1. Evolutionary informatics: unifying knowledge about the diversity of life 
Cynthia S. Parr, Robert Guralnick, Nico Cellinese, Roderic D.M. Page 
Trends in Ecology & Evolution 
Volume 27, Issue 2, Pages (February 2012)
DOI: /j.tree
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2. Figure 1
Interlinked challenges for evolutionary informatics. Informatics provides the ability to answer fundamental questions efficiently and rapidly by automating approaches to discover, interlink and analyze the ever-growing amount of data stored in repositories. Harnessing and augmenting data from multiple sources (e.g. biodiversity [78], anatomical and genetic studies) for evolutionary biology research is evolutionary informatics. Doing so creates new knowledge products that, in turn, can be linked together and lead to the ability to ask previously difficult or completely novel, broader-scale, research questions. The interlinked key challenges in developing this infrastructure are noted above and referenced numerically to the challenges in the main text. Unique to evolutionary informatics is the existence of an organizational framework, the Tree of Life, which results from the unfolding of evolutionary history. Although this framework is subject to uncertainty and controversy in its details, its existence is essential for appropriate semantic linking and interpretation of data across all fields of biological knowledge.
Trends in Ecology & Evolution  , DOI: ( /j.tree )
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3. Figure 2
Cumulative growth of publications on phylogenetics, based on the number of papers found in the Web of Science by searching on the key words ‘molecular’ and ‘phylogeny’ since 1981 [based on Page, R.D.M. (2007) Towards a taxonomically intelligent phylogenetic database. Nature Precedings 18 September updated to 2010] compared with the growth of the phylogenetic repository TreeBASE, which launched in 1996 (a study in TreeBASE is equivalent to a single paper). A similar analysis by Stoltzfus, O’Meara and Mounce found that only 4% of 2010 studies that generated new trees archived them in TreeBase (A. Stoltzfus, pers. comm.) Thus, it is clear that tree deposition into the repository lags far behind tree production, and that the gap is widening.
Trends in Ecology & Evolution  , DOI: ( /j.tree )
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4. Figure 3
The growth of unnamed sequences. (a) Growth in the numbers of new species-level taxa added to GenBank each year. Taxa are partitioned into those with scientific names (‘named’; gray shading) and those that have informal names (‘unnamed’; white shading). (b) Percentage of taxa in the named and unnamed categories. Even if these taxa represent known groups but have yet to be fully documented, the rise of such sequences is remarkable and the rate of deposition is only likely to increase.
Trends in Ecology & Evolution  , DOI: ( /j.tree )
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5. Figure I
An incompletely known network of biodiversity-related databases. Dots represent 1631 projects, clustered and color-coded by the Clauset-Newman-Moore algorithm [76] using NodeXL [77], with 1704 instances of data sharing (re-use of the same data), deep hyperlinking (e.g. a page for a taxon in one online database links to appropriate resources in another online database), or indexing. The size of dot reflects the degree (i.e. number of links); links between hubs (degree >15) are enlarged for emphasis. OBIS=Ocean Biogeographic Information System, WoRMS=World Register of Marine Species, AKN=Avian Knowledge Network. See main text and Box 1 for other acronyms. Projects included Encyclopedia of Life (EOL), a leading online aggregator of descriptive information about all organisms, its partners and their partners, and 588 projects registered in the Taxonomic Databases Working Group database. The cluster of unconnected dots indicates that no linkages are known among hundreds of projects.
Trends in Ecology & Evolution  , DOI: ( /j.tree )
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