Curator of the Future

One of the perks of being a research placement at the British museum is the possibility to go to events you normally wouldn’t have the chance to participate in. Today I went to the Curator of the Future conference. Afterwards I realised that I had no clear definition of the word ‘curator’ and consulted WordNet:

curator: the custodian of a collection (as a museum or library)

However, presentations at the session the Curator and Digital revolved around new ways of user engagement and story telling. I started wondering whether a curators role is shifting from being a custodian of a collection to the person we turn to for putting an object in its proper context.

A quote Zoe Hughes (Natural History Museum) provided was “people don’t care about your collection”. Considering this as a bit harsh, she wondered whether this was because they don’t know about the collection or don’t care about the topic and in response started tweeting about her fossil cephalopods. Is this something new, did curators previously not consider their public?

Anra Kennedy (Culture24) posed that the traditional ‘supply oriented’ approach of offering content does not work anymore and that this has to shift to considering audiences in areas such as social, local and mobile. But a point which Chris Michaels (British Museum) made during the discussion about digital publishing was: “If people do not know what is in you museum, why come?”. So should future story telling of curators be guided by the public? Isn’t it dangerous to let the public guide the topics of stories, while they might not even be aware whats in your museum? Digital publishing could also be an opportunity to show people what otherwise would be hidden.

Thanks to Sarah Mengler for pointing me to this conference!

Trip Report: MCN 2014

Dallas, not the most inspiring city to have a museum conference. Starting the conference off with a Forth Worth museum tour and having a great view from the 24th floor made me rethink that (a bit). Beforehand I was curious how I would experience a museum focussed conference such as MCN2014, but the many parallels with my work made it worth the while.

Cristiano Bianchi from keepthinking gave a thought provoking talk about responsiveness, starting of with the question whether responsiveness only involves adapting to different screen sizes. One of the insights was the fact that tablets are more often used for reading long pieces of text, while getting less content to show. Responsiveness should be more context dependent, especially now more and more varied devices are used to access web content. Having a smaller screen should mean better prioritisation of information, not less information and data structures should support this.

The session wisdom of the crowds showed a number of different approaches to using crowdsourcing in a museum context. Dominic McDevitt-Parks gave a very practical talk on how to setup a Wikipedia edithaton, while the Columbus museum showed how they use existing social networks to spark successful participatory initiatives focussed on photography. In their experience such initiatives help build a community, the lessons learned: test your hashtag, find a fitting audience and keep it simple.

The theme Linked Data was more prominent than expected, even having its own session. Nonetheless, an ideal use case such as integrating 150+ museum collections of museums on Nova Scotia never mentioned the existence of RDF. Apparently these museums were small enough to be told to all use the same content management system. I was pleasantly surprised though by the use of DBPedia for autocompletion of species in a horticultural database.

The International Image Interoperability Framework (IIIF) was a good showcase of how Linked Data principles can be used to integrate data (loved the coop silos picture). IIIF focusses on image delivery, providing two specifications of APIs. The image API is used to retrieve images from servers, enabling a standardised way of specifying size, format and region. The second API supports JSON-LD and is used to retrieve metadata of images. While all of this was based on Linked Data, they did a good job in not showing this to the user and keeping things as simple as possible. Mirrador was showcased, an image viewer focussed on humanities scholars utilising the two APIs, which could be very suitable for the INVENiT project.

The actual Linked Data session was a bit disappointing: people discussing their one year of experience in trying to publish their collections as Linked Data and a Google employee requesting more event data (as in when a exhibition will take place). There was an interesting question from the audience though: “We all know that Linked Data will be the future for museums, but how do we convince our museum directors, in terms of crowds buzz and revenue?”. Formulating an appropriate answer was surprisingly hard, the best candidate: “Think about putting a man on the moon”.

Linking Birds: Converting the IOC World Bird List to RDF

In SEALINCMedia presentations about Accurator we often use the example of a print described as “bird near red leaf”. Although this description captures what is seen in the print,  it can be much more precise. Questions such as what sort of bird is depicted,  What is the type of the red leaf, etc. can be further answered.

This is an ideal case for the Accurator framework. We engage the appropriate niche (bird enthusiasts) to help annotate the bird prints of the Rijksmuseum with bird names from a structured vocabulary. The only problem was that we did not have such a structured vocabulary at hand.

This is where the experts at Naturalis came in. They pointed us to the IOC World Bird List, het Nederlands soortenregister and provided us with data of their own specimen collection. Since we aim to integrate these different datasets to create a comprehensive list of birds, we turned to RDF. In this blog post I describe the conversion of the IOC list.

The IOC World Bird List is available in multiple file formats. Using the Cliopatria server extended with the xmlrdf package I started the conversion process by loading the available XML file. Xmlrdf automatically turns the hierarchy embedded in the XML into a graph structure. Using rewrite rules such as the one below, the graph can be refined.

common_name_property @@
{ A, birds:englishName, B }
{ A, txn:commonName, B@en }.

As you can see the rule above replaces the property created by xmlrdf with one from the TaxonConcept ontology. This ontology contains a lot of concepts useful for modelling species data and I reused as much of these concepts as possible. Initially all the concepts in the graph are blank nodes. Using the same sort of rewrite rules, I created IRI’s of the form: The IRI’s consist of the namespace, the level in the hierarchy (e.g. genus or species) and the scientific name.

Another useful resource is available on the IOC website: a spreadsheet with bird names in 19 different languages. Using the scientific names I found the corresponding species IRI in the graph and added the different commonNames with the corresponding language tags. An example of information linked to the birds:species-phoenicurus_auroreus resource:

Predicate Value
rdf:type txn:SpeciesConcept
txn:authority “(Pallas, 1776)”
birds:breedingRegions “EU”
birds:breedingSubregions “c,e”
txn:commonName “rehek mongolský”@cs, “Amurrødstjert”@da,
“Spiegelrotschwanz”@de, “Daurian Redstart”@en,
“Colirrojo Dáurico”@es, “mustselglepalind”@et,
“laaksoleppälintu”@fi, “Rougequeue aurore”@fr,
“tükrös rozsdafarkú”@hu, “Codirosso daurico”@it,
“ジョウビタキ”@ja, “Spiegelroodstaart”@nl,
“Aurorarødstjert”@no,”pleszka chińska”@pl,
“Сибирская горихвостка”@ru, “žltochvost zrkadlový”@sk,
“Svartryggad rödstjärt”@sv, “北红尾鸲”@zh
txn:inGenus birds:genus-phoenicurus
birds:nonbreedingRegions “s China, ne India”
txn:scientificName “Phoenicurus auroreus”

Many of the objects are currently literals, while some of them could be linked to external vocabularies. Linking the regions to GeoNames is something I will look into in the future, although parsing the more specific regions will be troublesome (e.g. “w slope of the e Andes in c Colombia”).

In a following blog post I will describe the conversion of the collection data of Naturalis to RDF and how I link that information to IOC World Bird List. This conversion was done at the Web & Media group at the VU University Amsterdam, if the work sparked your interest have a look at my site.