Relevant bibliographies by topics / Taxonomy information

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Taxonomy information'

Author: Grafiati
Published: 11 December 2022
Last updated: 26 January 2023

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Journal articles on the topic "Taxonomy information"

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Tuan, Luu Anh, Siu Cheung Hui, and See Kiong Ng. "Utilizing Temporal Information for Taxonomy Construction." Transactions of the Association for Computational Linguistics 4 (December 2016): 551–64. http://dx.doi.org/10.1162/tacl_a_00117.

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Taxonomies play an important role in many applications by organizing domain knowledge into a hierarchy of ‘ is-a’ relations between terms. Previous work on automatic construction of taxonomies from text documents either ignored temporal information or used fixed time periods to discretize the time series of documents. In this paper, we propose a time-aware method to automatically construct and effectively maintain a taxonomy from a given series of documents preclustered for a domain of interest. The method extracts temporal information from the documents and uses a timestamp contribution function to score the temporal relevance of the evidence from source texts when identifying the taxonomic relations for constructing the taxonomy. Experimental results show that our proposed method outperforms the state-of-the-art methods by increasing F-measure up to 7%–20%. Furthermore, the proposed method can incrementally update the taxonomy by adding fresh relations from new data and removing outdated relations using an information decay function. It thus avoids rebuilding the whole taxonomy from scratch for every update and keeps the taxonomy effectively up-to-date in order to track the latest information trends in the rapidly evolving domain.
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Rowley, Jennifer, and Frances Slack. "Information kiosks: a taxonomy." Journal of Documentation 63, no. 6 (October 23, 2007): 879–97. http://dx.doi.org/10.1108/00220410710836402.

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Burgin, Mark, and Gordana Dodig-Crnkovic. "Prolegomena to Information Taxonomy." Proceedings 1, no. 3 (June 9, 2017): 210. http://dx.doi.org/10.3390/is4si-2017-04035.

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McKinney and Yoos. "Information About Information: A Taxonomy of Views." MIS Quarterly 34, no. 2 (2010): 329. http://dx.doi.org/10.2307/20721430.

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Durkin, Louisa, Tobias Jansson, Marisol Sanchez, Maryia Khomich, Martin Ryberg, Erik Kristiansson, and R. Henrik Nilsson. "When mycologists describe new species, not all relevant information is provided (clearly enough)." MycoKeys 72 (September 10, 2020): 109–28. http://dx.doi.org/10.3897/mycokeys.72.56691.

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Taxonomic mycology struggles with what seems to be a perpetual shortage of resources. Logically, fungal taxonomists should therefore leverage every opportunity to highlight and visualize the importance of taxonomic work, the usefulness of taxonomic data far beyond taxonomy, and the integrative and collaborative nature of modern taxonomy at large. Is mycology really doing that, though? In this study, we went through ten years’ worth (2009–2018) of species descriptions of extant fungal taxa – 1,097 studies describing at most ten new species – in five major mycological journals plus one plant journal. We estimated the frequency at which a range of key words, illustrations, and concepts related to ecology, geography, taxonomy, molecular data, and data availability were provided with the descriptions. We also considered a range of science-demographical aspects such as gender bias and the rejuvenation of taxonomy and taxonomists as well as public availability of the results. Our results show that the target audience of fungal species descriptions appears to be other fungal taxonomists, because many aspects of the new species were presented only implicitly, if at all. Although many of the parameters we estimated show a gradual, and in some cases marked, change for the better over time, they still paint a somewhat bleak picture of mycological taxonomy as a male-dominated field where the wants and needs of an extended target audience are often not understood or even considered. This study hopes to leave a mark on the way fungal species are described by putting the focus on ways in which fungal taxonomy can better anticipate the end users of species descriptions – be they mycologists, other researchers, the public at large, or even algorithms. In the end, fungal taxonomy, too, is likely to benefit from such measures.
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M. Vitolo, Theresa, and Chris Coulston. "Taxonomy of Information Literacy Competencies." Journal of Information Technology Education: Research 1 (2002): 043–52. http://dx.doi.org/10.28945/343.

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Wagner, Richard H., and Étienne Danchin. "A taxonomy of biological information." Oikos 119, no. 2 (February 2010): 203–9. http://dx.doi.org/10.1111/j.1600-0706.2009.17315.x.

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Wheeler, Quentin D. "Taxonomic triage and the poverty of phylogeny." Philosophical Transactions of the Royal Society of London. Series B: Biological Sciences 359, no. 1444 (April 29, 2004): 571–83. http://dx.doi.org/10.1098/rstb.2003.1452.

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Revisionary taxonomy is frequently dismissed as merely descriptive, which belies its strong intellectual content and hypothesis–driven nature. Funding for taxonomy is inadequate and largely diverted to studies of phylogeny that neither improve classifications nor nomenclature. Phylogenetic classifications are optimal for storing and predicting information, but phylogeny divorced from taxonomy is ephemeral and erodes the accuracy and information content of the language of biology. Taxonomic revisions and monographs are efficient, high–throughput species hypothesis–testing devices that are ideal for the World Wide Web. Taxonomic knowledge remains essential to credible biological research and is made urgent by the biodiversity crisis. Theoretical and technological advances and threats of mass species extinctions indicate that this is the time for a renaissance in taxonomy. Clarity of vision and courage of purpose are needed from individual taxonomists and natural history museums to bring about this evolution of taxonomy into the information age.
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VICTOR, JANINE E., GIDEON F. SMITH, and ABRAHAM E. VAN WYK. "History and drivers of plant taxonomy in South Africa." Phytotaxa 269, no. 3 (August 5, 2016): 193. http://dx.doi.org/10.11646/phytotaxa.269.3.3.

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The development of plant taxonomy in South Africa from about 1600 to 2015 is reviewed, with emphasis on the main driving factors that have influenced the research direction, techniques used, and choice of taxonomic research topic. In addition, key personalities and important historical events are highlighted. The early scientific interest in the flora of South Africa and, by implication, its taxonomy was initially driven by curiosity. Exploration of plants for economic purposes especially for medicinal use and later, agriculture, drove the scientific development of botany and formed the foundation of formal botany in the country. Establishment of botanical gardens and herbaria influenced botanical research, in particular the field of taxonomy. Technological advances lead to increased modernisation of taxonomy as new sources of information derived from other fields of botany were incorporated into taxonomic research. Funding priorities and availability of financial resources influence the taxonomic research that is conducted, and international initiatives that impact on priorities in biodiversity science have further impact on taxonomy. At present the predominant culture of taxonomy is directed towards electronic dissemination of taxonomic information, leading to increased accessibility and connectivity. Strategic planning of plant taxonomy in South Africa has become more formal as relevance and impact of research products increasingly need to be justified with respect to the financial costs of conducting taxonomic research.
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Rauthmann, John F. "Structuring Situational Information." European Psychologist 20, no. 3 (July 2015): 176–89. http://dx.doi.org/10.1027/1016-9040/a000225.

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Abstract. There is as yet no consensually agreed-upon situational taxonomy. The current work addresses this issue and reviews extant taxonomic approaches by highlighting a “road map” of six research stations that lead to the observed diversity in taxonomies: (1) theoretical and conceptual guidelines, (2) the “type” of situational information studied, (3) the general taxonomic approach taken, (4) the generation of situation pools, (5) the assessment and rating of situational information, and (6) the statistical analyses of situation data. Current situational taxonomies are difficult to integrate because they follow different paths along these six stations. Some suggestions are given on how to spur integrated taxonomies toward a unified psychology of situations that speaks a common language.
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Dissertations / Theses on the topic "Taxonomy information"

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Chang, Dempsey H., and n/a. "A Gestalt-Taxonomy for Designing Multimodal Information Displays." University of Canberra. Arts & Design, 2007. http://erl.canberra.edu.au./public/adt-AUC20081203.123314.

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The theory of Gestalt was proposed in the nineteenth century to explain and predict the way that people perceptually group visual elements, and it has been used to develop guidelines for designing visual computer interfaces. In this thesis we seek to extend the use of Gestalt principles to the design of haptic and visual-haptic displays. The thesis begins with a survey of Gestalt research into visual, auditory and haptic perception. From this survey the five most commonly found principles are identified as figure-ground, continuation, closure, similarity and proximity. This thesis examines the proposition that these five principles can be applied to the design of haptic interfaces. Four experiments investigate whether Gestalt principles of figure-ground, continuation, closure, similarity and proximity are applicable in the same way when people group elements either through their visual (by colour) or haptic (by texture) sense. The results indicate significant correspondence between visual and haptic grouping. A set of haptic design guidelines for haptic displays are developed from the experiments. This allows us to use the Gestalt principles to organise a Gestalt-Taxonomy of specific guidelines for designing haptic displays. The Gestalt-Taxonomy has been used to develop new haptic design guidelines for information displays.
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Körlinge, Max. "Haxonomy : A Taxonomy for Web Hacking." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-254639.

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This study aims to show that the information present in public vulnerability reports from bug bounty programs can be utilized to provide aid for individual security researchers when performing their research. This is done here by creating a taxonomy based on the attack surfaces on a website that were used by the author of a report when discovering a vulnerability. Reports are then indexed according to this taxonomy together with the discovered vulnerability, to provide statistics on which vulnerabilities are most commonly found on what attack surfaces. The taxonomy and the indexed reports, referred to as the Haxonomy, are then also used as the basis for a machine learning algorithm which is trained to provide guidance to bug bounty hunters. It is concluded that this proof-of-concept, if developed fully, can be used to improve the success rate of individual security researchers operating on bug bounty platforms.
Syftet med denna studie är att visa att informationen som finns i offentliga sårbarhetsrapporter från så kallade bug-bounty program kan användas för att hjälpa individer att genomföra bättre sårbarhetstester. Detta görs här genom att skapa en taxonomi baserad på vilka attackytor på en hemsida som en författare av en sådan rapport har använt för att upptäcka sårbarheten. Sårbarhetsrapporter indexeras sedan enligt denna taxonomi, för att tillsammans med vilka sårbarheter som upptäckts ta fram statistik på vilka sårbarheter som man mest troligen kan hitta via vilka attackytor. Taxonomin och de indexerade rapporterna, tillsammans referrerade till som Haxonomin, används sedan också som material för att träna en algoritm med hjälp av maskininlärning, som kan vara till hjälp vid sårbarhetstester. Slutsatsen dras att detta konceptbevis kan utvecklas och användas för att hjälpa sårbarhetstestare att hitta fler sårbarheter i framtiden.
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Karresand, Martin. "A Proposed Taxonomy of Software Weapons." Thesis, Linköping University, Department of Electrical Engineering, 2002. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-1512.

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The terms and classification schemes used in the computer security field today are not standardised. Thus the field is hard to take in, there is a risk of misunderstandings, and there is a risk that the scientific work is being hampered.

Therefore this report presents a proposal for a taxonomy of software based IT weapons. After an account of the theories governing the formation of a taxonomy, and a presentation of the requisites, seven taxonomies from different parts of the computer security field are evaluated. Then the proposed new taxonomy is introduced and the inclusion of each of the 15 categories is motivated and discussed in separate sections. Each section also contains a part briefly outlining the possible countermeasures to be used against weapons with that specific characteristic.

The final part of the report contains a discussion of the general defences against software weapons, together with a presentation of some open issues regarding the taxonomy. There is also a part discussing possible uses for the taxonomy. Finally the report is summarised.

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Li, Danhui. "The application of mathematical taxonomy to automatic speech recognition." Thesis, University of Huddersfield, 1993. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.334681.

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Joseph, Daniel. "Linking information resources with automatic semantic extraction." Thesis, University of Manchester, 2016. https://www.research.manchester.ac.uk/portal/en/theses/linking-information-resources-with-automatic-semantic-extraction(ada2db36-4366-441a-a0a9-d76324a77e2c).html.

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Knowledge is a critical dimension in the problem solving processes of human intelligence. Consequently, enabling intelligent systems to provide advanced services requires that their artificial intelligence routines have access to knowledge of relevant domains. Ontologies are often utilised as the formal conceptualisation of domains, in that they identify and model the concepts and relationships of the targeted domain. However complexities inherent in ontology development and maintenance have limited their availability. Separate from the conceptualisation component, domain knowledge also encompasses the concept membership of object instances within the domain. The need to capture both the domain model and the current state of instances within the domain has motivated the import of Formal Concept Analysis into intelligent systems research. Formal Concept Analysis, which provides a simplified model of a domain, has the advantage in that not only does it define concepts in terms of their attribute description but object instances are simultaneously ascribed to their appropriate concepts. Nonetheless, a significant drawback of Formal Concept Analysis is that when applied to a large dataset, the lattice with which it models a domain is often composed of a copious amount of concepts, many of which are arguably unnecessary or invalid. In this research a novel measure is introduced which assigns a relevance value to concepts in the lattice. This measure is termed the Collapse Index and is based on the minimum number of object instances that need be removed from a domain in order for a concept to be expunged from the lattice. Mathematics that underpin its origin and behaviour are detailed in the thesis showing that if the relevance of a concept is defined by the Collapse Index: a concept will eventually lose relevance if one of its immediate subconcepts increasingly acquires object instance support; and a concept has its highest relevance when its immediate subconcepts have equal or near equal object instance support. In addition, experimental evaluation is provided where the Collapse Index demonstrated comparable or better performance than the current prominent alternatives in: being consistent across samples; the ability to recall concepts in noisy lattices; and efficiency of calculation. It is also demonstrated that the Collapse Index affords concepts with low object instance support the opportunity to have a higher relevance than those of high supportThe second contribution to knowledge is that of an approach to semantic extraction from a dataset where the Collapse Index is included as a method of selecting concepts for inclusion in a final concept hierarchy. The utility of the approach is demonstrated by reviewing its inclusion in the implementation of a recommender system. This recommender system serves as the final contribution featuring a unique design where lattices represent user profiles and concepts in these profiles are pruned using the Collapse Index. Results showed that pruning of profile lattices enabled by the Collapse Index improved the success levels of movie recommendations if the appropriate thresholds are set.
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Kasemsri, Rawiroj Robert. "A Survey, Taxonomy, and Analysis of Network Security Visualization Techniques." Digital Archive @ GSU, 2006. http://digitalarchive.gsu.edu/cs_theses/17.

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Network security visualization is a relatively new field and is quickly gaining momentum. Network security visualization allows the display and projection of the network or system data, in hope to efficiently monitor and protect the system from any intrusions or possible attacks. Intrusions and attacks are constantly continuing to increase in number, size, and complexity. Textually reading through log files or other textual sources is currently insufficient to secure a network or system. Using graphical visualization, security information is presented visually, and not only by text. Without network security visualization, reading through log files or other textual sources is an endless and aggravating task for network security analysts. Visualization provides a method of displaying large volume of information in a relatively small space. It also makes patterns easier to detect, recognize, and analyze. This can help security experts to detect problems that may otherwise be missed in reading text based log files. Network security visualization has become an active research field in the past six years and a large number of visualization techniques have been proposed. A comprehensive analysis of the existing techniques is needed to help network security designers make informed decisions about the appropriate visualization techniques under various circumstances. Moreover, a taxonomy of the existing visualization techniques is needed to classify the existing network security visualization techniques and present a high level overview of the field. In this thesis, the author surveyed the field of network security visualization. Specifically, the author analyzed the network security visualization techniques from the perspective of data model, visual primitives, security analysis tasks, user interaction, and other design issues. Various statistics were generated from the literatures. Based on this analysis, the author has attempted to generate useful guidelines and principles for designing effective network security visualization techniques. The author also proposed a taxonomy for the security visualization techniques. To the author’s knowledge, this is the first attempt to generate a taxonomy for network security visualization. Finally, the author evaluated the existing network security visualization techniques and discussed their characteristics and limitations. For future research, the author also discussed some open research problems in this field. This research is a step towards a thorough analysis of the problem space and the solution space in network security visualization.
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Alkhaldi, Rawan. "Spatial data transmission security authentication of spatial data using a new temporal taxonomy /." abstract and full text PDF (free order & download UNR users only), 2005. http://0-gateway.proquest.com.innopac.library.unr.edu/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqdiss&rft_dat=xri:pqdiss:1433280.

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Weng, Li-Tung. "Information enrichment for quality recommender systems." Thesis, Queensland University of Technology, 2008. https://eprints.qut.edu.au/29165/1/Li-Tung_Weng_Citation.pdf.

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The explosive growth of the World-Wide-Web and the emergence of ecommerce are the major two factors that have led to the development of recommender systems (Resnick and Varian, 1997). The main task of recommender systems is to learn from users and recommend items (e.g. information, products or books) that match the users’ personal preferences. Recommender systems have been an active research area for more than a decade. Many different techniques and systems with distinct strengths have been developed to generate better quality recommendations. One of the main factors that affect recommenders’ recommendation quality is the amount of information resources that are available to the recommenders. The main feature of the recommender systems is their ability to make personalised recommendations for different individuals. However, for many ecommerce sites, it is difficult for them to obtain sufficient knowledge about their users. Hence, the recommendations they provided to their users are often poor and not personalised. This information insufficiency problem is commonly referred to as the cold-start problem. Most existing research on recommender systems focus on developing techniques to better utilise the available information resources to achieve better recommendation quality. However, while the amount of available data and information remains insufficient, these techniques can only provide limited improvements to the overall recommendation quality. In this thesis, a novel and intuitive approach towards improving recommendation quality and alleviating the cold-start problem is attempted. This approach is enriching the information resources. It can be easily observed that when there is sufficient information and knowledge base to support recommendation making, even the simplest recommender systems can outperform the sophisticated ones with limited information resources. Two possible strategies are suggested in this thesis to achieve the proposed information enrichment for recommenders: • The first strategy suggests that information resources can be enriched by considering other information or data facets. Specifically, a taxonomy-based recommender, Hybrid Taxonomy Recommender (HTR), is presented in this thesis. HTR exploits the relationship between users’ taxonomic preferences and item preferences from the combination of the widely available product taxonomic information and the existing user rating data, and it then utilises this taxonomic preference to item preference relation to generate high quality recommendations. • The second strategy suggests that information resources can be enriched simply by obtaining information resources from other parties. In this thesis, a distributed recommender framework, Ecommerce-oriented Distributed Recommender System (EDRS), is proposed. The proposed EDRS allows multiple recommenders from different parties (i.e. organisations or ecommerce sites) to share recommendations and information resources with each other in order to improve their recommendation quality. Based on the results obtained from the experiments conducted in this thesis, the proposed systems and techniques have achieved great improvement in both making quality recommendations and alleviating the cold-start problem.
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Weng, Li-Tung. "Information enrichment for quality recommender systems." Queensland University of Technology, 2008. http://eprints.qut.edu.au/29165/.

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The explosive growth of the World-Wide-Web and the emergence of ecommerce are the major two factors that have led to the development of recommender systems (Resnick and Varian, 1997). The main task of recommender systems is to learn from users and recommend items (e.g. information, products or books) that match the users’ personal preferences. Recommender systems have been an active research area for more than a decade. Many different techniques and systems with distinct strengths have been developed to generate better quality recommendations. One of the main factors that affect recommenders’ recommendation quality is the amount of information resources that are available to the recommenders. The main feature of the recommender systems is their ability to make personalised recommendations for different individuals. However, for many ecommerce sites, it is difficult for them to obtain sufficient knowledge about their users. Hence, the recommendations they provided to their users are often poor and not personalised. This information insufficiency problem is commonly referred to as the cold-start problem. Most existing research on recommender systems focus on developing techniques to better utilise the available information resources to achieve better recommendation quality. However, while the amount of available data and information remains insufficient, these techniques can only provide limited improvements to the overall recommendation quality. In this thesis, a novel and intuitive approach towards improving recommendation quality and alleviating the cold-start problem is attempted. This approach is enriching the information resources. It can be easily observed that when there is sufficient information and knowledge base to support recommendation making, even the simplest recommender systems can outperform the sophisticated ones with limited information resources. Two possible strategies are suggested in this thesis to achieve the proposed information enrichment for recommenders: • The first strategy suggests that information resources can be enriched by considering other information or data facets. Specifically, a taxonomy-based recommender, Hybrid Taxonomy Recommender (HTR), is presented in this thesis. HTR exploits the relationship between users’ taxonomic preferences and item preferences from the combination of the widely available product taxonomic information and the existing user rating data, and it then utilises this taxonomic preference to item preference relation to generate high quality recommendations. • The second strategy suggests that information resources can be enriched simply by obtaining information resources from other parties. In this thesis, a distributed recommender framework, Ecommerce-oriented Distributed Recommender System (EDRS), is proposed. The proposed EDRS allows multiple recommenders from different parties (i.e. organisations or ecommerce sites) to share recommendations and information resources with each other in order to improve their recommendation quality. Based on the results obtained from the experiments conducted in this thesis, the proposed systems and techniques have achieved great improvement in both making quality recommendations and alleviating the cold-start problem.
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Costin, Aaron. "A new methodology for interoperability of heterogeneous bridge information models." Diss., Georgia Institute of Technology, 2016. http://hdl.handle.net/1853/55012.

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With the passing of the MAP-21 (Moving Ahead for Progress in the 21st Century) Act in 2012, the United States bridge industry has had a significant push for the use of innovative technologies to advance the highway transportation system. Bridge Information Modeling (BrIM) is emerging as an important trend in the industry, in which various technologies and software are being used in all phases of the bridge lifecycle and have been shown to have a variety of benefits. However, most software are stand alone applications and do not efficiently exchange data among other software. This lack of interoperability creates impediments for the efficient and seamless transfer of information across the bridge lifecycle. In recent years, the building industry developed standards to promote interoperability for Building Information Models (BIM). Unfortunately, these standards lack the ability to incorporate bridges. Therefore, there major need for a standard for Bridge Information Modeling (BrIM). Moreover, as technology and modeling software have been coming more prevalent in other domains (roads, geotechnical, environment systems, etc.) there is an even larger need to expand interoperability standards across multi-disciplinary domains. The purpose of this research is to develop a methodology that would enable the interoperability of multi-disciplinary information models. The scope of the methodology is for Bridge Information Models, but the approach is extendable to other domains. This research is motivated by the fundamental issues of interoperability, such as semantic, logic, and software issues. In this research, the fundamental issues of interoperability are investigated as well as an in-depth review of literature proposing solutions. Additionally, current standards for interoperability of information models are reviewed. Based on the findings of the literature review, this research develops, evaluates, and validates a novel methodology for interoperability of information models. The fundamental issues of interoperability are addressed by the use of a taxonomy and ontology. A new standardization process to capture domain knowledge, called in “Information Exchange Standard” is outlined along with a novel method of developing an ontology based on industry workflows. This methodology has been used and validated by an industry domain case study. A software tool to automate the capturing of domain knowledge and development of a taxonomy is presented.
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Books on the topic "Taxonomy information"

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Stone, Mark R. A new taxonomy of monetary regimes. [Washington D.C.]: International Monetary Fund, Monetary and Financial Systems Dept., 2004.

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Woods, William A. Understanding subsumption and taxonomy: A framework for progress. Cambridge, Mass: Harvard University, Center for Research in Computing Technology, Aiken Computer Laboratory, 1990.

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Toward precision medicine: Building a knowledge network for biomedical research and a new taxonomy of disease. Washington, D.C: National Academies Press, 2011.

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Hine, Christine. Systematics as cyberscience: Computers, change, and continuity in science. Cambridge, Mass: MIT Press, 2008.

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Watson, Leslie. Grass genera of the world: Illustrations of characters, descriptions, classification, interactive identification, information retrieval : with microfiches and floppy disks for MS-DOS microcomputers. Canberra: Australian National University, Research School of Biological Sciences, 1988.

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Mace, Emma Sian. Molecular, taxonomic and information technology studies in the Solanaceae. Birmingham: University of Birmingham, 1998.

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Rockmore, Marlene, Joseph Busch, Michael Lauruhn, and Ron Daniel. Art of Taxonomy: Creating Concept-Rich Services. O'Reilly Media, Incorporated, 2010.

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Ramzan, Naeem, and Heiko Angermann. Taxonomy Matching Using Background Knowledge: Linked Data, Semantic Web and Heterogeneous Repositories. Springer, 2018.

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Ramzan, Naeem, and Heiko Angermann. Taxonomy Matching Using Background Knowledge: Linked Data, Semantic Web and Heterogeneous Repositories. Springer, 2019.

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The Future of information architecture: Conceiving a better way to understand taxonomy, network, and intelligence. Oxford, England: Chandos Publishing, 2008.

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Book chapters on the topic "Taxonomy information"

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Atreya, C. D. "Application of genome sequence information in potyvirus taxonomy: an overview." In Potyvirus Taxonomy, 17–23. Vienna: Springer Vienna, 1992. http://dx.doi.org/10.1007/978-3-7091-6920-9_2.

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Drew, Richard A. I., and Meredith C. Romig. "Taxonomy." In The fruit fly fauna (Diptera: Tephritideae: Dacinae) of Papua New Guinea, Indonesian Papua, Associated Islands and Bougainville, 25–73. Wallingford: CABI, 2022. http://dx.doi.org/10.1079/9781789249514.0010.

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Bittner, Thomas, and Barry Smith. "A Taxonomy of Granular Partitions." In Spatial Information Theory, 28–43. Berlin, Heidelberg: Springer Berlin Heidelberg, 2001. http://dx.doi.org/10.1007/3-540-45424-1_3.

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Mashiane, Thulani, and Elmarie Kritzinger. "Cybersecurity Behaviour: A Conceptual Taxonomy." In Information Security Theory and Practice, 147–56. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-20074-9_11.

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Sindre, Guttorm. "Trust-Related Requirements: A Taxonomy." In Advances in Information Systems Development, 49–61. Boston, MA: Springer US, 2007. http://dx.doi.org/10.1007/978-0-387-70802-7_5.

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Zhou, Xujuan, Yuefeng Li, Peter Bruza, Yue Xu, and Raymond Y. K. Lau. "Pattern Taxonomy Mining for Information Filtering." In AI 2008: Advances in Artificial Intelligence, 416–22. Berlin, Heidelberg: Springer Berlin Heidelberg, 2008. http://dx.doi.org/10.1007/978-3-540-89378-3_42.

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Bielova, Nataliia, and Tamara Rezk. "A Taxonomy of Information Flow Monitors." In Lecture Notes in Computer Science, 46–67. Berlin, Heidelberg: Springer Berlin Heidelberg, 2016. http://dx.doi.org/10.1007/978-3-662-49635-0_3.

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Shearer, Rob, and Ian Horrocks. "Exploiting Partial Information in Taxonomy Construction." In Lecture Notes in Computer Science, 569–84. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-04930-9_36.

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Vidacic, Tomislav, and Vjeran Strahonja. "Taxonomy of Anomalies in Business Process Models." In Information System Development, 283–94. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-07215-9_23.

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Magnier-Watanabe, Remy. "A Practical Taxonomy of Knowledge." In Communications in Computer and Information Science, 23–29. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-81635-3_2.

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Conference papers on the topic "Taxonomy information"

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Tzitzikas, Yannis, and Anastasia Analyti. "Faceted Taxonomy-based Information Management." In 18th International Conference on Database and Expert Systems Applications (DEXA 2007). IEEE, 2007. http://dx.doi.org/10.1109/dexa.2007.27.

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Tzitzikas, Yannis, and Anastasia Analyti. "Faceted Taxonomy-based Information Management." In 18th International Conference on Database and Expert Systems Applications (DEXA 2007). IEEE, 2007. http://dx.doi.org/10.1109/dexa.2007.4312887.

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Zhang, Xia, Xu Chen, and Qin Zhan. "Study on Geographic Information Services Taxonomy." In 2009 Fourth International Conference on Computer Sciences and Convergence Information Technology. IEEE, 2009. http://dx.doi.org/10.1109/iccit.2009.136.

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Pousman, Zachary, and John Stasko. "A taxonomy of ambient information systems." In the working conference. New York, New York, USA: ACM Press, 2006. http://dx.doi.org/10.1145/1133265.1133277.

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Lemieux, Victoria, Barbara Endicott-Popovsky, Karl Eckler, Thomas Dang, and Adam Jansen. "Visualizing an information assurance risk taxonomy." In 2011 IEEE Conference on Visual Analytics Science and Technology (VAST). IEEE, 2011. http://dx.doi.org/10.1109/vast.2011.6102477.

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Yamada, Ichiro, Chikara Hashimoto, Jong-Hoon Oh, Kentaro Torisawa, Kow Kurod, Stijn De Saeger, Masaaki Tsuchida, and Jun'ichi Kazama. "Generating information-rich taxonomy from Wikipedia." In 2010 4th International Universal Communication Symposium (IUCS). IEEE, 2010. http://dx.doi.org/10.1109/iucs.2010.5666764.

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Miloslavskaya, Natalia, Alexander Tolstoy, and Sergey Zapechnikov. "Taxonomy for unsecure digital information processing." In 2016 Third International Conference on Digital Information Processing, Data Mining, and Wireless Communications (DIPDMWC). IEEE, 2016. http://dx.doi.org/10.1109/dipdmwc.2016.7529368.

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Griazev, Kiril, and Simona Ramanauskaite. "Web mining taxonomy." In 2018 Open Conference of Electrical, Electronic and Information Sciences (eStream). IEEE, 2018. http://dx.doi.org/10.1109/estream.2018.8394124.

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"B2B AUTOMATIC TAXONOMY CONSTRUCTION." In 10th International Conference on Enterprise Information Systems. SciTePress - Science and and Technology Publications, 2008. http://dx.doi.org/10.5220/0001702903250330.

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Kovalenko, Oleksii. "Information Taxonomy and Ontology for Situational Management." In 2018 IEEE 13th International Scientific and Technical Conference on Computer Sciences and Information Technologies (CSIT). IEEE, 2018. http://dx.doi.org/10.1109/stc-csit.2018.8526723.

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Reports on the topic "Taxonomy information"

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Altamirano, Álvaro, and Nicole Amaral. A Skills Taxonomy for LAC: Lessons Learned and a Roadmap for Future Users. Inter-American Development Bank, November 2020. http://dx.doi.org/10.18235/0002898.

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This note brings together lessons from the IDBs and other institutions efforts to adapt a skills taxonomy for Latin America and the Caribbean countries. These efforts have focused primarily on the ability to gather and make use of labor market information on skills demand from non-traditional data sources like online job vacancies. Most of these efforts have used the European Skills, Competences, Qualifications and Occupations (ESCO) taxonomy to underpin the identification and classification of skills. This note is intended to be a starting point and set of considerations for policymakers who may be considering, or already embarking on, similar efforts to use ESCO or other taxonomical structures to help better analyze, understand and use skills-level information for decision making. It also seeks to motivate the need for additional classification systems that help governments take stock of its citizens skills in increasingly complex and rapidly changing labor markets.
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Ben-Dov, Yair, Douglass R. Miller, G. Gibson, M. Kosztarab, and K. Veilleux. Computerized Synthesis of Information on the Scale Insects of the World. United States Department of Agriculture, August 2000. http://dx.doi.org/10.32747/2000.7573991.bard.

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Systematic information on all aspects of agriculture is a significant tool in finding solutions to various problems. This project was initiated to develop a searchable database on taxonomy, host plants, geographic distribution, economic importance and control of scale insects (Hemiptera: Coccoidea). A systematic database has been developed for 17 families of scale insects, namely, Aclerdidae, Asterolecaniidae, Beesoniidae, Carayonemidae, Cerococcidae, Coccidae, Conchaspididae, Dactylopiidae, Eriococcidae, Halimococcidae, Kerriidae, Lecanodiaspididae, Micrococcidae, Ortheziidae, Phenacoleachiidae, Phoenicococcidae and Pseudococcidae. These databases are now available on the Internet in ScaleNet - A Searchable Information System on Scale Insects - a Systematic Database of the Scale Insects of the World, (URL: http://www.sel.barc.usda.gov/scalenet/scalenet.htm ). Since 1997, the year in which ScaleNet was first placed on the Internet, this site became the best worldwide source of information on scale insects. The most reliable evaluation is that the site was 'visited' during 1999 by more than 50,000 users. Messages from the clientele of the site clearly indicate that it is widely used by researchers, applied entomologists, quarantine officers, students as well as the general public.
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Montgomery, Doug, Mark Carson, Timothy Winters, Michayla Newcombe, and Timothy Carlin. USGv6 Profile. National Institute of Standards and Technology, November 2020. http://dx.doi.org/10.6028/nist.sp.500-267br1.

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This profile establishes a basic taxonomy of IPv6 capabilities, defined in terms of IETF specifications, resulting in specific capability labels for common network functions and usage scenarios. The profile maps each such labeled capability to one or more specific technical specifications, or parts of specifications. Each labeled capability adopts by reference the normative requirements of the cited specifications. In rare cases the profile may augment or modify the normative requirements of a base specification. The defined capability labels effectively form a vocabulary for expressing IPv6 requirements for, and documenting the IPv6 capabilities of, specific products. It is expected that this profile, when combined with the USGv6 Test Program, can facilitate the efficient adoption of IPv6 technologies in Federal information systems.
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Shapovalov, Yevhenii B., Viktor B. Shapovalov, Roman A. Tarasenko, Stanislav A. Usenko, and Adrian Paschke. A semantic structuring of educational research using ontologies. [б. в.], June 2021. http://dx.doi.org/10.31812/123456789/4433.

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This article is devoted to the presentation of the semantic interoperability of research and scientific results through an ontological taxonomy. To achieve this, the principles of systematization and structuration of the scientific/research results in scientometrics databases have been analysed. We use the existing cognitive IT platform Polyhedron and extend it with an ontology-based information model as main contribution. As a proof-of-concept we have modelled two ontological graphs, “Development of a rational way for utilization of methane tank waste at LLC Vasylkivska poultry farm” and “Development a method for utilization of methane tank effluent”. Also, for a demonstration of the perspective of ontological systems for a systematization of research and scientific results, the “Hypothesis test system” ontological graph has created.
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Furey, John, Austin Davis, and Jennifer Seiter-Moser. Natural language indexing for pedoinformatics. Engineer Research and Development Center (U.S.), September 2021. http://dx.doi.org/10.21079/11681/41960.

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The multiple schema for the classification of soils rely on differing criteria but the major soil science systems, including the United States Department of Agriculture (USDA) and the international harmonized World Reference Base for Soil Resources soil classification systems, are primarily based on inferred pedogenesis. Largely these classifications are compiled from individual observations of soil characteristics within soil profiles, and the vast majority of this pedologic information is contained in nonquantitative text descriptions. We present initial text mining analyses of parsed text in the digitally available USDA soil taxonomy documentation and the Soil Survey Geographic database. Previous research has shown that latent information structure can be extracted from scientific literature using Natural Language Processing techniques, and we show that this latent information can be used to expedite query performance by using syntactic elements and part-of-speech tags as indices. Technical vocabulary often poses a text mining challenge due to the rarity of its diction in the broader context. We introduce an extension to the common English vocabulary that allows for nearly-complete indexing of USDA Soil Series Descriptions.
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Murphy, Joe J., Michael A. Duprey, Robert F. Chew, Paul P. Biemer, Kathleen Mullan Harris, and Carolyn Tucker Halpern. Interactive Visualization to Facilitate Monitoring Longitudinal Survey Data and Paradata. RTI Press, May 2019. http://dx.doi.org/10.3768/rtipress.2019.op.0061.1905.

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Surveys often require monitoring during data collection to ensure progress in meeting goals or to evaluate the interim results of an embedded experiment. Under complex designs, the amount of data available to monitor may be overwhelming and the production of reports and charts can be costly and time consuming. This is especially true in the case of longitudinal surveys, where data may originate from multiple waves. Other such complex scenarios include adaptive and responsive designs, which were developed to act on the results of such monitoring to implement prespecified options or alternatives in protocols. This paper discusses the development of an interactive web-based data visualization tool, the Adaptive Total Design (ATD) Dashboard, which we designed to provide a wide array of survey staff with the information needed to monitor data collection daily. The dashboard was built using the R programming language and Shiny framework and provides users with a wide range of functionality to quickly assess trends. We present the structure of the data used to populate the dashboard, its design, and the process for hosting it on the web. Furthermore, we provide guidance on graphic design, data taxonomy, and software decisions that can help guide others in the process of developing their own data collection monitoring systems. To illustrate the benefits of the dashboard, we present examples from the National Longitudinal Study of Adolescent to Adult Health (Add Health). We also discuss features of the dashboard to be developed for future waves of Add Health.
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Semerikov, Serhiy, Illia Teplytskyi, Yuliia Yechkalo, Oksana Markova, Vladimir Soloviev, and Arnold Kiv. Computer Simulation of Neural Networks Using Spreadsheets: Dr. Anderson, Welcome Back. [б. в.], June 2019. http://dx.doi.org/10.31812/123456789/3178.

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The authors of the given article continue the series presented by the 2018 paper “Computer Simulation of Neural Networks Using Spreadsheets: The Dawn of the Age of Camelot”. This time, they consider mathematical informatics as the basis of higher engineering education fundamentalization. Mathematical informatics deals with smart simulation, information security, long-term data storage and big data management, artificial intelligence systems, etc. The authors suggest studying basic principles of mathematical informatics by applying cloud-oriented means of various levels including those traditionally considered supplementary – spreadsheets. The article considers ways of building neural network models in cloud-oriented spreadsheets, Google Sheets. The model is based on the problem of classifying multi-dimensional data provided in “The Use of Multiple Measurements in Taxonomic Problems” by R. A. Fisher. Edgar Anderson’s role in collecting and preparing the data in the 1920s-1930s is discussed as well as some peculiarities of data selection. There are presented data on the method of multi-dimensional data presentation in the form of an ideograph developed by Anderson and considered one of the first efficient ways of data visualization.
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Wells, Aaron, Tracy Christopherson, Gerald Frost, Matthew Macander, Susan Ives, Robert McNown, and Erin Johnson. Ecological land survey and soils inventory for Katmai National Park and Preserve, 2016–2017. National Park Service, September 2021. http://dx.doi.org/10.36967/nrr-2287466.

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This study was conducted to inventory, classify, and map soils and vegetation within the ecosystems of Katmai National Park and Preserve (KATM) using an ecological land survey (ELS) approach. The ecosystem classes identified in the ELS effort were mapped across the park, using an archive of Geo-graphic Information System (GIS) and Remote Sensing (RS) datasets pertaining to land cover, topography, surficial geology, and glacial history. The description and mapping of the landform-vegetation-soil relationships identified in the ELS work provides tools to support the design and implementation of future field- and RS-based studies, facilitates further analysis and contextualization of existing data, and will help inform natural resource management decisions. We collected information on the geomorphic, topographic, hydrologic, pedologic, and vegetation characteristics of ecosystems using a dataset of 724 field plots, of which 407 were sampled by ABR, Inc.—Environmental Research and Services (ABR) staff in 2016–2017, and 317 were from existing, ancillary datasets. ABR field plots were located along transects that were selected using a gradient-direct sampling scheme (Austin and Heligers 1989) to collect data for the range of ecological conditions present within KATM, and to provide the data needed to interpret ecosystem and soils development. The field plot dataset encompassed all of the major environmental gradients and landscape histories present in KATM. Individual state-factors (e.g., soil pH, slope aspect) and other ecosystem components (e.g., geomorphic unit, vegetation species composition and structure) were measured or categorized using standard classification systems developed for Alaska. We described and analyzed the hierarchical relationships among the ecosystem components to classify 92 Plot Ecotypes (local-scale ecosystems) that best partitioned the variation in soils, vegetation, and disturbance properties observed at the field plots. From the 92 Plot Ecotypes, we developed classifications of Map Ecotypes and Disturbance Landscapes that could be mapped across the park. Additionally, using an existing surficial geology map for KATM, we developed a map of Generalized Soil Texture by aggregating similar surficial geology classes into a reduced set of classes representing the predominant soil textures in each. We then intersected the Ecotype map with the General-ized Soil Texture Map in a GIS and aggregated combinations of Map Ecotypes with similar soils to derive and map Soil Landscapes and Soil Great Groups. The classification of Great Groups captures information on the soil as a whole, as opposed to the subgroup classification which focuses on the properties of specific horizons (Soil Survey Staff 1999). Of the 724 plots included in the Ecotype analysis, sufficient soils data for classifying soil subgroups was available for 467 plots. Soils from 8 orders of soil taxonomy were encountered during the field sampling: Alfisols (<1% of the mapped area), Andisols (3%), Entisols (45%), Gelisols (<1%), Histosols (12%), Inceptisols (22%), Mollisols (<1%), and Spodosols (16%). Within these 8 Soil Orders, field plots corresponded to a total of 74 Soil Subgroups, the most common of which were Typic Cryaquents, Typic Cryorthents, Histic Cryaquepts, Vitrandic Cryorthents, and Typic Cryofluvents.
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Neeley, Aimee, Stace E. Beaulieu, Chris Proctor, Ivona Cetinić, Joe Futrelle, Inia Soto Ramos, Heidi M. Sosik, et al. Standards and practices for reporting plankton and other particle observations from images. Woods Hole Oceanographic Institution, July 2021. http://dx.doi.org/10.1575/1912/27377.

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This technical manual guides the user through the process of creating a data table for the submission of taxonomic and morphological information for plankton and other particles from images to a repository. Guidance is provided to produce documentation that should accompany the submission of plankton and other particle data to a repository, describes data collection and processing techniques, and outlines the creation of a data file. Field names include scientificName that represents the lowest level taxonomic classification (e.g., genus if not certain of species, family if not certain of genus) and scientificNameID, the unique identifier from a reference database such as the World Register of Marine Species or AlgaeBase. The data table described here includes the field names associatedMedia, scientificName/ scientificNameID for both automated and manual identification, biovolume, area_cross_section, length_representation and width_representation. Additional steps that instruct the user on how to format their data for a submission to the Ocean Biodiversity Information System (OBIS) are also included. Examples of documentation and data files are provided for the user to follow. The documentation requirements and data table format are approved by both NASA’s SeaWiFS Bio-optical Archive and Storage System (SeaBASS) and the National Science Foundation’s Biological and Chemical Oceanography Data Management Office (BCO-DMO).
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Jordan, Ramon L., Abed Gera, Hei-Ti Hsu, Andre Franck, and Gad Loebenstein. Detection and Diagnosis of Virus Diseases of Pelargonium. United States Department of Agriculture, July 1994. http://dx.doi.org/10.32747/1994.7568793.bard.

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Pelargonium (Geranium) is the number one pot plant in many areas of the United States and Europe. Israel and the U.S. send to Europe rooted cuttings, foundation stocks and finished plants to supply a certain share of the market. Geraniums are propagated mainly vegetatively from cuttings. Consequently, viral diseases have been and remain a major threat to the production and quality of the crop. Among the viruses isolated from naturally infected geraniums, 11 are not specific to Pelargonium and occur in other crops while 6 other viruses seem to be limited to geranium. However, several of these viruses are not sufficiently characterized to conclude that they are distinct agents and their nomenclature and taxonomy are confusing. The ability to separate, distinguish and detect the different viruses in geranium will overcome obstacles te developing effective detection and certification schemes. Our focus was to further characterize some of these viruses and develop better methods for their detection and control. These viruses include: isolates of pelargonium line pattern virus (PLPV), pelargonium ringspot virus (PelRSV), pelargonium flower break virus (PFBV), pelargonium leaf curl (PLCV), and tomato ringspot virus (TomRSV). Twelve hybridoma cell lines secreting monoclonal antibodies specific to a geranium isolate of TomRSV were produced. These antibodies are currently being characterized and will be tested for the ability to detect TomRSV in infected geraniums. The biological, biochemical and serological properties of four isometric viruses - PLPV, PelRSV, and PFBV (and a PelRSV-like isolate from Italy called GR57) isolated from geraniums exhibiting line and ring pattern or flower break symptoms - and an isolate ol elderbeny latent virus (ELV; which the literature indicates is the same as PelRSV) have been determined Cloned cDNA copies of the genomic RNAs of these viruses were sequenced and the sizes and locations of predicted viral proteins deduced. A portion of the putative replicase genes was also sequenced from cloned RT-PCR fragments. We have shown that, when compared to the published biochemical and serological properties, and sequences and genome organizations of other small isometric plant viruses, all of these viruses should each be considered new, distinct members of the Carmovirus group of the family Tombusviridae. Hybridization assays using recombinant DNA probes also demonstrated that PLPV, PelRSV, and ELV produce only one subgenomic RNA in infected plants. This unusual property of the gene expression of these three viruses suggests that they are unique among the Carmoviruses. The development of new technologies for the detection of these viruses in geranium was also demonstrated. Hybridization probes developed to PFBV (radioactively-labeled cRNA riboprobes) and to PLPV (non-radioactive digoxigenin-labeled cDNAs) were generally shown to be no more sensitive for the detection of virus in infected plants than the standard ELISA serology-based assays. However, a reverse transcriptase-polymerase chain reaction assay was shown to be over 1000 times more sensitive in detecting PFBV in leaf extracts of infected geranium than was ELISA. This research has lead to a better understanding of the identity of the viruses infecting pelargonium and to the development of new tools that can be used in an improved scheme of providing virus-indexed pelargonium plants. The sequence information, and the serological and cloned DNA probes generated from this work, will allow the application of these new tools for virus detection, which will be useful in domestic and international indexing programs which are essential for the production of virus-free germplasm both for domestic markets and the international exchange of plant material.
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