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Making the Case for LOD

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These are the session notes (rough I’m afraid) for the discussion on making the case for linked open data on day 1 of the 2013 LODLAM summit in Montreal.  At some point I’d really like to summarise these ideas better or maybe get to a point where it is possible to tell success stories and cautionary tales so that those interested in making or reusing LOD can pick up and expand on the precious work done thus far.

Gold leaf floating caught on the wind

Gold leaf floating caught on the wind
CC-BY Ingrid Mason

The wording in (brackets) is mine from recall.  Please feel free to comment and correct me if I’ve misinterpreted the notes.

  • What are the pain points? (also who feels the pain)
  • Should the O in LOD be K for knowledge and have it rebadged? (perhaps LOD isn’t the terminology for everyone to understand what LOD can do)
  • Explain LOD so people understand it (keep is simple smarty-pants)
  • Different elevator pitches to stakeholders to get support (headlines for execs perhaps and technical speak for techs?)
  • Internal use case (who will invest and put their support behind you in a LOD project in your organisation)
  • Public use case (who are the public stakeholders and are their any general or specific needs that could be filled with LOD)
  • Listening (to stakeholders, to others experience, etc)
  • Benefits? (work out what these are and who will value what you do)
  • Responsibility? (who leads this work and/or needs to be involved to make it a success)
  • Demystifying LOD for stakeholders (non-tech speak and maybe outcomes in lay terms)
  • Keep LOD ‘under the hood’ (see slide 80, ALIAOnline Practical Linked (Open) Data for Libraries, Archives and Museums, to see how the web view and the underlying linked data are presented)
  • Who for? (make sure it is clear who the audience is for LOD project)
  • Why? (be clear about the goals for a LOD project)
  • What? (have a good think about what data to generate and integration and why)
  • Issues? Backlogs of wobbly data (this is very common and often underestimated, so perhaps including this in a LOD project outline ensures this doesn’t turn into a SNAFU)
  • Type of project – demo or BAU? (depends on how much traction with key supporters and how experimental a LOD project is)
  • Creative Commons (0), revenue risk (something to do with pressure around capacity to generate income if data isn’t CC0 (which is valid in US but not Australia or NZ btw)
  • Focus on your own data – less risk and less cost
  • Example, BBC Music – point out (use other LOD)
  • Users – what are their drivers?
  • Find ways to communicate to them (the users) e.g. via discovery
  • Scale – take care with this – ecosystem grows
  • Metrics e.g. AustLit.edu.au  (to justify investment and uptake)
  • What legal or funding requirements need to be surmounted to enable the data to be released as LOD?
  • Upfront deal with rights and costs (sic and offer value or benefits)
  • Attribution – how to deal with this or ask for it
  • Galaxy Zoo and gamification of the classification of galaxies
  • Work acknowledgement (perhaps rather than at triple level, which seems quite insane)
  • Figshare as an example (of the strength of openness in support of scholarly communication)
  • Scholarly practice and new practices of tagging (as part of a LOD project?)
  • Some ideas based on experience with e-artexte by artexte (small non-profit)
  • Problem: (how to get moving and get support)
  • Agree to be a guinea pig (this is a perfect idea)
  • Find advocates in the community
  • Publishing and visibility (catalogues online via website) (LOD apparent in search interface too?)
  • Work with a partner (Concordia), extension of library service (piggy back)
  • Solution: (what they did)
  • Open access repository (see news release)
  • Lots of outreach (getting buy-in and engagement by long term partners and supporters)
  • Next steps: (building on success)
  • Research projects (taking on new ideas)
  • Success stories (these are needed for LOD projects that hit the spot!)
  • Ways to work with technophobes “helps me do something I already do” (solve a problem with LOD?)
  • Works for open data (Wikimedia), can work with linked open data
  • Who to convince? (what do you need: money, permission, technical partners, registrar time?)
  • Who to trust? (what and who are you relying on and have you relied on them before?)
  • How to manage the question of authority? (publish your own LOD because you created it and monitor that which you integrate or ingest externally)
  • Deliver to core user stories (don’t go off into the wilds unles you’ve been funded to)
  • Prototype stage (is this Agile, i.e. make sure if you have key stakeholders they’re fully engaged)
  • Keep (iterating and checking?)
  • Talk about enhancement of services (competition?)
  • Kickbacks, and feedback loops (look at how to make the most from what you have?)
  • Need to be able to demonstrate (keep the focus and the make the scope small)
  • Social – embedding your knowledge (into the LOD?)
  • Embed LOD in the tools people are already using
  • Attach LOD and allow it to emerge by stealth (trickery)
  • We need to consolidate stories for each to use (write these up)
  • Use the design pattern library

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Photo Credits

Montreal skyline photo CC BY from Flickr Manu_H
BAnQ elevator/stairs CC BY-NC-SA from Flickr 917Press