James Goulding

The Dataware manifesto

In this paper we concern ourselves with Service-Oriented Architectures (SOA) in the “business to consumer” (B2C) arena. In particular we consider the services required to enable consumers to combine data they possess with data held about them by businesses and government. We introduce the concept of Dataware as the logical federation of data sources containing “my data” and discuss an SOA to deliver new and compelling services and applications able to reap the benefits of value-in-use for consumers.

A refined limit on the predictability of human mobility

It has been recently claimed that human movement is highly predictable. While an upper bound of 93% predictability was shown, this was based upon human movement trajectories of very high spatiotemporal granularity. Recent studies reduced this spatiotemporal granularity down to the level of GPS data, and under a similar methodology results once again suggested a high predictability upper bound (i.e. 90% when movement was quantized down to a spatial resolution approximately the size of a large building). In this work we reconsider the derivation of the upper bound to movement predictability. By considering real-world topological constraints we are able to achieve a tighter upper bound, representing a more refined limit to the predictability of human movement. Our results show that this upper bound is between 11-24% less than previously claimed at a spatial resolution of approx. 100m×100m, with a greater improvement for finer spatial resolutions. This indicates that human mobility is potentially less predictable than previously thought. We provide an in-depth examination of how varying the spatial and temporal quantization affects predictability, and consider the impact of corresponding limits using a large set of real-world GPS traces. Particularly at fine-grained spatial quantizations, where a significant number of practical applications lie, these new (lower) upper limits raise serious questions about the use of location information alone for prediction, contributing more evidence that such prediction must integrate external variables.

Co-active intelligence for image retrieval

Lexical ambiguity in query-based image retrieval is an immemorial problem which has seemingly resisted all countermeasures. In this paper we introduce a methodology that expresses the users of a system and their navigational behaviour as the paramount resource for resolving query term ambiguity. Mass user consensus is modelled within a multi-dimensional feature space and evaluated through cluster analysis. This technique resolves query term ambiguity in a wholly democratic and dynamic fashion, in contrast to the brittle centralised models of contemporary word sense classification systems. The simple approach contained herein leads to several interesting emergent properties.

Mobile capture of remote points of interest using line of sight modelling

Recording points of interest using GPS whilst working in the field is an established technique in geographical fieldwork, where the users current position is used as the spatial reference to be captured; this is known as geo-tagging. We outline the development and evaluation of a smartphone application called Zapp that enables geo-tagging of any distant point on the visible landscape. The ability of users to log or retrieve information relating to what they can see, rather than where they are standing, allows them to record observations of points in the broader landscape scene, or to access descriptions of landscape features from any viewpoint. The application uses the compass orientation and tilt of the phone to provide data for a line of sight algorithm that intersects with a Digital Surface Model stored on the mobile device. We describe the development process and design decisions for Zapp present the results of a controlled study of the accuracy of the application, and report on the use of Zapp for a student field exercise. The studies indicate the feasibility of the approach, but also how the appropriate use of such techniques will be constrained by current levels of precision in mobile sensor technology. The broader implications for interactive query of the distant landscape and for remote data logging are discussed.

LLAMA: automatic hypertext generation utilizing language models

Manual hypertext construction is labour intensive and prone to error. Robust systems capable of automatic hypertext generation (AHG) could be of direct benefit to those individuals responsible for hypertext authoring. In this paper we propose a novel technique for the autonomous creation of hypertext which is dependent upon language models. This work is strongly influenced by those algorithms which process the hyperlinked structure of a corpus in an attempt to find authoritative sources. The algorithm was evaluated by experimental comparison with human hypertext authors, and we found that both approaches produced broadly similar results.

Practical applitudes: case studies of applications of the ZigZag hypermedia system

ZigZag is a paradigm of hypermedia that consists of a multidimensional system of principled interconnections. Its basic features and specifications are now well known, but despite this, very few practical applications have been described or discussed. This paper examines two projects as case studies. These projects both use the unique properties of ZigZag in order to solve real-world problems. One of these case studies is a personal information management system for mobile phones, and the other is a bioinformatics visualization system. Although superficially extremely different, these areas both make use of information that is loosely structured and deeply interconnected.

The Influence of Digital Surface Model Choice on Visibility-based Mobile Geospatial Applications

In this work we investigate the effectiveness of different types of visibility models for use within location-based services. This article outlines the methodology and results for our experiments, which were designed to understand the accuracy and effects of model choices for mobile visibility querying. Harnessing a novel mobile media consumption and authoring application called Zapp, the levels of accuracy of various digital surface representations used by a line of sight visibility algorithm are extensively examined by statistically assessing randomly sampled viewing sites across the 1 km2 study area, in relation to points of interest (POI) across the University of Nottingham campus. Testing was carried out on three different surface models derived from 0.5 m LiDAR data by visiting physical sites on each surface model with 14 random point of interest masks being viewed from between 10 and 16 different locations, totalling 190 data points. Each site was ground-truthed by determining whether a given POI could be seen by the user and could also be identified by the mobile device. Our experiments in a semi-urban area show that choice of surface model has important implications for mobile applications that utilize visibility in geospatial query operations.

Autonomous authoring tools for hypertext

Autonomous authoring tools are routinely used to expedite the translation of large document collections into functioning hypertexts. They are also used to add hyperlinks to pre-existing hypertext structures. In this survey we describe a taxonomy of autonomous hypertext authoring tools. The classification of any given system is determined by the type and nature of the document analysis it performs.

A Comparison of Acceptance Criteria for the Daily Car-Pooling Problem

Previous work on the Daily Car-Pooling problem includes an algorithm that consists of greedy assignment alternating with random perturbation. In this study, we examine the effect of varying the move acceptance policy, specifically Late-acceptance criteria with and without reheating. Late acceptance-based move acceptance criteria were chosen because there is strong empirical evidence in the literature indicating their superiority. Late-acceptance compares the objective values of the current solution with one which was obtained at a fixed number of steps prior to the current step during the search process in order to make an acceptance decision. We observe that the Late-acceptance criteria also achieve superior results in over 75 % of cases for the Daily Car-Pooling problem, the majority of these results being statistically significant.

G con : a graph-based technique for resolving ambiguity in query translation candidates

In the field of cross-language information retrieval (CLIR), the resolution of lexical ambiguity is a key challenge. Common mechanisms for the translation of query terms from one language to another typically produce a set of possible translation candidates, rather than some authoritative result. Correctly reducing a list of possible candidates down to a single translation is an enduring problem. Thus far, solutions have concentrated upon the use of the use of term co-occurrence information to guide the process of resolving translation-based ambiguity. In this paper we introduce a new disambiguation strategy which employs a graph-based analysis of generated co-occurrence data to determine the most appropriate translation for a given term.