May 23, 2012
photo credit: Ed Bremner
The first Discovery Licensing Clinic brought together representatives from a number of different libraries, archives and museums to spend a day considering practical responses to the Discovery open licensing principles and getting practical guidance from the assembled experts. It was an opportunity to identify issues and discuss the range of tactics that institutions might adopt in scoping metadata releases and making the associated licensing decisions.
Our panel of experts on the day consisted of Francis Davey (Barrister), Naomi Korn (Copyright Consultant), Paul Miller (Cloud of Data) and Chris Banks (University Librarian & Director, Library, Special Collections & Museums, University of Aberdeen)
Chris Banks has written a blogpost reflecting on the day and her presentation slides can be viewed below:
The issues around licensing open metadata do represent a significant hurdle for institutions but none of those issues are insurmountable. Our hope is that licensing clinics such as this one, and the ones we plan to run in the future, will give managers and decision makers the knowledge they need to progress the open metadata agenda within their organisation.
May 22, 2012
On the 23rd April colleagues from projects across the Discovery, JISC Content, JISC OER and Emerging Opportunities programmes gathered in Birmingham to share knowledge and identify shared challenges and key agendas that need to be progressed going forward. As is often the way with these types of events the discussions that took place over a day and a half were as useful to those running the event as they were for the delegates attending. The notes below represent just a handful of my highlights.
Joy Palmer presented on behalf of the Discovery Programme and gave a compelling overview of the challenges and aspirations we share around the discovery of content. She highlighted how, as the RDTF work was translated into the Discovery initiative, it became clear that we needed to talk in terms of an ecosystem as opposed to an ‘infrastructure’ because the latter suggested that the initiative was aiming to impose an overarching infrastructure model over the entire museums, libraries and archives (and JISC) discovery space.
“To a large degree, what today is about is determining to what degree we can operate as a healthy and thriving ecosystem, where components of our content or applications interact as a system, linked together by the flow of data and transactions.”
But as Joy stated, this is not to oversimplify matters. Her talk touched on the many apparently competing theories about how to enable discovery in the dataspace, highlighting the complexity we’re all confronting as we make decisions about the discovery and use of our data: Big Data and The Cloud, Paradata, Linked Data, Microdata, and the ‘return’ of Structured Data.
But in terms of our shared goals to have our content discoverable or useable via the web, she explained it is the tactic of opening up data that is relevant to us all, even if our challenges in achieving ‘openness’ differ.
The slides from Joy’s presntation are available to view on Slideshare:
Discovery: Towards a (meta)data ecology for education and research
In the afternoon I facilitated Andy McGregor and David Kay’s session on business cases where the participants obligingly contributed to David’s mapping exercises.
There were some interesting discussions around the participants’ experience of writing business cases, including useful suggestions for getting the most out of building a business case:
- Predicting and measuring benefit are key challenges to overcome but we can do that by using the data at our disposal to create a convincing narrative. However it’s not about manipulating that data and making up stories retrospectively, we need to put energy into building robust analytics that help communicate our story clearly and convincingly.
- Filling out a business case template shouldn’t be an activity that only happens in order to secure funding or other resources – it can be very useful to reiterate the process throughout the course of the project in order to track any changes in the course of the project.
The following links may be useful if you are interested in building robust business cases:
In the plenary session on day two the conversations centred around a number of discussion points:
- Terms such as ‘microdata’ (machine-readable semantic tagging of webpage content) and ‘paradata’ (usage analytics or contextual information about data/metadata) were new to some of the participants and this prompted a discussion around the seemingly unavoidable challenge of jargon that we face within the Discovery arena. One suggestion was that instead of working to define a stronger vocabulary that is understood by all, perhaps we should be identifying stronger metaphors which everyone can relate to; metaphors that communicate the vision of what we are working towards and help everyone understand how they can get involved with delivering that vision within their own context.
- We should be stepping outside of the sector to see the potential for emerging areas of activity (e.g. paradata). Looking to those sectors who are ahead of the game saves the library, museum and archives sectors having to try and work from a blank page. We also need to identify where our sectors are ahead and recognise how those advantages leave us well positioned to make significant progress.
- Projects would benefit from a system of ‘evaluation buddies’ from within their programme to help uncover evidence of project impact and then share this evidence, together with highlighting any awards and recognition won by projects. This will help institutions build their internal business cases for bidding to run and then embed JISC projects in the future. There was also the suggestion that JISC could usefully build a collection of the major use cases (in a similar way to the Open Bibliographic Data Guide) together with short case studies that demonstrate the institutional impact.
- Across the two days there were mentions of ‘microdata’ (machine-readable semantic tagging of webpage content), ‘big data’ (i.e. high volume) and ‘heavy data’ (data which ‘stretches current infrastructure or tools due to its size or bulk’ but the argument was made that the primary objective should be to produce ‘simple data’ (data that is both simple to produce and simple to consume).
- There was recognition that aggregation is an art not a science and that current data standards are a) opinion, not fact and b) open to interpretation. High quality data is key to producing usable datasets but there was a question about how that quality can be defined. One suggestion was that data clean-up is a highly specialist service that should be decoupled, as per the government’s view with regard to open data.
Some key takeaway points for the Discovery programme:
- Information about the Discovery programme, its projects and the underlying principles should be in a format that is ‘reframeable’, making it easy for interested parties to access information on their terms and cascade that information to their own audience or stakeholders.
- Identifying and highlighting the tangible benefits of the Discovery Priniciples enables supporters of those principles to embark on fruitful conversations with colleagues in their institutions.
- There is huge benefit in sharing the learning and challenges from within, and without, the Discovery programme. An ongoing process of synthesis, re-synthesis and distillation will extract maximum value from the activity taking place across the Discovery initiative.
- The quality of metadata is key to the success of Discovery initiatives – we need to explore how high quality metadata is defined and ensured.