Information Management

Crowdsourcing Behavior in Reporting Civic Issues: The Case of Boston's 311 Systems

Many cities in the United States use civic technologies like 311 systems as part of their public service systems for monitoring non-emergency civic issues. These systems have enhanced the city's monitoring capability by diversifying communication channels. However, the data created through these systems is often biased because of differences in people's use of technology (i.e., digital divide) and individuals' behavioral patterns in providing types of information to the systems.

A Visualization Tool and Assessment Framework for Civic Technology Use in the DMV Area: The Case of 311 Systems During the COVID-19 Outbreak

The 311 systems that city officials currently deploy can efficiently detect non-emergency civic issues such as potholes and trash. From a socio-technical perspective, residents can re-appropriate the technology for their own purpose adding new capacities and affordances not initially intended. For example, when Hurricane Irma hit Miami in 2017, residents used 311 systems to report disaster-related issues, which led city officials to adapt the system by creating a new category.

Toward Understanding Civic Data Bias in 311 Systems: An Information Deserts Perspective

While civic technologies for public issues and services such as 311 systems are widely adopted in many U.S. cities, the impact of the emerging civic technologies and their datalevel dynamics are unclear. Because the provision patterns of civic issues to technological systems are different across neighborhoods and populations, it is difficult for city officials to understand whether the provided data itself reflects civic issues. Also, the disparities in the information provided to civic technologies in different neighborhoods may exacerbate the existing inequality.

A Theoretical Analysis of Independent Business Owners’ Preferences for Informal Information Sources

Independent business owners often prefer informal information sources to formal ones such as library collections. Part of these preferences is rational because contextual and application-oriented information is usually available from informal sources, which are theoretically the best matches for this kind of information. This suggests that, in addition to outreach strategies, efforts to integrate informal sources of business-relevant information can improve public libraries' ability to support independent business owners' information needs.

Cultural Activity Diversity and Community Characteristics: An Exploratory Study

Cultural diversity has been conceptualized and studied in diverse ways. On the one hand, cultural diversity can be conceptualized based on people’s ethnic and national backgrounds. On the other hand, cultural dimensions are defined based on individuals' behaviors and traits. Sociologists further categorize the latter depending on the degree of typicality in cultural artifacts/activities and individuals’ omnivorousness over cultural tastes.

Local Information Landscapes: Theory, Measures, and Evidence

To understand issues about information accessibility within communities, research studies have examined human, social, and technical factors by taking a sociotechnical view. While this view provides a profound understanding of how people seek, use, and access information, this approach tends to overlook the impact of the larger structures of information landscapes that constantly shape peoples access to information.

KNEXT: Data Analytics to Support Innovation Communities

KNEXT is a three-year collaborative project between Kent State University (KSU-SLIS) and the University of Maryland (UMD-CIS), which partners with local public libraries, small business development centers, economic development organizations, and community advocacy groups to bring advanced data analytics and business intelligence (DA&BI) services to public libraries in order to support small businesses, entrepreneurs, and community advocates within two recovering communities in Ohio and Maryland.

Virtual Observatory of Innovation Communities and Ecosystems (VOICE): Advancing Big Data with Ecology Theory and Data Science

Today's digital revolution is fostering remarkable innovations. The landscape of innovation is rapidly changing and thus difficult to navigate or study. Understanding broader participation in innovation requires large datasets on the innovation participants and their activities. As organizational and industry boundaries become fuzzy in the digitized world, small data analysis cannot fully explain how boundaries shift and evolve. Open innovation leads to overlapping roles of designer and user, making it inadequate to examine innovation development and adoption separately.

How are Information Deserts Created? A Theory of Local Information Landscapes

To understand issues about information accessibility within communities, research studies have examined human, social, and technical factors and contexts by taking a socio-technical view. While this view provides a profound understanding of how people seek, use, and access information, this approach tends to overlook the impact of the larger structures of information landscapes that shape people’s access to information.

Open Data Impact Map

The Center for Open Data Enterprise is a non-profit organization that aims to maximize the value of open data as a public resource that anyone can use. As a means to promote the impact and value of using open data, the center designed and developed the Open Data Impact map. As a Data Science & Technology Fellow at the Center for Open Data Enterprise, I have worked on the Open Data Impact Map, which is a searchable, centralized database of open data use cases from around the world. The map shows the distribution of organizations in the world that make use of open data.

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