A model of social collaboration in Molecular Biology knowledge bases (bibtex)
@inproceedings{DeFerrari_2009,
	_Day = {01},
	_Month = {01},
	Abstract = {Manual annotation of biological data cannot keep up with data production.
   Open annotation models using wikis have been proposed to address
   this problem. In this empirical study we analyse 36 years of knowledge
   collection by 738 authors in two Molecular Biology wikis (EcoliWiki
   and WikiPathways) and two knowledge bases (OMIM and Reactome). We
   first investigate authorship metrics (authors per entry and edits
   per author) which are power-law distributed in Wikipedia and we find
   they are heavy-tailed in these four systems too. We also find surprising
   similarities between the open (editing open to everyone) and the
   closed systems (expert curators only). Secondly, to discriminate
   between driving forces in the measured distributions, we simulate
   the curation process and find that knowledge overlap among authors
   can drive the number of authors per entry, while the time the users
   spend on the knowledge base can drive the number of contributions
   per author.},
	Author = {De Ferrari, L. and Aitken, S. and van Hemert, J.I. and Goryanin, I.},
	Booktitle = {Proceedings of the 6th Conference of the European Social Simulation Association (ESSA'09)},
	Date-Modified = {2016-03-18 11:23:11 +0000},
	Editor = {Edmonds, Bruce and Gilbert, Nigel},
	Isbn = {1844690172},
	Keywords = {e-science; data mining; curation},
	Organization = {European Social Simulation Association},
	Pages = {47},
	Publisher = {European Social Simulation Association},
	Title = {A model of social collaboration in Molecular Biology knowledge bases},
	Year = {2009}}
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