Playing with collections at the Cooper-Hewitt (September 19)

September 19, 2012 by

1. Some terms to look up and define for your group, in your own words:

  • metadata
  • API (Hint: You’re probably going to find the PDFs at the bottom of the Wikipedia article more accessible than the Wikipedia entry itself.)
  • Creative Commons
  • public domain
  • open source
  • Omeka
  • Dublin Core

2. Visit the Cooper-Hewitt website.  What do you think the museum’s mission is?  Why would it decide make its collections data digitally accessible to so many people? How does that release of data correspond to its mission?

3. What do Ridge and Murray-John suggest are the biggest hurdles to working with collections data from museums?  Why might these hurdles exist?

4. Micah Walter writes that the visualizations he shares in his blog post “are only possible because we released the collection data as a single dump. If we had, like many museums, only provided an API, this would not have been possible (or at least been much more difficult) to do.”

  • What is the difference between releasing a collection’s metadata as a single file and providing an API to the museum’s collections?
  • What are the challenges to museum staff and end users in each scenario (API and data release in a single file)?
  • Why would a museum opt to use either approach rather than (or in addition to) sharing its collections through a web browser interface it built, as the Powerhouse Museum has done?  (See also the Cooper-Hewitt’s searchable collections database.)
  • What are the advantages and liabilities of each approach?

5. Does what you learned today, through the readings and during class discussion, change how you would approach the big data visualization project your group proposed during the last class?  If so, how and why? If not, why not?

Filed Under: Big data, Data curation, Data experimentation

Digital Data Curation (September 12)

September 12, 2012 by

1. What is a collection? What is an aggregation?

2. What is the difference among the practices of preserving, curating, and aggregating data?  What are the challenges of each of these practices?

3. What are some of the tensions present in data curation?  (For example, “openness and access vs. intellectual property rights”)  How are these tensions being addressed, and how, if at all, might they be resolved?

4. How would you go about digitally preserving or documenting your family history? How much would you share, and where/how would you share it? How would you determine what to keep private, if anything? How would you organize the information? How much would you curate the collection?  (For example, would you just put up a searchable database of the digital objects, or would you create finding aids, set up browsable categories, or write an essay that provides an overview of the collection?) Would you make it easy for other people to contribute to the collection, or would it be a closed collection (limited to your own objects)?  How would you determine what objects, people, or topics belonged in the collection and what did not?

5. Knowing that archivists’ time and preservation resources aren’t unlimited, what criteria should the Library of Congress use to determine which election-related or end-of-presidential-term websites should be preserved? In what form should those websites be preserved, and through what interface should they be made findable by researchers and others?

Filed Under: Big data, Data curation, Digital preservation