05041nam a22006617i 4500 on1353293269 EBZ 20251029164104.0 m d cr cnu---unuuu 221206s2022 flu ob 001 0 eng d EBZ eng EBZ 9781003292951 (electronic bk.) 100329295X (electronic bk.) 1000781321 (electronic bk. : EPUB) 9781000781304 (electronic bk. : PDF) 1000781305 (electronic bk. : PDF) 9781000781328 (electronic bk.) 9781032274683 1032274689 9781032264592 1032264594 10.1201/9781003292951 doi 9781003292951 Taylor & Francis HT166 BUS 061000 bisacsh COM 021030 bisacsh MAT 029000 bisacsh PBT bicssc MAIN O'Brien, Daniel T., 1983- author. https://isni.org/isni/0000000499334317 64647 Urban informatics : using big data to understand and serve communities / Daniel T. O'Brien. Boca Raton : Chapman & Hall/CRC, 2022. 1 online resource (1 volume) text txt rdacontent computer c rdamedia online resource cr rdacarrier textual sapdv EBSCOhost Chapman & Hall/CRC data science series Includes bibliographical references and index. Urban Informatics: Using Big Data to Understand and Serve Communities introduces the reader to the tools of data management, analysis, and manipulation using R statistical software. Designed for undergraduate and above level courses, this book is an ideal onramp for the study of urban informatics and how to translate novel data sets into new insights and practical tools. The book follows a unique pedagogical approach developed by the author to enable students to build skills by pursuing projects that inspire and motivate them.Each chapter has an Exploratory Data Assignment that prompts readers to practice their new skills on a data set of their choice. These assignments guide readers through the process of becoming familiar with the contents of a novel data set and communicating meaningful insights from the data to others. Key Features: The technical curriculum consists of both data management and analytics, including both as needed to become acquainted with and reveal the content of a new data set. Content that is contextualized in real-world applications relevant to community concerns. Unit-level assignments that educators might use as midterms or otherwise. These include Community Experience assignments that prompt students to evaluate the assumptions they have made about their data against real world information. All data sets are publicly available through the Boston Data Portal. EBSCOhost "EBSCO evaluates our products based on the Web Content Accessibility Guidelines (WCAG) and the related Section 508 and EN 301 549 regulations in the US and EU. Most EBSCO products are substantially conformant with WCAG 2.2 level AA." Source: https://connect.ebsco.com/s/article/EBSCO-VPATs?language=en_US. Last accessed April 22, 2025. Daniel T. O'Brien is Associate Professor in the School of Public Policy and Urban Affairs and the School of Criminology and Criminal Justice at Northeastern University. He focuses on the use of modern digital data sets to better understand urban processes, including crime, education, transportation, public health, and neighborhood social dynamics. He is Director of the Boston Area Research Initiative, in which capacity he has worked extensively to build effective models of research-policy collaboration that help us to better understand and serve cities. His previous book, The Urban Commons, captures the intersection of his efforts to advance both science and practice in cities, using the study of "custodianship" in neighborhoods through Boston's 311 system to illustrate the potential of cross-sector collaborations in urban informatics. Print version record. City planning. 57465 Big data. 57216 City planning Data processing. 64648 BUSINESS & ECONOMICS / Statistics bisacsh 64448 COMPUTERS / Database Management / Data Mining bisacsh 64305 MATHEMATICS / Probability & Statistics / General bisacsh 63965 Print version: O'Brien, Daniel T., 1983- Urban informatics. Boca Raton : Chapman & Hall/CRC, 2022 9781032274683 EBSCOhost https://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&db=nlabk&AN=3461328 Askews and Holts Library Services ASKH AH40232904 EBSCOhost EBSC 3461328 92 N$T 56036 56036