School of Information

Location-awareness, in the form of location information about clients and location-based services provided by servers, is becoming increasingly important for networked communications in general, and wireless and mobile devices in particular. The current fragmented landscape of location concepts and location-awareness, however, is not suitable for handling location information on a Web scale. Providing users with mechanisms which allow them to control how they want to expose their location information, and thus allow control over how to share location information with others and services, is a crucial step for better location management for mobile devices. This paper presents a concept for representing location vocabularies, matching and mapping them, how these vocabularies can be used to support better privacy for users of location-based services, and better location sharing between users and services. The concept is based on a language for describing place name vocabularies, which we call "Place Markup Language (PlaceML)", and on various ways how these vocabularies can be used in a location-aware infrastructure of networked devices.

Tourism exists in the interplay between places and stories. In making sense of travel, we are also making sense of ourselves and the world around us. Indeed, the global tourist industry produces places as “destinations” through stories and souvenirs. The audience for tourism stories has changed greatly with changes in technologies of communication and representation, with one of the most radical changes the introduction of networked media. With the rise of web-based services, tourist experiences have acquired a digital penumbra of content available in ever more formats and locations. This paper examines these technological changes, and the potential consequences for digital storytelling, travel, and the production of destinations.

In this paper, I outline the legislative framework governing information privacy practices in the public and private sectors in the United States and, more narrowly, the state of California, with particular attention paid to criminal justice system information. I will explore the relationship between the courts, which maintain public criminal records, and Corporate Data Brokers (CDBs), which aggregate and sell information from court records, as well as the accuracy and privacy of their systems. While legislation guiding the government's handling of information may need to be extended to the private sector, state governments have a role to play in improving their technology infrastructure to ensure that accurate, timely information is available in the public records. This is particularly important for the criminal justice system, the source of data brokers collecting. In making this argument, I look at one state, Colorado, that did a great deal early on to improve their criminal records technology infrastructure.

This paper presents a search for direct top squark pair production in events with missing transverse momentum plus either a pair of jets consistent with Standard Model Higgs boson decay into b-quarks or a same-flavour opposite-sign dilepton pair with an invariant mass consistent with a Z boson. The analysis is performed using the proton–proton collision data at s=13 TeV collected with the ATLAS detector during the LHC Run-2, corresponding to an integrated luminosity of 139 fb- 1. No excess is observed in the data above the Standard Model predictions. The results are interpreted in simplified models featuring direct production of pairs of either the lighter top squark (t~ 1) or the heavier top squark (t~ 2), excluding at 95% confidence level t~ 1 and t~ 2 masses up to about 1220 and 875 GeV, respectively.

Oral History Interview of Michael K. Buckland education and career by Robert V. Williams, April 7-8, 2011,

As scientific endeavors and data analysis become increasingly collaborative, there is a need for data management systems that natively support the versioning or branching of datasets to enable concurrent analysis, cleaning, integration, manipulation, or curation of data across teams of individuals. Common practice for sharing and collaborating on datasets involves creating or storing multiple copies of the dataset, one for each stage of analysis, with no provenance information tracking the relationships between these datasets. This results not only in wasted storage, but also makes it challenging to track and integrate modifications made by different users to the same dataset. In this paper, we introduce the Relational Dataset Branching System, Decibel, a new relational storage system with built-in version control designed to address these shortcomings. We present our initial design for Decibel and provide a thorough evaluation of three versioned storage engine designs that focus on efficient query processing with minimal storage overhead. We also develop an exhaustive benchmark to enable the rigorous testing of these and future versioned storage engine designs.