Data Analytics for Community Decision-Making
In the age of big data, pervasive digital technology is reshaping the innovation landscape, dispersing innovation activities toward the periphery of organizations and across organizational and geographic boundaries. Smart and connected communities can turn knowledge and ideas into local value by actively developing and maintaining a diverse innovation ecosystem. Smart communities are those which can innovate and identify creative solutions to address their needs and the ongoing and evolving challenges they face. Such a conception of smart communities mandates an in-depth understanding of the processes that technological advancements implement in communities to improve civic health and economic prosperity. As data production grows (e.g., sensor data, social media data, etc.) the needs of local community actors (e.g., small business, entrepreneurs, and community advocates) for tools and methods to make sense of complex data landscape increase as well. Investigating the feasibility and planning for developing a community accessible framework for learning, accessing, and utilizing these tools and methods is an overarching focus of this proposal. In recent years, we have witnessed massive growth in computational methods and discoveries; however, we do not yet know how to successfully and effectively deploy such technologies in local community decision making and what their role should be in innovation processes in those communities. It is still unclear how local communities can directly benefit from the advances in big data and data analytic technologies, and how such technologies can create an innovation-supporting environment to stimulate economic growth in recovering communities. The present planning grant aims to embark on a team building and community engagement program to initiate a multidisciplinary, multi-community effort to address the above questions through a sociotechnical lens. By bringing scholars from areas such as entrepreneurship, economic development, and data science and by engaging with community we plan to investigate the feasibility of creating a hub for advanced data analytics and business intelligence (DA&BI) services to support recovering communities. We focus our planning and community engagement effort on the existing networks within two recovering communities in Ohio and Maryland. The goal of this planning grant is to investigate how information technology advances and knowledge resources can be shared between knowledge institutions and communities to create an innovation ecosystem for sustainable smart communities. CODE (Community Decision-Making) is a multidisciplinary collaboration led by Kent State University which will bring together research expertise from a wide range of disciplines such as data and information science, science and technology studies, organizational studies, urban and regional planning, economic development, and community planning. CODE is an attempt improves our understanding of the innovation ecosystem by exploring a model for public knowledge institutions such as libraries and universities to work in tandem with small business development centers (SBDCs), economic development organizations (EDOs), and community advocacy groups. Working together, they can enhance the community’s capabilities and transform knowledge into innovation that encourages economic and community development.
December 2017 - September 2020
Additional UMD Investigator(s):
Kent State University
Total Award Amount: