An announcement. The taxonbytes website has seen minimal new content in the past 6-8 months. We now have an official successor for the blog, and effectively for much of the content presented here. taxonbytes will soon become dormant, but not taken off-line. Our new, more social, and more formally branded content will be presented here:
We hope that taxonbytes has been a source of valuable information to some, and thank everybody very profoundly for contributing and reading along. Nico Franz
Novel Euler/X diagnostics for inconsistent input alignments.
Two taxonomies together with 9 input articulations are shown in the TAP (taxonomy alignment problem) on the left. It is not clear what the “combined taxonomy” looks like. For this example, calling Euler/X’s “check-consistency” command yields “No” – the TAP is inconsistent, i.e., self-contradictory. Even for the trained expert it is difficult to locate the error. Euler/X can execute a “black-box inconsistency analysis”, trying various combinations of articulations to see which subsets of articulations are consistent. The resulting diagnosis lattice has 2^9 = 512 nodes, and is therefore hard to navigate. Euler/X can extract from the 512 combinations 9 maximal consistent sets (i.e., the purple combinations in the lower right cannot be extended with any of the missing articulations without rendering the alignment inconsistent), and 2 minimal inconsistent sets (i.e., the red subsets are already inconsistent, but removing any articulation will yield a consistent subset). This allows the user to effectively explore and understand the consistency/inconsistency landscape, leading to efficient repair actions.
Euler/X toolkit visualization of Maximal Consistent Sets (MCS) and Minimal Inconsistent Sets (MIS).
Fourth post in this sequence (here are posts 1, 2, 3, respectively). Changing gears a little. The motivation for this post is to explore the interactions of explicitly and implicitly communicated taxonomic concepts in conversations among (living, meeting) humans with comparable levels of taxonomic expertise. How many identifiers are we talking about?
The exploration has two parts. The first part simulates a brief conversation of the kind that two human speakers may engage in while meeting in the hallways at a taxonomically oriented conference. The speakers know of each other, either through prior personal interactions or (minimally) by having read several of each other’s taxonomic publications. The conversation is hypothetical, and even though certain real persons are mentioned, the sole purpose of this is to add some realism, not to pass my judgment on any taxonomic particulars. The post is about exploring how the issue of taxonomic name/concept identifier resolution relates to this kind of communication, generally.
The second part examines the conservation from the perspective of representing taxonomic reference – “logically”. By that I mean framing the taxonomic content identifiers communicated explicitly or implicitly by the human speakers in such a way that a computational, logic-based application can adequately represent them. Ok, so here goes (in part, as it will turn out).
A 1-year NSF Funded Postdoctoral Fellow position is available immediately in the Section of Invertebrate Zoology at the Carnegie Museum of Natural History, Pittsburgh, PA. Specific details of the position, and instructions on how to apply, are listed in the announcement below. The initial review of applications is scheduled to begin on June 25th, but will be continued to accept applications until the position is filled.
Our group has two posters up for presentation at SPNHC 2015 this week.
1. Basham A., A. Mast, N.M. Franz & K.H. Holmes. 2015. Libraries of Life: connecting collections with community via Augmented Reality and specimen-based learning applications. 30th Annual Meeting of The Society for the Preservation of Natural History Collections. Gainesville, FL. Link to PDF
Third post in this sequence. In the first post, I reviewed that biological nomenclature promotes (even requires) fairly deep taxonomic semantics, due to semantically forceful principles such as Typification, Priority, Coordination, and Binomial Names. In the second post, I suggested (again, nothing very new here) that the Linnaean system has many features which, given the task on hand (reliably identifying nature’s hierarchy), are nearly optimally aligned with evolutionarily constrained human cognitive universals.
Both posts are ultimately about advancing biodiversity informatics infrastructure design. That motivation points to finding sound models of knowledge communication in the taxonomic domain. Lessons from the two preceding posts may be as follows. (1) If the goal is to build data environments that largely continue to reflect the strengths and weaknesses of human cognitive universals, then the particular balance struck by Linnaean names and name relationships acting as identifiers of evolving human taxonomy making is adequate. (2) There may be better solutions out there, particularly solutions that more effectively utilize the reasoning and scalability strengths of computational logic.
Another post on nomenclature, related to this previous post on the possibly thankfully strong influence of nomenclatural principles on taxonomic practice.
Many taxonomists, including myself certainly, continue to wonder and explore why exactly nomenclature is the way it is. The aim is first and foremost to obtain a sound explanatory account. Whether one likes the explanations, or the practice as illuminated in part by the explanations, is initially another subject.