Session question: As museum and archives staff with collections digitization and access responsibilities, how can we best help scholars in their work?
Two threads to this question:
- Digitized museum/archives material—how do museums and archives make that relevant?
- How do museums and archives find out what scholars want?
What point are researchers at when they reach us in the Reading Room—e.g. early in their research, later on, too late for us to help?
- We’re not always sure.
- At The Henry Ford, we get a lot of walk-in traffic from Greenfield Village.
- But isn’t the walk-in traffic a good thing? Creates interest/excitement among the public about archival research.
Right now, scholars find museums/archives (specifically The Henry Ford) in a couple of ways:
- Via word of mouth—our archival collections, subjects covered, etc., traced from one academic book or paper to the next. (Possibility here of cultivating user contact networks—see below.)
- Cataloging (library catalog, online collections, etc.)
Other ways museums and archives might engage with scholars and share ideas:
- The Tech Museum in Stockholm has a board of scholars located throughout Sweden—mostly mid-career folks who provide advice, user contacts, etc.
- Since some museums/archives (like The Henry Ford) take in many new collections, we could we could think about cultivating new/influential/important users or specialists for certain collections? Maybe write blog posts, document their findings.
- A Lemelson fellow notes that Lemelson requested a “pop” blog post early on from him—not required, but requested. Another way to reach out to a potentially broader audience, span academic and public history, cultivate relationships with potential users.
Look into use of usability and personas.
- The Henry Ford is working on this in its current digital efforts, but existing personas are more “general public” focused rather than scholarly, given THF’s public history focus.
Think about crowdsourcing.
- One cool example: New York Public Library “What’s on the Menu” crowdsourcing project
- The Henry Ford has tens of thousands of auto racing photos on Flickr, digitized by the donor, and users have provided feedback via comments, and have found errors (wrong race, etc.)
- Consider multiple layers or sets of metadata authority: official tags, machine generated tags, crowdsourced tags. What if searchers could turn each set on/off?
How can we share more?
- One professor likes The Henry Ford’s videos on YouTube of the Model T—but how can we share more? For example, have to go to another YouTube user to find a video showing how to drive a Model T. This could be a teaching tool (but also general public friendly).
How centralized does content have to be (e.g. on collections website vs. YouTube, Flickr, aggregator sites)?
- “Your destination is your content, not your domain.” — Piotr Adamczyk, Program Manager, Google Cultural Institute
What library/archive/museum sites work/don’t work for scholars?
- “Google works.”
- WorldCat
- Southern folklore collection – not well digitized (hundreds of images in one big file)—but you can tell what was digitized and what wasn’t
- Digital New Zealand—aggregated national collections with really user friendly APIs, used in schools, nice social media integration
- National Library New Zealand – nice job digitally; monetization on some content (high res) to offset costs.
Suggestion: Find ways to bring people “behind the scenes” digitally, expose this work. Examples:
- National Railway of Scotland—brought people behind the scenes with locomotives
- Seaport Museum in Philadelphia—has a live shot cam
- Academy of Nat’l Sciences Philadelphia (Drexel)—live lab cam
- Nat’l Inst. of Health/PubMed – scrolling live feed shows what people are searching for
- At The Henry Ford, why not add glass to see into archival stacks from hall? Real, live archivists, registrars, etc. doing their day-to-day work.
What is the cost-benefit analysis for digitization?
- Appropriate for The Henry Ford: Think about automotive metaphors for balance between digitization access and volume (the Lincoln versus the Fiesta)
- What level of effort do we have to make before putting out a dataset—e.g., how much work do we have to do vs. how much work do the scholars have to do?
- One example: business ledgers. We could image, we could OCR—but what else do we need to do? Excel or other formatting? Probably better not to go that far—scholars would rather do the analytic work themselves to be sure it’s right. Make data available for download—but use share-alike license. Perhaps create one model data set as a seed.
- It doesn’t need to be polished but needs to be findable/accessible, in order to start the “trip down the rabbit hole.” Need agile layers of specificity.
- Copyright and permissions are also factors here.
One conclusion: Get stuff out there, doesn’t always have to be perfect! Just be open about how “not perfect” it is—being open about process, not always only about the output.
