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Stephen H. Holden

Researcher at University of Maryland, Baltimore County

Publications -  15
Citations -  710

Stephen H. Holden is an academic researcher from University of Maryland, Baltimore County. The author has contributed to research in topics: Government & Information technology. The author has an hindex of 11, co-authored 15 publications receiving 686 citations. Previous affiliations of Stephen H. Holden include Internal Revenue Service & University of Baltimore.

Papers
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Proceedings ArticleDOI

A comparison of perceived and real shoulder-surfing risks between alphanumeric and graphical passwords

TL;DR: Findings indicate that configuring data entry for Passfaces™ through a keyboard is the most effective deterrent to shoulder-surfing in a laboratory setting and the participants' perceptions were consistent with that result.

Is Your Local Government Plugged In? Highlights of the 2000 Electronic Government Survey

TL;DR: In this article, the authors describe how more and more citizens have come to expect an increasingly higher level of convenience and services from their local governments, including electronic payment of taxes, tickets and fines; online registrations; and access to a range of local government documents and records.
Proceedings ArticleDOI

Electronic government at the grass roots: contemporary evidence and future trends

TL;DR: It is found that the emergence of electronic government at the local level is still in its formative stages and local e-government offerings tended to be more basic when compared to the normative model although many local governments indicate that they have plans to develop more sophisticated offerings in the future.
Book ChapterDOI

The evolution of information technology management at the federal level: implications for public administration

TL;DR: The authors analyzes federal IT management literature from several academic disciplines and government documents and compares it with a normative model of management maturity focusing on the strategic objectives for IT and related management approaches.
Journal ArticleDOI

Semantic integration of government data for water quality management

TL;DR: This paper outlines techniques to integrate numerous water quality monitoring data sources, to resolve data disparities, and to retrieve data using semantic relationships among data sources taking advantage of customized user profiles to enhance quantity and quality of information available for water quality management.