A short paper related to the Euler/X toolkit and concept taxonomy alignment project has been published. It deals with the issue of diagnosing inconsistent input constraints in an attempted pairwise taxonomy alignment, analyzing and visualizing their logical provenance so that the user can localize the inconsistencies and proceed towards repairing them. These logic services are already implemented in the toolkit.
Abstract. Derivations and proofs are a form of provenance in automated deduction that can assist users in understanding how reasoners derive logical consequences from premises. However, system-generated proofs are often overly complex or detailed, and making sense of them is non-trivial. Conversely, without any form of provenance, it is just as hard to know why a certain fact was derived. We study provenance in the application of Euler/X, a logic-based toolkit for aligning multiple biological taxonomies. We propose a combination of approaches to explain both, logical inconsistencies in the input alignment, and the derivation of new facts in the output taxonomies.
Chen, M., S. Yu, P. Kianmajd, N. Franz, S. Bowers & B. Ludäscher. 2015. Provenance for explaining taxonomy alignments. In: Ludäscher, B. & B. Plale (Editors), Provenance and Annotation of Data and Processes. Revised Selected Papers of the 5th International Provenance and Annotation Workshop, IPAW 2014, Cologne, Germany, June 9-13, 2014. Lecture Notes in Computer Science 8628: 258-260. Available on-line here.
Three members of the taxonbytes lab (Sal Anzaldo, Nico Franz, and former postdoc Aaron Smith) are co-authors of a new paper published in PLoS Biology: Finding Our Way through Phenotypes. Lead authors (in a large community effort) are Andrew Deans, Paula Mabee, and members of the Phenotype Research Coordination Network.
Deans, A.R. et al. (73 co-authors, including S.S. Anzaldo, N.M. Franz & A.D. Smith). 2015. Finding our way through phenotypes. PLoS Biol 13(1): e1002033. Link to publication
Abstract. Despite a large and multifaceted effort to understand the vast landscape of phenotypic data, their current form inhibits productive data analysis. The lack of a community-wide, consensus-based, human- and machine-interpretable language for describing phenotypes and their genomic and environmental contexts is perhaps the most pressing scientific bottleneck to integration across many key fields in biology, including genomics, systems biology, development, medicine, evolution, ecology, and systematics. Here we survey the current phenomics landscape, including data resources and handling, and the progress that has been made to accurately capture relevant data descriptions for phenotypes. We present an example of the kind of integration across domains that computable phenotypes would enable, and we call upon the broader biology community, publishers, and relevant funding agencies to support efforts to surmount today’s data barriers and facilitate analytical reproducibility.
With lead author Corinna Gries of the University of Wisconsin, two Franz Lab members have a new publication in the Biodiversity Data Journal reviewing the Symbiota software platform. Symbiota has become popular with a broad range of North American collections networks and is gaining support in Central America as well.
- Gries, C., E.E. Gilbert & N.M. Franz. 2014. Symbiota – a virtual platform for creating voucher-based biodiversity information communities. Biodiversity Data Journal 2: e1114 (24 Jun 2014). doi: 10.3897/BDJ.2.e1114. Link to Open Access publication.
A new publication is now out in BMC Research Notes.
Scientific names of organisms: attribution, rights, and licensing
David J. Patterson, Willi Egloff, Donat Agosti, David Eades, Nico Franz, Gregor Hagedorn, Jonathan A. Rees & David P. Remsen. BMC Research Notes 2014, 7:79. (9 pp.) Read more