Richard Urban – THATCamp Museum Computer Network 2010 http://mcn2010.thatcamp.org The Humanities and Technology Camp Sat, 30 Oct 2010 18:08:18 +0000 en-US hourly 1 https://wordpress.org/?v=4.9.12 Visualizing Museum Collections http://mcn2010.thatcamp.org/10/08/visualizing-museum-collections/ http://mcn2010.thatcamp.org/10/08/visualizing-museum-collections/#comments Fri, 08 Oct 2010 04:13:18 +0000 http://mcn2010.thatcamp.org/?p=190

As our online collections grow larger, understanding the forest for the trees becomes increasingly difficult. Online search engines like Google represent an increasing source for website traffic, providing targeted search results to user queries. Many museum websites offer only a tantalizing glimpse at the rich resources that make your museum’s collection unique.

This unconference session explores the opportunities of using lightweight visualization techniques to provide a different view of your museum’s collection information that can be used to inform in-house metadata projects, provide users with an overview of your collection’s depth and breadth.

Information visualization technology has been developing rapidly over the last few years. Much of it has been inspired by the rapid accumulation of data in science and commerce. Many visualization projects are very expensive long term projects that develop a novel way of representing a unique dataset. The resulting visualizations are indeed spectacular and can be powerful tools for analysis, for inspiring new insights and for teaching and explaining findings. However in parallel to this ‘Cadillac’ infoviz, we have recently seen the growth of a more modest, low cost but surprisingly robust and powerful ‘Model T’ infoviz. By exploiting online tools and cloud computing (including Many Eyes and Google docs and maps), it is possible to put together visualization in minutes and at practically no cost – once you know the tricks and the quirks of the system. Naturally there is less flexibility than in the bespoke systems built from scratch, but we have found that often these visualizations are ‘good enough’ for particular purposes. Their speed of development makes it feasible to design many different visualizations for many different needs, rather than trying to design a single very expensive visualization that has to be all things to all people in order to justify its expense.

This unconference session will extend the conversation begun during the

Information Visualization and Museum Practice session and provide an open opportunity for delegates to discuss the problems that information visualization might solve at their institution.

To get the conversation started,  we might explore the following questions:
How can information visualization help visitors to the collection:

  • What is this collection ‘about’? What is this subcollection about?
  • What is this collection mostly about?
  • Where have most of our items come from?
  • That looks odd! Interesting – I think I need to look at that more closely

How can information visualization help stakeholders/staff:

  • That looks odd! I think that must be an error in our metadata.
  • That looks odd! I think there may be a consistent pattern of errors in our metadata.
  • That looks odd! Surely something is missing!
  • We have some but limited resources to add some metadata – what should we do?
  • How are our collections being used?
  • What is as we expected?
  • What have visitors done that is surprising?
  • What have visitors not done much of that is surprising?

Facilitators will provide case studies from the development of “collections dashboards” for the Metropolitan Museum of Art, the Opening History aggregation and theSpurlock Museum, along with related international projects. Panelists will outline how participants can extract flexible metadata for use in rapid prototyping visualization tools and services that they can use to get started on their own museum visualizations.

Session Info

  • Type: Unconference
  • Keywords: visualization, metadata,
  • Relevance: This unconference session addresses both back-of the house needs to understand institutional data and front-of-the-house needs to make information about our collections transparent.
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