NZ eResearch Symposium 2012: Notes from the first keynote
Cameron Neylon, soon to be the Advocacy Director of the Public Library of Science provided the symposium's first keynote. Here is a loose collection of themes and arguments that were presented at the talk. Note: any incompleteness is purely my fault!
The public are the customers of research. The public cares about outcomes, not outputs like research papers. Research impacts are important.
Massive networks enable massive network effects. The Internet has qualitatively changed the nature of research. This means that systems which were designed in a pre-Internet era must change.
Themes and topic areas
Replace (or at least supplement) supply-side filtering with demand-side filtering
By design, peer-review acts as a filter for what is published. This, it was argued, was flawed. Someone's flawed conclusion may be some else's new metholodogy. Someone's flawed metholodogy may be the source of someone's new data.
Metrics for research
Citation count should not be the only way to count research. As research outcomes are what people care about, they should be what are measured. Citations, papers and conference proceedings are not interesting to the "customer" of research -- the global public.
Old way of publishing is dead...
The talk spent some time explaining that the economics of research communities will drive publishing companies to open research.
...but the issue is how to transition to a new model
There are many dependencies with the old model. Many of out processes are based on it existing.
Are we replacing an inequitable system with another inequity? That is, will researchers who can't afford to have their works published in open access journals be excluded from the research community.
Here are some raw notes that I produced while the talk was happening:
Science infrastructure has lots of potential. But not yet a sense of
achieving it. There seems to be something missing in the potential of the web. Background: - open access, perhaps extreme; but wont be talking about public good. 3 areas of the talk: - quality of service - value for money - sustainability Who is the customer? - Crown, ... - public Outputs - research outcomes - not papers - not datasets Public has quite a sophistic - creating long term infrastructure - but they're not interested in the medium that research is communicated Why are we having this discussion now? - Technological shift; will necessarily drive change within research - Most densly connected network that has ever connected - They change what we can achieve, not just Phase change
- exhibits all of the same properties - qualitatively change the properties of the material What does it mean? - they enable us to do new things - qualitatively different Example 1: Tim Gowers Question : Is it possible to do massively collaborative mathematics? World's expert has been beaten by comments in a blog. "It feels as though
this is to normal research as driving is to pushing a car"
Example 2: Galaxy Zoo Classification of galaxies. Humans are much better than people. 150k people
had usded. 100 in a week. To publish, you would need about 10,000 galaxies. Over the
course of PhD, one person classified 50,000 galaxies. Even at this scale,
the community was getting inconsistent results. Because the classified
images were 1/20th of what the Sloan Digital Sky Survey. The architecture: the Internet allowed results to be sent to information
processing units, e.g. people, and efficient transfer of the results. Has
qualitatively changed what is needed for publication today. Systems need
to minimise friction for each of the parties. So.. how do we make networks? - As service provides, how do we deliver those networks? Requisites: 1. scale 2. transfer of information needs to havevery low friction 3. it's no good to tell people to go to public libraries, because "that's
good enough" The web makes these easy. But there is a problem. If your process requires
creating friction, you are selling a product that nonoe wants. You are
creating a system that is deliberately wasteful.
Tweets within a few days of publication are highly correlated with citations. It doesn't matter that other people are not researchers. At the scale of
hundreds of millions, you "manufacture serendipity". You make connections
outside of If any of those people click on a link and can't access the paper, you break
a connection. You lose connectivity. You break potential outcomes. Researchers are optimising impact, people outside of the research ocmmunity
is the value proposition. Limiting access will break things. Why don't we? Car analogy. You send car to be serviced. Imagine you are paying for that
by giving the to the garage and renting that back to you. Makes perfect
sense. Until you try to use the car for something else. By paying up front, you are free to do what you want. However, you're also
risking quality. First-copy costs. SMEs - Denmark - e72 million in So say $30M in NZL. $3k * 10k papers = $30 millino Need to think of this is a service economy. Demand-side filters Our old publicaiton models are dead. They are zombies. They will not work.
But making content marked-up, semantically accessible is a great business
model. Peer-review is a filter. Filters block. Blocks are also friction. What is
something doesn't get to get to get peer-review. Intimidation, et cetera. Peer-review is not the right filter for everyone. Google doesn't get better by taking pages off the web. It gets better by
understanding what users are viewing on . Filter on the demand side allows customers to have control to get what
they need and what they find useful. Authors want to be used and cited. Open access and open content is how this happens. It enables a larger
network. Summary 1. network at scale 2. low friction 3. demand-side filters We need to think at network scale. At scale, there is someone interested.
You have no idea who they are or what they will do with your work. What can researchers do? Build human networks. Human networks work. Share. The worst that could happen is that someone could use your work. The
research commons is non-rivalous. We can all use this to make money and
send stories to the government about why investment in public infrastructure
is important. We could build a sustem based on today's truths. But today wont last. You build tomorrow by building on tomorrow's futures. Innovators do not
follow markets, they create them.