user's conceptualization process while also helping guide users to their own discoveries.Comment: 10 pages, submitted to BELIV 2020 Worksho

The prevalence of star formation as a function of Galactocentric radius

We present large-scale trends in the distribution of star-forming objects revealed by the Hi-GAL survey. As a simple metric probing the prevalence of star formation in Hi-GAL sources, we define the fraction of the total number of Hi-GAL sources with a 70 μm counterpart as the ‘star-forming fraction’ or SFF. The mean SFF in the inner galactic disc (3.1 kpc < RGC < 8.6 kpc) is 25 per cent. Despite an apparent pile-up of source numbers at radii associated with spiral arms, the SFF shows no significant deviations at these radii, indicating that the arms do not affect the star-forming productivity of dense clumps either via physical triggering processes or through the statistical effects of larger source samples associated with the arms. Within this range of Galactocentric radii, we find that the SFF declines with RGC at a rate of −0.026 ±0.002 per kiloparsec, despite the dense gas mass fraction having been observed to be constant in the inner Galaxy. This suggests that the SFF may be weakly dependent on one or more large-scale physical properties of the Galaxy, such as metallicity, radiation field, pressure or shear, such that the dense sub-structures of molecular clouds acquire some internal properties inherited from their environment

Molecular Line Observations of Infrared Dark Clouds: Seeking the Precursors to Intermediate and Massive Star Formation

We have identified 41 infrared dark clouds from the 8 micron maps of the Midcourse Space Experiment (MSX), selected to be found within one square degree areas centered on known ultracompact HII regions. We have mapped these infrared dark clouds in N2H+(1-0), CS(2-1) and C18O(1-0) emission using the Five College Radio Astronomy Observatory. The maps of the different species often show striking differences in morphologies, indicating differences in evolutionary state and/or the presence of undetected, deeply embedded protostars. We derive an average mass for these clouds using N2H+ column densities of ~2500 solar masses, a value comparable to that found in previous studies of high mass star forming cores using other mass tracers. The linewidths of these clouds are typically ~2.0 - 2.9 km/s. Based on the fact that they are dark at 8 micron, compact, massive, and have large velocity dispersions, we suggest that these clouds may be the precursor sites of intermediate and high mass star formation.Comment: Accepted to ApJS, 22 pages, 10 pages of figures. For full-resolution images, see http://www.astro.lsa.umich.edu/~seragan/pubs/fcrao/figures.tar.g

The Influence of Visual Provenance Representations on Strategies in a Collaborative Hand-off Data Analysis Scenario

Conducting data analysis tasks rarely occur in isolation. Especially in intelligence analysis scenarios where different experts contribute knowledge to a shared understanding, members must communicate how insights develop to establish common ground among collaborators. The use of provenance to communicate analytic sensemaking carries promise by describing the interactions and summarizing the steps taken to reach insights. Yet, no universal guidelines exist for communicating provenance in different settings. Our work focuses on the presentation of provenance information and the resulting conclusions reached and strategies used by new analysts. In an open-ended, 30-minute, textual exploration scenario, we qualitatively compare how adding different types of provenance information (specifically data coverage and interaction history) affects analysts' confidence in conclusions developed, propensity to repeat work, filtering of data, identification of relevant information, and typical investigation strategies. We see that data coverage (i.e., what was interacted with) provides provenance information without limiting individual investigation freedom. On the other hand, while interaction history (i.e., when something was interacted with) does not significantly encourage more mimicry, it does take more time to comfortably understand, as represented by less confident conclusions and less relevant information-gathering behaviors. Our results contribute empirical data towards understanding how provenance summarizations can influence analysis behaviors.Comment: to be published in IEEE Vis 202