I managed to get it done in a week which was good for me.
We titled it "A methodology for identifying methodologies from full text from literature"
We wanted to keep it to a description of how we did what we did, some of the many! tech problems we had to solve and how succesful this kind of thing can be. Clearly many elements can be improved, but thats more reason to get it out there. Surely there must be some proper text miners who are sick of PPI's and abstracts and want to solve some new problems, well, i've got plenty.
The best bit about the whole article is the final figure.
This was drawn using my java3D software, using my data andmy ideas over how to present the data.
Its nice to do something all by yourself that is actually quite novel and reasonable succesful in its aims.
The image describes the usage of different workflows through time (z-axis). Each workflow is represented by a shape, the diameter of which determined by it usage in each year. Colour is determined by the first use of the workflow. The x,y clustering of the workflows is specified by a radial tree, inferred using the NJ algorithm and a distance matrix of f-measure term similarity values.
