When visuals gone wrong ...
If you are in biosciences related work many times you have seen a fabulous but meaning-less image in the sci papers, typical error to represent data with wrong visuals perceptions, M. E. J. Newman named "Ridiculograms" (you can see the related video in Youtube).
A ridiculogram can be defined as:
After a group discussion and a no so good seminar about text mining for disease terms, some agree that the last point can not be required, I want to extend this concept to other parts in bioinformatics.
Many people are working in the user interaction part, novel technologies have large and heavy output and require some tools to show the results, but many of this tools are redundant (yes, many people want a desktop/web/network interfaces or some programs for Linux/Windows/Mac or versions in Java/C#/Python/Perl) and while the developers think "in the user experience", they forget the concept of the tool: to show an interpretable way for the data.
Besides, this infinite dataset are non-human analyzable, who can read thousand of alignments just to say if well annotate a genomic bank? or just give the information to an army of slaves/students to perform automatic process. Maybe the way in some bioinformatic tools follow endless paths.
I prefer to code for real tools which can give a clue in the biological universe even if this looks ugly.
A ridiculogram can be defined as:
- Visual stunning
- Scientifically worthless
- Published in Nature or Science
After a group discussion and a no so good seminar about text mining for disease terms, some agree that the last point can not be required, I want to extend this concept to other parts in bioinformatics.
Many people are working in the user interaction part, novel technologies have large and heavy output and require some tools to show the results, but many of this tools are redundant (yes, many people want a desktop/web/network interfaces or some programs for Linux/Windows/Mac or versions in Java/C#/Python/Perl) and while the developers think "in the user experience", they forget the concept of the tool: to show an interpretable way for the data.
Besides, this infinite dataset are non-human analyzable, who can read thousand of alignments just to say if well annotate a genomic bank? or just give the information to an army of slaves/students to perform automatic process. Maybe the way in some bioinformatic tools follow endless paths.
I prefer to code for real tools which can give a clue in the biological universe even if this looks ugly.
I love the concept of ridiculograms. Thanks!
ReplyDelete(And, have you any notes from the seminar on TM for biomedical terms?)
Sorry but I did not take notes, but you can read:
ReplyDeletePLoS Comput Biol. 2006 Sep 8;2(9):e118.
Cell. 2008 Jul 11;134(1):9-13.
EMBO Rep. 2008 Mar;9(3):212-5.