I attended the Evolution 2014 meeting a few months ago in Raleigh, NC, and presented a poster on Phenoscape’s curation effort: “Moving the mountain: How to transform comparative anatomy into computable anatomy?”, with coauthors A. Dececchi, N. Ibrahim, H. Lapp, and P. Mabee. In this work, we assessed the efficiency of our workflow for the curation of evolutionary phenotypes from the matrix-based phylogenetic literature. We identified the bottlenecks and areas of improvement in data preparation, phenotype annotation, and ontology development. Gains in efficiency, such as through improved community data practices and development of text-mining tools, are critical if we are to translate evolutionary phenotypes from an ever-growing literature. The poster was well received and several researchers at the meeting were interested in learning more about open source tools for phenotype annotation.
There is a wealth of phenotypic information in the evolutionary literature that comes in the the form of semi-structured character state descriptions. To get that information into computable form is, right now, an awfully slow process. In Phenoscape I, we estimated that it took about five person-years in total to curate semantic phenotype annotations from 47 papers. If we are to get computable evolutionary phenotypes from a larger slice of the literature, we really need to figure out ways to speed this up.
One promising approach is to use text-mining. This could contribute in a few different ways. First, one could efficiently identify all the terms in the text that are not currently represented in ontologies and add them en masse, so that data curation does not have to stop and resume whenever such terms are encountered. Second, one could present a human curator with suggestions for what terms to use and what relations those terms have to one another, speeding the process of composing an annotation.
CharaParser, developed by Hong Cui at the University of Arizona, is an expert-based system that decomposes character descriptions into recognizable grammatical components, and it is now being used in several different biodiversity informatics projects. Baseline evaluation results from BioCreative III showed that a naive workflow combining CharaParser and Phenex, the software curators use to compose ontological annotations and relate them to character states, was capable of identifying candidate entity and quality phrases (it outperformed biocurators by 20% in recall on average) but had difficulty translating those into ontological annotations. This first iteration workflow also was not yet reducing curation time.
In March, a small contingent from NESCent (Jim Balhoff, Hilmar Lapp and Todd Vision) visited Hong Cui’s group in Tucson. We talked through improvements to CharaParser and the curation workflow, brainstormed plans for a more thorough set of evaluation tests, began refactoring of the code so that it can be more easily shared across projects, and gained a better understanding of what features make a character difficult to curate for humans vs. text-mining. We made substantial progress on all fronts, and are looking forward to seeing how much improvement in the accuracy and efficiency of curation will be achieved in the next round of testing.
We are also pleased to report that the CharaParser codebase will now be available from GitHub under an open source (MIT) license.
In June I had the opportunity to attend DILS 2012 (Data Integration in the Life Sciences), at the University of Maryland in College Park. I presented a poster on Phenoscape, “The Phenoscape Knowledgebase: Integrating phenotypic data across taxonomy, from biodiversity to developmental genetics”. The poster highlighted some of the new directions the Phenoscape project is heading, such as broadening taxonomic coverage and adoption of semantic web technologies. DILS was a small conference but had several talks discussing the applications of ontologies to biological data. I’m looking forward to DILS 2013 in Montreal, in conjunction with ICBO and the Canadian Semantic Web conference.
A new bugfix release of Phenex is available. Phenex 1.4.2 addresses the following issues:
- Fixed missing “not” relationship in post-composition editor, https://github.com/phenoscape/Phenex/issues/14
- Fixed term filters to allow choosing provisional terms, https://github.com/phenoscape/Phenex/issues/13
- Fixed “freezing” panels display anomalies
- Fixed some ontology loading issues by updating internal OBO-Edit components to latest versions
The NESCent Informatics group periodically holds “hack days”, one day mini-hackathons where we take a break from our usual schedule and push forward on a specific topic of interest. Most recently, the topic was support for the mobile web. I took a look at the Phenoscape Knowledgebase layout on the iPad and iPhone. In general the site did not adapt well to small screen sizes.
In order to avoid serving different layouts to specific devices, I applied techniques from the Responsive Web Design approach, which uses new functionality from CSS 3 to dynamically adjust the page layout based on the size of the browser window. In the new layout, when the window is small, controls move from the side to the top, allowing both the controls and the content table to use the full screen width.
The new layout works across most of the pages on the Knowledgebase site. In general, it is a big improvement on mobile devices. However, there are a few remaining glitches to address, such as controls that appear upon mouse hover: difficult to use on a touchscreen device, where there is no mouse.
We have recently released version 1.2.1 of our Phenex annotation software. This release adds some functionality for easier collaborative editing of data files. While our curators have used Subversion revision control software in the past, the new features make it more reliable to share Phenex data files with user-friendly file synchronization software such as Dropbox. While a NeXML document is open in Phenex, the application monitors for changes to the document file in the background. If the file is being shared via Dropbox and is simultaneously edited by someone else, Phenex will alert the user that the file has changed and offer to load the new version. If there are no unsaved edits then Phenex will reload the file automatically. Phenex 1.2 also provides an autosave feature which saves the document after every edit—this reduces the chance that the file might be edited elsewhere while one has unsaved changes, avoiding complicated file merges.