Always Already Computational: Collections as Data: Final Report

Authors

Thomas Padilla, University of Nevada, Las Vegas
Laurie Allen, University of Pennsylvania
Hannah Frost, Stanford University
Sarah Potvin, Texas A&M University
Elizabeth Russey Roke, Emory University
Stewart Varner, University of Pennsylvania

Date of this Version

5-22-2019

Document Type

Article

Citation

Always Already Computational: Collections as Data: Final Report, by Thomas Padilla (PI) Laurie Allen (Co‑PI) Hannah Frost (Co‑I) Sarah Potvin (Co‑I) Elizabeth Russey Roke (Co‑I) Stewart Varner (Co‑I), May 22, 2019.

Also available at: https://zenodo.org/record/3152935#.X6WOf-LPzIU.

Comments

Copyright 2019, the authors. Open access material. License: CC-BY-SA.

Abstract

Scope Note

From 2016‑2018 Always Already Computational: Collections as Data documented, iterated on, and shared current and potential approaches to developing cultural heritage collections that support computationally‑driven research and teaching. With funding from the Institute of Museum and Library Services, Always Already Computational held two national forums, organized multiple workshops, shared project outcomes in disciplinary and professional conferences, and generated nearly a dozen deliverables meant to guide institutions as they consider development of collections as data.

This report documents the activities and impacts of the Always Already Computational project, delineates findings, and identifies areas for further inquiry.