The Beyond the PDF Conference is currently taking place in Amsterdam. Unfortunately I am unable to attend in person this time (I took part in the first Beyond the PDF in January 2011), but I was watching the livestream of the Business Case panel discussion yesterday afternoon.
How to pay for the development of new scientific infrastructure and tools is something that I think a lot about science moving away from academia to become a developer of scientific software last year. I would assume three things:
If we have enough great ideas and enough money, but don’t see the results we expect, something must be going wrong. A simple answer would be that it is different people and organizations that have the ideas from those that have the money, but I don’t think that this is the reason. My suspicion is that there is a deeper problem, and that the approach we take to scholarly innovation is broken. Below is how innovation is approached by the major players:
At the end of the day it seems that we have a lot of great ideas, but many of them never reach critical mass, and an even smaller number has long-term sustainability. I can think of a number of great projects that have never gained traction, and of a number of great tools and services where I have no idea how their development and service is paid for. The idea to get to a large number of users no matter what it costs, and figure out the business plan later is popular with internet startups, but dangerous when we care about tools we want to still use two years from now. Two projects that are not specific to science, but are important for science and have made this work are Wikipedia and Github. From the long list of tools for scientists I would not pick Mendeley or figshare (both great services, but still in search of sustainability), but ArXiV and Papers.It also doesn’t help that most scientists are a conservative bunch when it comes to technology, and that the scientific market is fairly small compared to the overall number of users. Another big challenge is to innovate in an open environment, i.e. to make the innovation available to as many people as possible without barriers of access. Some of my personal conclusions from all this are the following:
Visualizing Scholarly Content
One topic I will cover this Sunday in a presentation on Open Scholarship Tools at Wikimania 2014 together with Ian Mulvany is visualization.Data visualization is all about telling stories with data, something that is of course not only important for scholarly content, ...