Conference Agenda (All times are shown in Mountain Daylight Time (MDT) unless otherwise noted)

Overview and details of the sessions of this conference. Please select a date or location to show only sessions at that day or location. Please select a single session for detailed view (with abstracts and downloads if available).

 
 
Session Overview
Session
Paper Session 12: Information and Policy
Time:
Monday, 28/Oct/2024:
2:00pm - 3:30pm

Session Chair: Shengnan Yang, Western University, USA
Location: Imperial Ballroom 1, Third Floor


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Presentations
2:00pm - 2:30pm
ID: 205 / PS-12: 1
Long Papers
Confirmation 1: I/we acknowledge that all session authors/presenters have read and agreed to the ASIS&T Annual Meeting Policies
Topics: Information and Knowledge Management (data and information management; personal information management; knowledge management)
Keywords: interagency collaboration, data exchange, data consistency, system availability, consortium blockchain

Ensuring Consistency in Interagency Government Data Exchange: A Blockchain-Based Solution

Qian Geng, Ziang Chuai, Jian Jin

Beijing Normal University at Beijing, People’s Republic of China

Effective data exchange holds the potential to bridge information gaps between government agencies, creating essential prerequisites for enhanced collaboration. However, consistency issue often hinders the performance of interagency government data exchange. Inconsistent query results may be returned from different databases if data records are not timely synchronized, degrading mutual trust and collaboration efficiency among agencies. To address this issue, an interagency government data exchange approach is proposed. Specifically, consortium blockchain is leveraged as a write-ahead log, enabling different agencies to trace relevant requests failed to be executed in real-time, thereby promptly providing consistent query results. Detailed settings on protocol level are designed for the blockchain platform to facilitate data exchange regulation, including data structures, consensus algorithms and access control mechanism. Extensive simulation experiments are conducted to evaluate the performance of the proposed approach and investigate the impact of different parameters on data consistency and system availability.



2:30pm - 3:00pm
ID: 379 / PS-12: 2
Long Papers
Confirmation 1: I/we acknowledge that all session authors/presenters have read and agreed to the ASIS&T Annual Meeting Policies
Topics: Privacy; Ethics; and Regulation (information ethics; AI ethics; open access; Information security; information privacy; information policy; legislation and regulation; international information issues)
Keywords: artificial intelligence, generative AI, copyright, information policy, technology ethica

Mining, Scraping, Training, Generating: Copyright Implications of Generative AI

Alissa Centivany

Western University, Canada

Generative AI (GenAI) impacts the ways we create, engage with, and understand creative and intellectual works. These new forms of sociotechnical (inter)action pose challenges for existing legal regimes, ethical frameworks, and social relationships. This research undertakes an in-depth copyright analysis of GenAI based on U.S. law, focusing on its fair use doctrine and conceptions of transformation. This work finds that courts’ characterization of uses as primarily either “expressive” or “mediating” is an important, though often implicit, factor in their decisions. Furthermore, while “transformative use” has dominated fair use decisions for the past thirty years, findings from this research suggest that GenAI may usher in a renewed emphasis on the doctrine’s market harms element which, in application, may be dispositive with respect to GenAI outputs. This work concludes by offering recommendations aimed at clarifying that the value of copyright arises from social and relational aspects of creative practice and sociotechnical transformation. Arguments and rationales that (over)emphasize atomization and algorithmic decontextualization of the material properties of creative works are unlikely to attend to the underlying purpose of the Act: “[t]o promote the Progress of Science and the useful Arts”.



3:00pm - 3:30pm
ID: 450 / PS-12: 3
Long Papers
Confirmation 1: I/we acknowledge that all session authors/presenters have read and agreed to the ASIS&T Annual Meeting Policies
Topics: Knowledge Organization (information knowledge organization; knowledge representation; metadata; classification; thesauri; and ontology construction; indexing and abstracting; indexing languages; terminology & standards; information architecture & design)
Keywords: Vehicle Travel Speed, Open Data, Vehicle Speed Metadata, Road Safety, Public Health.

Standardizing Vehicle Travel Speed Data for Road Safety

Liliana Salas, Arlie Adkins

University of Arizona, USA

In 2022, almost 50,000 people died in road crashes in the United States, with speeding implicated in 29% of these fatalities. Despite known links between vehicle speeds and crash occurrence and severity, there are no federal guidelines for collecting vehicle travel speed (VTS) data. Cities with open VTS data are using unstandardized datasets, which complicates large-scale and cross-jurisdictional analysis. We conducted a qualitative assessment of open data repositories for the 25 largest U.S. cities, using a framework of knowledge representation, evaluated twelve metadata components, and determined the potential usability of these datasets. Our knowledge representation framework includes five data elements: speed metric, timestamp, geospatial representation, posted speed and vehicle type. Findings show that one-quarter of these cities have open VTS datasets. Of those cities, none has a VTS dataset containing all the elements defined in our framework. This suggests the need to design information policy standards for the collection and sharing of open VTS data.