Ramping up

Giving a researcher sudden access to a wealth of powerful new tools, techniques and methods is no more likely to lead to a successful journey than if someone who hasn’t learned to drive is put at the wheel of a strange new vehicle. Not even the instruction manual is going to help much! It’s challenging, it requires investment of effort and it’s even dangerous. It should be no surprise if they would rather get out and resume more familiar modes of transport.

The way we learn to be a proficient driver is incremental and assisted. At the end we can drive by ourselves. And some go on to more advanced driving challenges like fast sports cars or heavy goods vehicles. Some teach other drivers.

Similarly researchers need a means of incremental engagement with the tools, techniques and methods of e-Science, so that they can meet their needs and on their own terms. To use another transport metaphor, we can think of this as an “on ramp”: it is the intellectual access ramp for data-intensive science.

Successful projects understand this and have built all sorts of ramps to meet the different needs in different communities. On our trip the ramp has turned out to be a powerful socio-technical metaphor. Once people see the ramp as an object in its own right we can look at its shape, how it’s built and how well it works – we have become ramp-spotters and I’m thinking of compiling the Observers Book of Ramps! Some have gentle curves. Some have activation energy. Some look like tall brick walls – those tend to be the ones that don’t work well…

We come bearing ramps. The UK Virtual Research Environment projects are ramps: myExperiment provides a gentle and familiar ramp into the “World of Workflows” where workflows are easy to run but tricky to write. Some of the efforts to hide complex infrastructure behind simple APIs are ramps for developers, like SAGA (Simple API for Grid Applications) and other offerings from OMII-UK (whose business is ramp rengineering!) For the scientist, a simple drag-and-drop interface to running e-Science computations is a gentle ramp – elegantly demonstrated by the dropbox drag-and-drop interface to Condor job submission developed by Ian Cottam in the Manchester Interdisciplinary Biocentre.

We’ve seen some great ramps on the trip, including scientist-focused tool provision alongside data products in operations like Birn and Unidata. The Science Gateways endeavour to be ramps and NanoHub is a great example. It’s interesting, and perhaps no coincidence, that successful ramps like NanoHub and Unidata have “education” in their mission statements.

Some ramps have facilitators to guide researchers up the ramp – think of librarians using their skills to assist a researcher who is then able to help themselves. We’ve also seen models where a layer of abstraction is implemented to protect the researchers from the underlying details – intermediaries rather than facilitators – but there is wariness that these may also serve to hide the computational thinking from the researchers and deny potential for new practice and new accomplishments.

It seems that successful ramps are characterised by an effective alignment of community, data and software, and they have a role in developing research skills as well as conducting research. It follows that ramp construction needs an alignment of interests and funding from a community of users in research and education, their data providers, service providers and software tools providers. This combination might not be in the remit of any one funder but it’s in the interests of all, because everyone stands to gain from researchers ascending the intellectual access ramps to achieve new outcomes and build new know-how.

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