Publication
Available online and in print.
Symposium Participants & Contributors
Lisa Ackerman (World Monuments Fund)
Interview – Heritage Data Collection
Marco Castro Cosio (Columbia University School of Journalism)
Interview – Mapping Experiences onto the Digital and Physical Landscape
Andrew S. Dolkart (Columbia GSAPP)
The Challenges of Legacy Data in Preserving the Historic Built Environment
Matthew Hampel (Loveland Technologies)
Managing Historic Complexity: Practical Lessons from Tech-Forward Historic Resource Surveys
Janet Hansen and Sara Delgadillo Cruz (City of Los Angeles)
Big City, Big Data: Los Angeles’s Historic Resources
Randall Mason (University of Pennsylvania School of Design)
Connecting Preservation to Urban Policy in a Data-Rich Future
Jennifer L. Most (New York City Department of Transportation)
The Case for Data Analytics in Preservation Education and Practice
Douglas S. Noonan (Indiana University School of Public and Environmental Affairs) and Tetsuharu Oba (Kyoto University)
Perspectives on Data in Urban Historic Preservation Policy
Michael Powe (National Trust for Historic Preservation Research and Policy Lab)
Using New Data to Demonstrate Why Old Buildings Matter
Eduardo Rojas (University of Pennsylvania School of Design)
Social Actors in Urban Heritage Conservation: Do We Know Enough?
Alicia Roualt (18F)
Interview – Urban Planning and Technology Practice: A Heritage Opportunity
Stephanie Ryberg-Webster (Cleveland State University) and Kelly L. Kinahan (University of Louisville)
The Possibilities and Perils of Data-Driven Preservation Research: Lessons from a Multiyear Study of Federal Historic Rehabilitation Tax Credits
Emily Talen (University of Chicago)
Historic Buildings, Chain Stores, and Mom-and-Pop Retail
Amanda L. Webb (University of Cincinnati)
Historic Preservation in a New Era of Building Energy Data
Vicki Weiner (Pratt Center for Community Development)
Democratizing Data: Pratt Center’s Neighborhood Data Portal
Jeremy C. Wells (University of Maryland, College Park), Vanilson Burégio (Federal Rural University of Pernambuco), and Rinaldo Lima (Federal Rural University of Pernambuco)
Big and Deep Heritage Data: The Social HEritage Machine (SHEM)