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How Might We Democratize Data? Analyzing Implications of Federal Data System Design for Communities and Individuals.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	How Might We Democratize Data? Analyzing Implications of Federal Data System Design for Communities and Individuals.
作者:	Zachary, Drew A.
出版者:	Ann Arbor : ProQuest Dissertations & Theses, 2023
面頁冊數:	139 p.
附註:	Source: Dissertations Abstracts International, Volume: 84-08, Section: A.
附註:	Advisor: Meschede, Tatjana.
Contained By:	Dissertations Abstracts International84-08A.
標題:	Public policy.
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=30246599
ISBN:	9798371918789

How Might We Democratize Data? Analyzing Implications of Federal Data System Design for Communities and Individuals.
Zachary, Drew A.

How Might We Democratize Data? Analyzing Implications of Federal Data System Design for Communities and Individuals. - Ann Arbor : ProQuest Dissertations & Theses, 2023 - 139 p.

Source: Dissertations Abstracts International, Volume: 84-08, Section: A.

Thesis (Ph.D.)--Brandeis University, The Heller School for Social Policy and Management, 2023.

This item must not be sold to any third party vendors.

Data are critical to life in the 21st century to support everyday activities, business processes, decision making and more. There are increasingly many sources and users of data, but one important data provider is the United States government. Federal agencies provide thousands of open data sets for public use. Laws such as the Evidence Act, the OPEN Government Data Act and the 21st Century Integrated Digital Experience Act now require agencies to publish open data sets online for use by the public, and also mandate that government websites be as clear and easy to use as possible. Thus, it is important for government data providers to make their data not only open but easily usable. Yet there are challenges to doing so, including the relatively narrow historical user base of federal statistical data, and the complexity of understanding data use processes for a user base as broad as the general public. The Census Bureau provides a case to study these challenges, as the nation’s largest statistical agency, providing data from nearly 150 Censuses and surveys, including the Decennial Census of the population. This three-paper dissertation used qualitative methods to explore how people interact with Census Bureau data and for what purposes, how they envision solving usability challenges, and a participatory method that simultaneously captures all of this information. Paper 1 answered the question: “How do people interact with Census data and for what purposes” and applied the framework of naturalistic decision theory and recognition primed decision making. Data came from 30 interviews (n = 32) conducted with individuals who use or could use Census data for work-related needs, in which they were asked about their data needs and data use tasks. Interviews included a task observation in which they used think aloud protocol to demonstrate completion of a task within the Census Bureau’s data access portal. Three dimensions emerged that described the data utilization process: 1) the user’s background knowledge and experience with data in general and Census data in particular, 2) their immediate goal, and 3) their downstream goal. Four key user types were identified along these dimensions. Paper 2 addressed the question, “how do Census data users envision solving data usability challenges?” and was informed by past research and theoretical frameworks from participatory research and cognitive task analysis. Data came from 2 workshops (n = 46) conducted via Zoom with Census data users. In these participatory design workshops, data users were placed into small groups with facilitators from the Census Bureau in which they discussed their current data uses, and then brainstormed solutions and created virtual notes and artifacts representing their ideas. These ideas were analyzed by group, by user type, and overall to identify themes and trends, and 4 across group themes emerged in the users’ ideas for improvements: 1) Communicating with users and building awareness about the data, 2) Improving search and navigation, 3) Streamlining workflows and allowing customization, and 4) Providing more clear, complete and easily accessible data documentation. Paper 3 addressed the question, “Can one participatory workshop method be used to produce reliable data on both user needs and potential solutions to problems facing target users?” and explored what elements would enable such a method to produce robust data. This builds on the previous papers and past literature indicating that contextual information on user needs is critical for understanding possible solutions. It also draws on theoretical frameworks for the value of participation in solution development. Data came from 4 workshops conducted between 2019–2022 (n = 20–60 per workshop) including 2 in-person and 2 virtual workshops. This paper described the method in detail as well as findings about the workshop format, protocol, facilitation, and participants included that influenced success and data quality. The paper described the advantages and disadvantages of PDWs compared with interviews and focus groups. Limitations of these papers include a small sample size, and that some elements of the research topics could not be explored in detail, among other limitations described in each paper. This dissertation presents findings that are relevant for research and practice, as researchers and government agencies continue to evolve in an ever more digitally engaged world.

ISBN: 9798371918789Subjects--Topical Terms:

280699
Public policy.
Subjects--Index Terms:

Data policy

How Might We Democratize Data? Analyzing Implications of Federal Data System Design for Communities and Individuals.
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