Unconventional oil and gas extraction is fueling a wave of resource development often touted as a new era in US energy independence. However, assessing the true costs of extraction is made difficult by the vastness of the industry and lack of regulatory transparency. This paper addresses efforts to fill knowledge gaps taken up by civil society groups, where the resources produced in these efforts are used to make informed critiques of extraction processes and governance. We focus on one civil society organization, called FracTracker Alliance, which works to enhance public understanding by collecting, interpreting, and visualizing oil and gas data in broad partnerships. Drawing on the concepts of civic science, we suggest that the informational practices of civil society research organizations facilitate critical knowledge flows that we term "civic informatics." We offer three case studies illustrating how different characteristics of civic informatics enable public-minded research as well as build capacity for political mobilizations.Finally, we suggest that empirical studies of civic informatics and its facilitators offer insights for the study of "engaged" Science and Technologies Studies (STS) that seek to generate new models of science at the intersection of praxis and theory.

The quality and availability of unconventional oil and gas (O&G) data in the United States have never been compared methodically state-to-state. By conducting such an assessment, this study seeks to better understand private and publicly sourced data variability and to identify data availability gaps. We developed an exploratory data-grading tool - Data Accessibility and Usability Index (DAUI) - to guide the review of O&G data quality. Between July and October 2013, we requested, collected, and assessed 5 categories of unconventional O&G data (wells drilled, violations, production, waste, and Class II disposal wells) from 10 states with active drilling activity. We based our assessment on eight data quality parameters (accessibility, usability, point location, completeness, metadata, agency responsiveness, accuracy, and cost). Using the DAUI, two authors graded the 10 states and then averaged their scores. The average score received across all states, data categories, and parameters was 67.1 out of 100, largely insufficient for proper data transparency. By state, Pennsylvania received the highest average ( = 93.5) and ranked first in all but one data category. The lowest scoring state was Texas ( = 44) largely due to its policy of charging for certain data. This article discusses the various reasons for scores received, as well as methodological limitations of the assessment metrics. We argue that the significant variability of unconventional O&G data-and its availability to the public-is a barrier to regulatory and industry transparency. The lack of transparency also impacts public education and broader participation in industry governance. This study supports the need to develop a set of data best management practices (BMPs) for state regulatory agencies and the O&G industry, and suggests potential BMPs for this purpose.