We are witnesses to and participants in a great demographic, economic, and cultural transformation. The dynamics driving this change originate from our increasing interconnectedness with the rest of the world, principally through markets, technology, and migrations of people. Although markets are often portrayed as mechanical processes, in reality they are ways of organizing complex networks of human actions and interactions. Our expanding connections to global financial, product, and labor markets result in our deepening global interdependencies along many dimensions. Similarly, the advance of digital technologies allows for ever-greater capacity to generate, manage, mine, and analyze information. Expanding networks of near-instantaneous communication connect us to people and ideas globally. Finally, the greater frequency and volume of long-distance migrations of people have introduced cultural, ethnic, linguistic, and intellectual diversity that has catalyzed creative synergies and new cross cultural collaborations. However, the confluence and interplay of all these dynamics is coincident with increasing economic inequality.
Importantly, patterns of this emerging complexity and diversity vary dramatically by neighborhood and community. Statewide or even city-level averages do not capture the wide range of socioeconomic conditions or demographic characteristics. Because people experience their lives in neighborhoods, an understanding of current and changing conditions that impact individual life opportunities and outcomes requires high-quality data at ever smaller geographies. Similarly, appropriate and effective policies, practices, and investments in education, housing, public health, transportation, and other areas require a sound foundation of data at the neighborhood level. There is high demand across a broad spectrum of entities for accurate and contemporaneous community-level data to guide decision making and investment strategies as well as to evaluate the impacts of investments and policies after implementation.
Simultaneously, the era of “big data” has dawned, with an explosion in the volume of digital data that is generated. Fortunately, our analytical tools and computational capacity have also advanced significantly. Enormous datasets are often available, but most people and organizations lack the technical resources to collect and analyze these ever-expanding masses of data. Datasets are generally difficult to integrate across topics, organizations, and disciplines. Further, some key datasets that had previously been supplied by the public sector are no longer being produced. Given the high demand for timely, frequent, and accurate small-area demographic, housing, and socioeconomic data, many communities have responded by creating online community-indicator information systems which are often housed at universities. Although there are dozens of examples across the nation, Utah currently has no such system. The Utah Community Data Project has just been launched at the University of Utah and will, when built out, provide a suite of data, profiles, community indicators, and neighborhood-focused research projects to fill this void. BEBR
