One of my latest assignment is a forward looking study on science 2.0: what will science look like in 2050 based on the 2.0 paradigm?
I’d like now to start a collective brainstorming exercise. Let’s start thinking together about a fully deployed science 2.0 world. What will it look like? What will be the main differences? What are the risks and opportunities?
To kick-off the discussion, here’s a first “scenario snippet”.
In the future, the reputation of scientists will not only be based on their papers. Reuse of scientific data, for purposes such as replication and meta-review , will be a normal part of the scientist work. By default, scientist will publish their datasets, duly curated, in common repositories for other scientists to access.
These datasets will be published as linked data, which will facilitate reuse, but will also facilitate tracking of this reuse through data citation mechanisms. You will know who has reused the datasets, and what conclusions they have drawn from it.
Tracking of reuse and data citation will enable building new reputation mechanisms beyond impact factor and H-index. These new reputation mechanism will reward scientists who produce datasets that are reused by many other scientists. Data citations will be as worthy as article citations. This will encourage further data sharing as scientists who share data will actually gain from it, in terms of career.
Just as, in the music business, streaming services such as Spotify provide a far more accurate measurement of popularity than the old “top of the pops” by actually tracking the act of listening to a song down at the level of individual, so, in science, data citations will allow for more accurate measures of the reputation of scientists.
Now, it’s your turn. Provide your ideas, wild as they can be. It’s not a time to criticize and get it right; it’s the time to think aloud. Share your snippets of the science 2.0 of the future!