Issue No. 12 - December (2005 vol. 38)
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/MC.2005.399
Digital Government Research in Academia, pp. 33-39
Lois Delcambre and Genevieve Giuliano
Housed in the Computer and Information Science and Engineering Directorate, the National Science Foundation's interdisciplinary Digital Government research program is intended to fund "… research at the intersection of the computer and information science research communities and the mid- to long-term needs of the Federal information service communities."
As active participants in NSF DG research projects and cochairs of the recent 2005 National Digital Government Conference, the authors suggest that DG research, a growing activity, involves many researchers beyond those associated with the NSF DG program. They advocate reaching out to this larger community of scholars to form a critical mass that will support a society, annual conference, and academic journal.
Data Alignment and Integration, pp. 43-50
Patrick Pantel, Andrew Philpot, and Eduard Hovy
To handle the wide range of geographic scales and complex tasks it must administer, the US government splits its data in many different ways, collecting it at different times and through different agencies. The resulting massive data heterogeneity makes it impossible to effectively locate, share, or compare data across sources.
Many settings urgently need some form of data alignment or merging. Addressing these issues requires finding similarities between entities within or across heterogeneous data sources. To date, most approaches for integrating data collections, or even for creating mappings across comparable data sets, require manual effort.
Applying a purely data-driven paradigm, the authors built two systems: Guspin for automatically identifying equivalence classes or aliases, and Sift for automatically aligning data across databases. The key to their underlying technology involves identifying the most informative observations, then matching entities that share them.
Accessing Government Statistical Information, pp. 52-61
Gary Marchionini, Stephanie W. Haas, Junliang Zhang, and Jonathan Elsas
As government agencies provide increasing amounts of information through their Web sites, more people attempt to make sense of it. The resulting queries reveal a major stumbling block to widespread digital access: how best to provide highly codified, statistical data to a diverse population.
The University of North Carolina's GovStat project coordinates with federal statistical agencies to make it easier for users at all levels—both agency staff and the general population—to locate and understand government statistical data.
The project takes a twofold approach. First, define a statistical knowledge network that can evolve as the general population and government agencies share and integrate statistical information. Second, create user interface prototypes that make finding and understanding that information easy for various populations.
Building Community Information Systems: The Connected Kids Case, pp. 62-69
Teresa M. Harrison, James P. Zappen, and Sibel Adali
Users find collaborative information systems attractive because they make it possible to find information from diverse sources easily and efficiently. Such systems also make good sense for information providers because they can attract and serve a larger audience than a solitary effort might otherwise command, making it possible to pool resources to achieve certain economies in scale and technology expense.
The advantages of collaborative information systems are particularly relevant to those who design applications for government organizations or other organizations that work with government. The difficulty with developing collaborative information systems can be seen in examples that use new technologies to make information more available, accessible, and oriented toward community development.
To date, the authors' efforts have focused on developing Connected Kids, a community information system project in Troy, New York, that began in a formal sense in 1999 and continues today.
Analyzing Government Regulations Using Structural and Domain Information, pp. 70-76
Gloria T. Lau, Kincho H. Law, and Gio Wiederhold
Apart from the difficulties in locating and understanding a particular regulation, users often must consult and reconcile multiple authoritative sources. For example, US companies frequently must comply with overlapping federal, state, and local regulations; in addition, some nonprofit organizations publish their own codes of practice. The problem is exacerbated in the European Union, where regulators must harmonize legislation across countries with different languages and traditions. For enterprises involved in global commerce, regulatory compliance presents a major challenge.
Individuals and small companies with limited resources need a framework they can use to retrieve related regulations from multiple governing copies and then perform comparative analysis. Stanford University's Regnet project seeks to develop such a framework, with a current focus on US national and regional codes in the domains of disabled access and environmental standards.