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1.
BMC Res Notes ; 7: 79, 2014 Feb 04.
Article in English | MEDLINE | ID: mdl-24495358

ABSTRACT

BACKGROUND: As biological disciplines extend into the 'big data' world, they will need a names-based infrastructure to index and interconnect distributed data. The infrastructure must have access to all names of all organisms if it is to manage all information. Those who compile lists of species hold different views as to the intellectual property rights that apply to the lists. This creates uncertainty that impedes the development of a much-needed infrastructure for sharing biological data in the digital world. FINDINGS: The laws in the United States of America and European Union are consistent with the position that scientific names of organisms and their compilation in checklists, classifications or taxonomic revisions are not subject to copyright. Compilations of names, such as classifications or checklists, are not creative in the sense of copyright law. Many content providers desire credit for their efforts. CONCLUSIONS: A 'blue list' identifies elements of checklists, classifications and monographs to which intellectual property rights do not apply. To promote sharing, authors of taxonomic content, compilers, intermediaries, and aggregators should receive citable recognition for their contributions, with the greatest recognition being given to the originating authors. Mechanisms for achieving this are discussed.


Subject(s)
Classification , Copyright , Terminology as Topic , Checklist , Databases, Factual/legislation & jurisprudence , European Union , Internationality/legislation & jurisprudence , Licensure , Ownership/legislation & jurisprudence , Publishing/legislation & jurisprudence , Publishing/standards , Registries , United States
2.
Bioinformatics ; 23(11): 1434-6, 2007 Jun 01.
Article in English | MEDLINE | ID: mdl-17392332

ABSTRACT

UNLABELLED: Web content syndication through standard formats such as RSS and ATOM has become an increasingly popular mechanism for publishers, news sources and blogs to disseminate regularly updated content. These standardized syndication formats deliver content directly to the subscriber, allowing them to locally aggregate content from a variety of sources instead of having to find the information on multiple websites. The uBioRSS application is a 'taxonomically intelligent' service customized for the biological sciences. It aggregates syndicated content from academic publishers and science news feeds, and then uses a taxonomic Named Entity Recognition algorithm to identify and index taxonomic names within those data streams. The resulting name index is cross-referenced to current global taxonomic datasets to provide context for browsing the publications by taxonomic group. This process, called taxonomic indexing, draws upon services developed specifically for biological sciences, collectively referred to as 'taxonomic intelligence'. Such value-added enhancements can provide biologists with accelerated and improved access to current biological content. AVAILABILITY: http://names.ubio.org/rss/


Subject(s)
Abstracting and Indexing/methods , Classification/methods , Database Management Systems , Information Storage and Retrieval/methods , Internet , Natural Language Processing , Periodicals as Topic , Terminology as Topic , Vocabulary, Controlled
3.
Biol Bull ; 210(1): 18-24, 2006 Feb.
Article in English | MEDLINE | ID: mdl-16501061

ABSTRACT

Given the current trends, it seems inevitable that all biological documents will eventually exist in a digital format and be distributed across the internet. New network services and tools need to be developed to increase retrieval rates for documents and to refine data recovery. Biological data have traditionally been well managed using taxonomic principles. As part of a larger initiative to build an array of names-based network services that emulate taxonomic principles for managing biological information, we undertook the digitization of a major taxonomic reference text, Nomenclator Zoologicus. The process involved replicating the text to a high level of fidelity, parsing the content for inclusion within a database, developing tools to enable expert input into the product, and integrating the metadata and factual content within taxonomic network services. The result is a high-quality and freely available web application (http://uio.mbl.edu/NomenclatorZoologicus/) capable of being exploited in an array of biological informatics services.


Subject(s)
Classification , Computational Biology/methods , Databases as Topic , Terminology as Topic , Zoology , Animals , Internet
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