LIKE 45: Strictly Open

LIKE (London Information and Knowledge Exchange) always has interesting talks so my simple rule of thumb is to go to all that I can get to and not to worry too much what the actual subject.

And that's how I found myself at a talk on open data in academic research, which I found interesting.

We had three guides to take us through the topic, Ross Mounce of the Open Knowledge Foundation, Velichka Dimitrova, OpenEconomics coordinator, and John Murtagh a Project Officer whoo is Training in Data Management at the University of East London. Together they gave us a broad and consistent view of the subject.

As always I struggled to mix paying attention with taking notes and tweeting, so what follows is somewhat chaotic and I've applied some post-event clean-ups and analysis to try and make sense of it all. The mistakes are mine, not the speakers'.


Publishers have a monopoly on the academic papers they publish, irrespective of academics' wishes.

Academic material is non substitutable, there is only one source.

Research literature has a wider use beyond academia but they have no access to it. This is a block on further research and, hence, progress.

A lot of research is publicly funded but then hidden behind pay walls. Downloaded PDFs are not allowed to be mined electronically.

There is a basic conflict of interest at the heart of this debate; profit (for publishers etc.) v shared knowledge leading to new discoveries. Open Data helps us to stand on the shoulder of giants.

Need to share research data to understand/challenge the research, hence the new topic of Research Data Management.

Access to the data is required but it must also be controlled, i.e. used properly.

Need access to the publish data alongside the article that comes to conclusions from it. The data and data collection are separately citable. The data may even be more valuable than the report summarising it and the collection of data is a skill in its own right.

Data are information, and librarians know how to manage information.

My summary of the summary is that we have been used to KM being at the top of a Data > Information > Knowledge pyramid and that means that the importance of Data has sometimes been overlooked.

After the talks LIKE does what it always does and the conversations continued over food and drinks as the social element of the evening came to the fore.