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JSTOR is a not-for-profit service that helps scholars, researchers, and students discover, use, and build upon a wide range of content in a trusted digital archive. We use information technology and tools to increase productivity and facilitate new forms of scholarship. For more information about JSTOR, please contact support@jstor.org.. International Association for Plant Taxonomy (IAPT) is collaborating with JSTOR to digitize, preserve and extend access to Taxon. SummaryProblems in the use of electronic data processing (EDP) in biological collections are explored. To accomplish this, the uses of EDP, actual and potential, are first set forth. The uses are divided into three groups, depending on the source from which the relevant information is obtained. The problems themselves are then grouped into nine mutually exclusive categories. Each problem is discussed in detail. The concept of a decision context is introduced. Its use in making the overall decision as to whether or not EDP should be used in a particular situation is explained. A questionnaire on the problems of EDP in biological collections was returned by 22 curators. Their comments are incorporated into the appropriate places of the text. All use subject to JSTOR Terms and Conditions types do we have, etc. Lists of specimens available for exchange or loan. Lists of specimens examined or scored in a taxonomic study. Preparation of duplicate ribbon copies of specimen labels. Breeding and flowering times. Geographic distribution maps. Multivariate analysis of distribution maps. Specimen InformationAutomated character recording. Storage and analysis of information for floras. Preliminary establishment of multivariate patterns of phenetic relationships among groups. Automated construction of keys using generalized discriminant functions (e.g., Blackith, 1965). Automated specimen identification. Screening and searching data for special characters or particular states. Host-pathogen lists. Ecological studies, e.g., principal components analysis of the vegetation of a small area. Character analysis (e.g.,, Sokal, 1962). Extraspecimen InformationNomenclatural lists, e.g., the Gray Herbarium Index. Bibliographies according to taxa, geographic areas, etc. List of current taxonomic projects, by taxon, taxonomist, country, etc. Chromosome lists. Lists of vernacular names.
JSTOR is a not-for-profit service that helps scholars, researchers, and students discover, use, and build upon a wide range of content in a trusted digital archive. We use information technology and tools to increase productivity and facilitate new forms of scholarship. For more information about JSTOR, please contact support@jstor.org.. International Association for Plant Taxonomy (IAPT) is collaborating with JSTOR to digitize, preserve and extend access to Taxon. SummaryProblems in the use of electronic data processing (EDP) in biological collections are explored. To accomplish this, the uses of EDP, actual and potential, are first set forth. The uses are divided into three groups, depending on the source from which the relevant information is obtained. The problems themselves are then grouped into nine mutually exclusive categories. Each problem is discussed in detail. The concept of a decision context is introduced. Its use in making the overall decision as to whether or not EDP should be used in a particular situation is explained. A questionnaire on the problems of EDP in biological collections was returned by 22 curators. Their comments are incorporated into the appropriate places of the text. All use subject to JSTOR Terms and Conditions types do we have, etc. Lists of specimens available for exchange or loan. Lists of specimens examined or scored in a taxonomic study. Preparation of duplicate ribbon copies of specimen labels. Breeding and flowering times. Geographic distribution maps. Multivariate analysis of distribution maps. Specimen InformationAutomated character recording. Storage and analysis of information for floras. Preliminary establishment of multivariate patterns of phenetic relationships among groups. Automated construction of keys using generalized discriminant functions (e.g., Blackith, 1965). Automated specimen identification. Screening and searching data for special characters or particular states. Host-pathogen lists. Ecological studies, e.g., principal components analysis of the vegetation of a small area. Character analysis (e.g.,, Sokal, 1962). Extraspecimen InformationNomenclatural lists, e.g., the Gray Herbarium Index. Bibliographies according to taxa, geographic areas, etc. List of current taxonomic projects, by taxon, taxonomist, country, etc. Chromosome lists. Lists of vernacular names.
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