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 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

The Complicated Provenance of American Community Survey Data: How Far Will PROV and DDI Take Us? Tools

In a series of three papers in 2013, researchers at the Cornell Node of the NSF Census Research Network (http://ncrn.cornell.edu) investigated and proposed solutions for two fundamental yet distinct issues in the curation of quantitative social science data: confidentiality and provenance. We argued that the W3C PROV model, a foundation for semantically-rich, interoperable, and web-compatible provenance metatdata, is especially important in a web environment in which data from distributed sources and of varying integrity can be combined and derived. In this paper we combine and expand upon these two separate threads—confidentiality and provenance—and experiment with the use of PROV and DDI in documenting the complex provenance chain between the highly confidential environment of the U.S. Census Bureau and restricted and public versions of internal census demographic files. In particular, our presentation will report on our effort to: 1) test PROV’s ability to describe meaningful relationships between confidential, restricted and public data at the variable level; 2) develop a user interface for researchers attempting to understand the relationships between distinct versions of confidential, restricted, and public census files. Longer term our work should produce a useful metadata resource for users of public and restricted American Community Survey data

KinImmerse: Macromolecular VR for NMR ensembles

<p>Abstract</p> <p>Background</p> <p>In molecular applications, virtual reality (VR) and immersive virtual environments have generally been used and valued for the visual and interactive experience – to enhance intuition and communicate excitement – rather than as part of the actual research process. In contrast, this work develops a software infrastructure for research use and illustrates such use on a specific case.</p> <p>Methods</p> <p>The Syzygy open-source toolkit for VR software was used to write the KinImmerse program, which translates the molecular capabilities of the kinemage graphics format into software for display and manipulation in the DiVE (Duke immersive Virtual Environment) or other VR system. KinImmerse is supported by the flexible display construction and editing features in the KiNG kinemage viewer and it implements new forms of user interaction in the DiVE.</p> <p>Results</p> <p>In addition to molecular visualizations and navigation, KinImmerse provides a set of research tools for manipulation, identification, co-centering of multiple models, free-form 3D annotation, and output of results. The molecular research test case analyzes the local neighborhood around an individual atom within an ensemble of nuclear magnetic resonance (NMR) models, enabling immersive visual comparison of the local conformation with the local NMR experimental data, including target curves for residual dipolar couplings (RDCs).</p> <p>Conclusion</p> <p>The promise of KinImmerse for production-level molecular research in the DiVE is shown by the locally co-centered RDC visualization developed there, which gave new insights now being pursued in wider data analysis.</p

Detecting Mediterranean White Sharks with Environmental DNA

The white shark (Carcharodon carcharias) is a globally distributed, ecologically important top predator whose biology and population dynamics are challenging to study. Basic biological parameters remain virtually unknown in the Mediterranean Sea due to its historically low population density, dwindling population size, and lack of substantial sightings. White sharks are considered Critically Endangered in the Mediterranean Sea, and recent analyses suggest that the population has declined by 52% to 96% from historical levels in different Mediterranean sectors (Moro et al., 2020). Thus, white shark sightings dating back to 1860 are being used to estimate population trajectories throughout the entire region. Though the population size is unknown, remaining individuals are thought to be primarily restricted to a handful of hotspots deemed important for their reproduction and foraging. One of these hypothesized hotspots is the Sicilian Channel, which accounts for 19% of total historical sightings

MolProbity: all-atom contacts and structure validation for proteins and nucleic acids

MolProbity is a general-purpose web server offering quality validation for 3D structures of proteins, nucleic acids and complexes. It provides detailed all-atom contact analysis of any steric problems within the molecules as well as updated dihedral-angle diagnostics, and it can calculate and display the H-bond and van der Waals contacts in the interfaces between components. An integral step in the process is the addition and full optimization of all hydrogen atoms, both polar and nonpolar. New analysis functions have been added for RNA, for interfaces, and for NMR ensembles. Additionally, both the web site and major component programs have been rewritten to improve speed, convenience, clarity and integration with other resources. MolProbity results are reported in multiple forms: as overall numeric scores, as lists or charts of local problems, as downloadable PDB and graphics files, and most notably as informative, manipulable 3D kinemage graphics shown online in the KiNG viewer. This service is available free to all users at http://molprobity.biochem.duke.edu

Entrance Channel X-HF (X=Cl, Br, and I) Complexes studied by High-Resolution Infrared Laser Spectroscopy in Helium Nanodroplets

Rotationally resolved infrared spectra are reported for halogen atom - HF free radical complexes formed in helium nanodroplets. An effusive pyrolysis source is used to dope helium droplets with Cl, Br and I atoms, formed by thermal dissociation of Cl$_2$, Br$_2$ and I$_2$. A single hydrogen fluoride molecule is then added to the droplets, resulting in the formation of the X-HF complexes of interest. Analysis of the resulting spectra confirms that the observed species have $^2\Pi_{3/2}$ ground electronic states, consistent with the linear hydrogen bound structures predicted from theory. Stark spectra are also reported for these species, from which the permanent electric dipole moments are determined.Comment: 41 pages, 16 figures, 5 table