Building Capacity for Data-Driven Governance: Creating a New Foundation for Democracy

Abstract

Existing data flows at the local level, public and administrative records, geospatial data, social media, surveys, as well as other federal, state, and local databases, are ubiquitous in our everyday life. These data, when integrated, can tell the story of a community. The Community Learning Data Driven Discovery (CLD3) process liberates, integrates and makes these data available to government leaders and researchers to tell their community's story and to use these stories to build an equitable and sustainable social transformation within and across communities to address their most pressing needs.The CLD3 process starts with asking local leaders what their questions are but cannot currently answer; identifying data sources that can provide insights; wrangling the data (profiling, cleaning, transforming, linking); using statistical and geospatial learning along with the communities' collective knowledge to inform policy decisions; and developing, deploying, and evaluating intervention strategies based on scientifically based principles. CLD3 is a continuous, sustainable and controlled feedback loop. CLD3 is described conceptually and through examples as a process that builds capacity for data driven governance at the local level.

Opportunities to observe and measure intangible inputs to innovation: Definitions, operationalization, and examples

“…We categorize data into four categories and provide examples in the context of this paper (24,25). Categorizing data by types can accelerate the data discovery phase (described below).…”

Harnessing the power of data to support community‐based research

“…The community learning process cycles through discovering data sources to answer these questions, acquiring and repurposing the data sources, conducting exploratory data analysis, generating hypotheses, creating statistical learning models, and collaborating with these civic leaders who provide insights about the findings and contribute to interpretation of the statistical analyses (Keller, Lancaster, & Shipp, ). Our goal is to foster learning and to build capacity for data‐driven governance.…”

“…Data source: Fire/ emergency medical service (EMS) data for Arlington, Virginia (2011-2013. Reprinted with permission from Keller, Lancaster et al (2017) FIGURE 6 Identification of nonemergency call locations of 911 fire and EMS callers. Loyal locations are those that calls come from three or more times in 1 month.…”

“…Data sources: Fire/emergency medical service (EMS) data for Arlington, Virginia (2011-2013. Reprinted with permission from Keller, Lancaster et al (2017) a patient or staff call 911 to take a patient for a regularly scheduled doctor's appointment or to pick up a prescription or to ask a question about the hospital's hours of operations.…”

Towards a Public Sector Data Culture: Data as an Individual and Communal Resource in Progressing Democracy

“…Digital data, as a potential recourse, is one that both citizens and governments possess. And as the public sector is entering into an era of algorithmic governance-where algorithms, automation and data-driven services constitute a cornerstone in decision making (Doneda and Almeida 2016), that balance needs a new articulation (Keller et al 2017).…”