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The use and limits of scientific names in biological informatics.

ABSTRACT: Scientific names serve to label biodiversity information: information related to species. Names, and their underlying taxonomic definitions, however, are unstable and ambiguous. This negatively impacts the utility of names as identifiers and as effective indexing tools in biological informatics where names are commonly utilized for searching, retrieving and integrating information about species. Semiotics provides a general model for describing the relationship between taxon names and taxon concepts. It distinguishes syntactics, which governs relationships among names, from semantics, which represents the relations between those labels and the taxa to which they refer. In the semiotic context, changes in semantics (i.e., taxonomic circumscription) do not consistently result in a corresponding and reflective change in syntax. Further, when syntactic changes do occur, they may be in response to semantic changes or in response to syntactic rules. This lack of consistency in the cardinal relationship between names and taxa places limits on how scientific names may be used in biological informatics in initially anchoring, and in the subsequent retrieval and integration, of relevant biodiversity information. Precision and recall are two measures of relevance. In biological taxonomy, recall is negatively impacted by changes or ambiguity in syntax while precision is negatively impacted when there are changes or ambiguity in semantics. Because changes in syntax are not correlated with changes in semantics, scientific names may be used, singly or conflated into synonymous sets, to improve recall in pattern recognition or search and retrieval. Names cannot be used, however, to improve precision. This is because changes in syntax do not uniquely identify changes in circumscription. These observations place limits on the utility of scientific names within biological informatics applications that rely on names as identifiers for taxa. Taxonomic systems and services used to organize and integrate information about taxa must accommodate the inherent semantic ambiguity of scientific names. The capture and articulation of circumscription differences (i.e., multiple taxon concepts) within such systems must be accompanied with distinct concept identifiers that can be employed in association with, or in replacement of, traditional scientific names.

SUBMITTER: Remsen D

PROVIDER: S-EPMC4741222 | biostudies-other | 2016

REPOSITORIES: biostudies-other

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Project description:For more than 250 years, the taxonomic enterprise has remained almost unchanged. Certainly, the tools of the trade have improved: months-long journeys aboard sailing ships have been reduced to hours aboard jet airplanes; advanced technology allows humans to access environments that were once utterly inaccessible; GPS has replaced crude maps; digital hi-resolution imagery provides far more accurate renderings of organisms that even the best commissioned artists of a century ago; and primitive candle-lit microscopes have been replaced by an array of technologies ranging from scanning electron microscopy to DNA sequencing. But the basic paradigm remains the same. Perhaps the most revolutionary change of all - which we are still in the midst of, and which has not yet been fully realized - is the means by which taxonomists manage and communicate the information of their trade. The rapid evolution in recent decades of computer database management software, and of information dissemination via the Internet, have both dramatically improved the potential for streamlining the entire taxonomic process. Unfortunately, the potential still largely exceeds the reality. The vast majority of taxonomic information is either not yet digitized, or digitized in a form that does not allow direct and easy access. Moreover, the information that is easily accessed in digital form is not yet seamlessly interconnected. In an effort to bring reality closer to potential, a loose affiliation of major taxonomic resources, including GBIF, the Encyclopedia of Life, NBII, Catalog of Life, ITIS, IPNI, ICZN, Index Fungorum, and many others have been crafting a "Global Names Architecture" (GNA). The intention of the GNA is not to replace any of the existing taxonomic data initiatives, but rather to serve as a dynamic index to interconnect them in a way that streamlines the entire taxonomic enterprise: from gathering specimens in the field, to publication of new taxa and related data.

Project description:BackgroundScientific names in biology act as universal links. They allow us to cross-reference information about organisms globally. However variations in spelling of scientific names greatly diminish their ability to interconnect data. Such variations may include abbreviations, annotations, misspellings, etc. Authorship is a part of a scientific name and may also differ significantly. To match all possible variations of a name we need to divide them into their elements and classify each element according to its role. We refer to this as 'parsing' the name. Parsing categorizes name's elements into those that are stable and those that are prone to change. Names are matched first by combining them according to their stable elements. Matches are then refined by examining their varying elements. This two stage process dramatically improves the number and quality of matches. It is especially useful for the automatic data exchange within the context of "Big Data" in biology.ResultsWe introduce Global Names Parser (gnparser). It is a Java tool written in Scala language (a language for Java Virtual Machine) to parse scientific names. It is based on a Parsing Expression Grammar. The parser can be applied to scientific names of any complexity. It assigns a semantic meaning (such as genus name, species epithet, rank, year of publication, authorship, annotations, etc.) to all elements of a name. It is able to work with nested structures as in the names of hybrids. gnparser performs with ≈99% accuracy and processes 30 million name-strings/hour per CPU thread. The gnparser library is compatible with Scala, Java, R, Jython, and JRuby. The parser can be used as a command line application, as a socket server, a web-app or as a RESTful HTTP-service. It is released under an Open source MIT license.ConclusionsGlobal Names Parser (gnparser) is a fast, high precision tool for biodiversity informaticians and biologists working with large numbers of scientific names. It can replace expensive and error-prone manual parsing and standardization of scientific names in many situations, and can quickly enhance the interoperability of distributed biological information.

Project description:BackgroundWith the emerging information and communication technology, the field of medical informatics has dramatically evolved in health care and medicine. Thus, it is crucial to explore the global scientific research landscape on medical informatics.ObjectiveThis study aims to present a visual form to clarify the overall scientific research trends of medical informatics in the past decade.MethodsA bibliometric analysis of data retrieved and extracted from the Web of Science Core Collection (WoSCC) database was performed to analyze global scientific research trends on medical informatics, including publication year, journals, authors, institutions, countries/regions, references, and keywords, from January 1, 2011, to December 31, 2020.ResultsThe data set recorded 34,742 articles related to medical informatics from WoSCC between 2011 and 2020. The annual global publications increased by 193.86% from 1987 in 2011 to 5839 in 2020. Journal of Medical Internet Research (3600 publications and 63,932 citations) was the most productive and most highly cited journal in the field of medical informatics. David W Bates (99 publications), Harvard University (1161 publications), and the United States (12,927 publications) were the most productive author, institution, and country, respectively. The co-occurrence cluster analysis of high-frequency author keywords formed 4 clusters: (1) artificial intelligence in health care and medicine; (2) mobile health; (3) implementation and evaluation of electronic health records; (4) medical informatics technology application in public health. COVID-19, which ranked third in 2020, was the emerging theme of medical informatics.ConclusionsWe summarize the recent advances in medical informatics in the past decade and shed light on their publication trends, influential journals, global collaboration patterns, basic knowledge, research hotspots, and theme evolution through bibliometric analysis and visualization maps. These findings will accurately and quickly grasp the research trends and provide valuable guidance for future medical informatics research.

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The use and limits of scientific names in biological informatics.

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