Human-Centered Approaches in Geovisualization Design: Investigating Multiple Methods Through a Long-Term Case Study

Working with three domain specialists we investigate human-centered approaches to geovisualization following an ISO13407 taxonomy covering context of use, requirements and early stages of design. Our case study, undertaken over three years, draws attention to repeating trends: that generic approaches fail to elicit adequate requirements for geovis application design; that the use of real data is key to understanding needs and possibilities; that trust and knowledge must be built and developed with collaborators. These processes take time but modified human-centred approaches can be effective. A scenario developed through contextual inquiry but supplemented with domain data and graphics is useful to geovis designers. Wireframe, paper and digital prototypes enable successful communication between specialist and geovis domains when incorporating real and interesting data, prompting exploratory behaviour and eliciting previously unconsidered requirements. Paper prototypes are particularly successful at eliciting suggestions, especially for novel visualization. Enabling specialists to explore their data freely with a digital prototype is as effective as using a structured task protocol and is easier to administer. Autoethnography has potential for framing the design process. We conclude that a common understanding of context of use, domain data and visualization possibilities are essential to successful geovis design and develop as this progresses. HC approaches can make a significant contribution here. However, modified approaches, applied with flexibility, are most promising. We advise early, collaborative engagement with data – through simple, transient visual artefacts supported by data sketches and existing designs – before moving to successively more sophisticated data wireframes and data prototypes

Information, information processing and gravity

I discuss fundamental limits placed on information and information processing by gravity. Such limits arise because both information and its processing require energy, while gravitational collapse (formation of a horizon or black hole) restricts the amount of energy allowed in a finite region. Specifically, I use a criterion for gravitational collapse called the hoop conjecture. Once the hoop conjecture is assumed a number of results can be obtained directly: the existence of a fundamental uncertainty in spatial distance of order the Planck length, bounds on information (entropy) in a finite region, and a bound on the rate of information processing in a finite region. In the final section I discuss some cosmological issues related to the total amount of information in the universe, and note that almost all detailed aspects of the late universe are determined by the randomness of quantum outcomes. This paper is based on a talk presented at a 2007 Bellairs Research Institute (McGill University) workshop on black holes and quantum information.Comment: 7 pages, 5 figures, revte

X-ray Studies of Two Neutron Stars in 47 Tucanae: Toward Constraints on the Equation of State

We report spectral and variability analysis of two quiescent low mass X-ray binaries (X5 and X7, previously detected with the ROSAT HRI) in a Chandra ACIS-I observation of the globular cluster 47 Tuc. X5 demonstrates sharp eclipses with an 8.666+-0.01 hr period, as well as dips showing an increased N_H column. The thermal spectra of X5 and X7 are well-modeled by unmagnetized hydrogen atmospheres of hot neutron stars. No hard power law component is required. A possible edge or absorption feature is identified near 0.64 keV, perhaps an OV edge from a hot wind. Spectral fits imply that X7 is significantly more massive than the canonical 1.4 \Msun neutron star mass, with M>1.8 \Msun for a radius range of 9-14 km, while X5's spectrum is consistent with a neutron star of mass 1.4 \Msun for the same radius range. Alternatively, if much of the X-ray luminosity is due to continuing accretion onto the neutron star surface, the feature may be the 0.87 keV rest-frame absorption complex (O VIII & other metal lines) intrinsic to the neutron star atmosphere, and a mass of 1.4 \Msun for X7 may be allowed.Comment: 16 pages, 7 figures, accepted by Ap

A Block Minorization--Maximization Algorithm for Heteroscedastic Regression

The computation of the maximum likelihood (ML) estimator for heteroscedastic regression models is considered. The traditional Newton algorithms for the problem require matrix multiplications and inversions, which are bottlenecks in modern Big Data contexts. A new Big Data-appropriate minorization--maximization (MM) algorithm is considered for the computation of the ML estimator. The MM algorithm is proved to generate monotonically increasing sequences of likelihood values and to be convergent to a stationary point of the log-likelihood function. A distributed and parallel implementation of the MM algorithm is presented and the MM algorithm is shown to have differing time complexity to the Newton algorithm. Simulation studies demonstrate that the MM algorithm improves upon the computation time of the Newton algorithm in some practical scenarios where the number of observations is large