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{{For|the branch of biology|Taxonomy (biology)}}
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{{Redirect|Scientific classification}}
{{Information science}}

'''Taxonomy''' is the practice and science of [[categorization]] or [[classification (general theory)|classification]].

A taxonomy (or taxonomical classification) is a scheme of classification, especially a [[hierarchical classification]], in which things are organized into groups or types. Among other things, a taxonomy can be used to organize and index knowledge (stored as documents, articles, videos, etc.), such as in the form of a [[library classification system]], or a [[Taxonomy for search engines|search engine taxonomy]], so that users can more easily find the information they are searching for. Many taxonomies are [[hierarchy|hierarchies]] (and thus, have an intrinsic [[tree structure]]), but not all are.

Originally, taxonomy referred only to the categorisation of organisms or a particular categorisation of organisms. In a wider, more general sense, it may refer to a categorisation of things or concepts, as well as to the principles underlying such a categorisation. Taxonomy organizes taxonomic units known as "taxa" (singular "taxon")."

Taxonomy is different from [[meronomy]], which deals with the categorisation of parts of a whole.

== Etymology ==
The word was coined in 1813 by the Swiss botanist [[Augustin Pyramus de Candolle|A. P. de Candolle]] and is irregularly compounded from the [[Greek language|Greek]] {{Lang|grc|τάξις}}, ''taxis'' 'order' and {{Lang|grc|νόμος}}, ''nomos'' 'law', connected by the French form {{Nowrap|''-o-''}}; the regular form would be ''{{not a typo|taxinomy}}'', as used in the Greek [[reborrowing]] {{Lang|el|ταξινομία}}.<ref>{{Cite book |title=Oxford English Dictionary |publisher=Oxford University Press |year=1910}} (partially updated December 2021), [https://www.oed.com/view/Entry/198292 ''s.v.'']</ref><ref>review of ''Aperçus de Taxinomie Générale'' in ''Nature'' '''60''':[https://www.nature.com/articles/060489b0 489–490] {{Webarchive|url=https://web.archive.org/web/20230126084203/https://www.nature.com/articles/060489b0 |date=2023-01-26 }} (1899)</ref>

==Applications==
Wikipedia categories form a taxonomy,<ref>Zirn, Cäcilia, Vivi Nastase and Michael Strube. 2008. [http://webarchive.nationalarchives.gov.uk/20140111074556/http://www.h%2Dits.org/english/research/nlp/papers/zirn08.pdf "Distinguishing Between Instances and Classes in the Wikipedia Taxonomy"] [http://videolectures.net/eswc08_zirn_dbi/ (video lecture).] {{Webarchive|url=https://web.archive.org/web/20191220123127/https://webarchive.nationalarchives.gov.uk/20140111074556/http://www.h-its.org/english/research/nlp/papers/zirn08.pdf |date=2019-12-20 }} 5th Annual [[European Semantic Web Conference]] (ESWC 2008).</ref> which can be extracted by automatic means.<ref>S. Ponzetto and M. Strube. 2007. [https://www.aaai.org/Papers/AAAI/2007/AAAI07-228.pdf "Deriving a large scale taxonomy from Wikipedia"] {{Webarchive|url=https://web.archive.org/web/20170814042325/http://www.aaai.org/Papers/AAAI/2007/AAAI07-228.pdf |date=2017-08-14 }}. Proc. of the 22nd Conference on the Advancement of Artificial Intelligence, Vancouver, B.C., Canada, pp. 1440–1445.</ref> {{As of|2009}}, it has been shown that a manually-constructed taxonomy, such as that of computational lexicons like [[WordNet]], can be used to improve and restructure the Wikipedia category taxonomy.<ref>S. Ponzetto, R. Navigli. 2009. [https://web.archive.org/web/20110715113552/http://ijcai.org/papers09/Papers/IJCAI09-343.pdf "Large-Scale Taxonomy Mapping for Restructuring and Integrating Wikipedia"]. Proc. of the 21st International Joint Conference on Artificial Intelligence (IJCAI 2009), Pasadena, California, pp. 2083–2088.</ref>

In a broader sense, taxonomy also applies to relationship schemes other than parent-child hierarchies, such as [[Network (mathematics)|network structure]]s. Taxonomies may then include a single child with multi-parents, for example, "Car" might appear with both parents "Vehicle" and "Steel Mechanisms"; to some however, this merely means that 'car' is a part of several different taxonomies.<ref>Jackson, Joab. [http://gcn.com/Articles/2004/02/03/Taxonomys-not-just-design-its-an-art.aspx?Page=1&p=1 "Taxonomy's not just design, it's an art,"] {{Webarchive|url=https://web.archive.org/web/20200205130201/https://gcn.com/articles/2004/02/03/taxonomys-not-just-design-its-an-art.aspx |date=2020-02-05 }} ''Government Computer News'' (Washington, D.C.). September 2, 2004.</ref> A taxonomy might also simply be organization of kinds of things into groups, or an alphabetical list; here, however, the term vocabulary is more appropriate. In current usage within [[knowledge management]], taxonomies are considered narrower than [[ontology (computer science)|ontologies]] since ontologies apply a larger variety of relation types.<ref>Suryanto, Hendra and Paul Compton. [http://ol2000.aifb.uni-karlsruhe.de/final/HSuryanto_5.pdf "Learning classification taxonomies from a classification knowledge based system."] {{Webarchive|url=https://web.archive.org/web/20170809021830/http://ol2000.aifb.uni-karlsruhe.de/final/HSuryanto_5.pdf |date=2017-08-09 }} [[University of Karlsruhe]]; [http://www.greenchameleon.com/gc/blog_detail/defining_taxonomy/ "Defining 'Taxonomy',"] {{Webarchive|url=https://web.archive.org/web/20170809021830/http://ol2000.aifb.uni-karlsruhe.de/final/HSuryanto_5.pdf |date=2017-08-09 }} Straights Knowledge website.</ref>

Mathematically, a hierarchical taxonomy is a [[tree structure]] of classifications for a given set of objects. It is also named [[containment hierarchy]]. At the top of this structure is a single classification, the root node, that applies to all objects. Nodes below this root are more specific classifications that apply to subsets of the total set of classified objects. The progress of reasoning proceeds from the general to the more specific.

By contrast, in the context of legal terminology, an open-ended contextual taxonomy is employed—a taxonomy holding only with respect to a specific context. In scenarios taken from the legal domain, a formal account of the open-texture of legal terms is modeled, which suggests varying notions of the "core" and "penumbra" of the meanings of a concept. The progress of reasoning proceeds from the specific to the more general.<ref>Grossi, Davide, [[Frank Dignum]] and John-Jules Charles Meyer. (2005). [http://www.springerlink.com/content/9yj2lfa5cy67c78m/fulltext.pdf?page=1 "Contextual Taxonomies" in ''Computational Logic in Multi-Agent Systems,'' pp. 33–51]{{dead link|date=February 2020|bot=medic}}{{cbignore|bot=medic}}.</ref>

==History==
[[cultural anthropology|Anthropologists]] have observed that taxonomies are generally embedded in local cultural and social systems, and serve various social functions. Perhaps the most well-known and influential study of [[folk taxonomy|folk taxonomies]] is [[Émile Durkheim]]'s ''[[The Elementary Forms of Religious Life]]''. A more recent treatment of folk taxonomies (including the results of several decades of empirical research) and the discussion of their relation to the scientific taxonomy can be found in [[Scott Atran]]'s ''Cognitive Foundations of Natural History.'' Folk taxonomies of organisms have been found in large part to agree with scientific classification, at least for the larger and more obvious species, which means that it is not the case that folk taxonomies are based purely on utilitarian characteristics.<ref>{{cite book|title=Evolution, Order and Complexity|author1=Kenneth Boulding |author2=Elias Khalil |publisher=Routledge|year=2002|isbn=9780203013151|url=https://books.google.com/books?id=N-OUCDi8SS8C&q=Durkheim+folk+taxonomy}} p. 9</ref>

In the seventeenth century the German mathematician and philosopher [[Gottfried Leibniz]], following the work of the thirteenth-century Majorcan philosopher [[Ramon Llull]] on his ''[[Ars generalis ultima]]'', a system for procedurally generating concepts by combining a fixed set of ideas, sought to develop an [[alphabet of human thought]]. Leibniz intended his ''[[characteristica universalis]]'' to be an "algebra" capable of expressing all conceptual thought. The concept of creating such a "[[universal language]]" was frequently examined in the 17th century, also notably by the English philosopher [[John Wilkins]] in his work ''[[An Essay towards a Real Character and a Philosophical Language]]'' (1668), from which the classification scheme in [[Peter Mark Roget|Roget]]'s [[Thesaurus]] ultimately derives.

==Taxonomy in various disciplines==
===Natural sciences===
{{main|Taxonomy (biology)}}
Taxonomy in biology encompasses the description, identification, nomenclature, and classification of organisms. Uses of taxonomy include:
*[[Alpha taxonomy]], the description and basic classification of new species, subspecies, and other taxa
** [[Linnaean taxonomy]], the original classification scheme of Carl Linnaeus
** [[Taxonomic rank|rank-based]] scientific classification as opposed to clade-based classification
*[[Evolutionary taxonomy]], traditional post-Darwinian hierarchical biological classification
*[[Numerical taxonomy]], various taxonomic methods employing numeric algorithms
*[[Phenetics]], system for ordering species based on overall similarity
*[[Phylogenetics]], biological taxonomy based on putative ancestral descent of organisms
*[[Plant taxonomy]]
*[[Virus classification]], taxonomic system for viruses
*[[Folk taxonomy]], description and organization, by individuals or groups, of their own environments
*[[Nosology]], classification of diseases
*[[Soil classification]], systematic categorization of soils

===Business and economics===
Uses of taxonomy in business and economics include:
*[[Corporate taxonomy]], the hierarchical classification of entities of interest to an enterprise, organization or administration
*[[Economic taxonomy]], a system of classification for economic activity
**[[Global Industry Classification Standard]], an industry taxonomy developed by MSCI and Standard & Poor's (S&P)
**[[Industry Classification Benchmark]], an industry classification taxonomy launched by Dow Jones and FTSE
**[[International Standard Industrial Classification]] (ISIC), a United Nations system for classifying economic data
**[[North American Industry Classification System]] (NAICS), used in Canada, Mexico, and the United States of America
**[[Pavitt's Taxonomy]], classification of firms by their principal sources of innovation
**[[Standard Industrial Classification]], a system for classifying industries by a four-digit code
**[[United Kingdom Standard Industrial Classification of Economic Activities]], a Standard Industrial Classification by type of economic activity
*[[EU taxonomy for sustainable activities]], a classification system established to clarify which investments are environmentally sustainable, in the context of the [[European Green Deal]].
* [[Records management taxonomy]], the representation of data, upon which the classification of unstructured content is based, within an organization.
* [[XBRL Taxonomy]], eXtensible Business Reporting Language
* [[SRK taxonomy]], in workplace user-interface design

=== Computing ===
==== Software engineering ====
Vegas et al.<ref>{{cite journal|last1=Vegas|first1=S.|title=Maturing software engineering knowledge through classifications: A case study on unit testing techniques.|journal=IEEE Transactions on Software Engineering|date=2009|volume=35|issue=4|pages=551–565|doi=10.1109/TSE.2009.13|citeseerx=10.1.1.221.7589|s2cid=574495}}</ref> make a compelling case to advance the knowledge in the field of software engineering through the use of taxonomies. Similarly, Ore et al.<ref>{{cite journal|last1=Ore|first1=S.|title=Critical success factors taxonomy for software process deployment|journal=Software Quality Journal|date=2014|volume=22|issue=1|pages=21–48|doi=10.1007/s11219-012-9190-y|s2cid=18047921}}</ref> provide a systematic methodology to approach taxonomy building in software engineering related topics.

Several taxonomies have been proposed in software testing research to classify techniques, tools, concepts and artifacts. The following are some example taxonomies:
# A taxonomy of model-based testing techniques<ref>{{cite journal|last1=Utting|first1=Mark|title=A taxonomy of model-based testing approaches|journal=Software Testing, Verification & Reliability|date=2012|volume=22|issue=5|pages=297–312|doi=10.1002/stvr.456|s2cid=6782211|url=http://dl.acm.org/citation.cfm?id=2344870|access-date=2017-04-23|archive-date=2019-12-20|archive-url=https://web.archive.org/web/20191220123127/https://dl.acm.org/citation.cfm?id=2344870|url-status=live}}</ref>
# A taxonomy of static-code analysis tools<ref>{{cite journal|last1=Novak|first1=Jernej|title=Taxonomy of static code analysis tools|journal=Proceedings of the 33rd International Convention MIPRO|date=May 2010|pages=418–422|url=https://ieeexplore.ieee.org/document/5533417|access-date=2020-03-03|archive-date=2022-06-27|archive-url=https://web.archive.org/web/20220627160409/https://ieeexplore.ieee.org/document/5533417|url-status=live}}</ref>

Engström et al.<ref name="EngstromPAB16">{{cite journal|last1=Engström|first1=Emelie|title=SERP-test: a taxonomy for supporting industry–academia communication|journal=Software Quality Journal|volume=25|issue=4|date=2016|pages=1269–1305|doi=10.1007/s11219-016-9322-x|s2cid=34795073}}</ref> suggest and evaluate the use of a taxonomy to bridge the communication between researchers and practitioners engaged in the area of software testing. They have also developed a web-based tool<ref>{{cite web|url=https://serpconnect.readthedocs.io/en/latest/index.html|title=SERP-connect|access-date=2021-08-28|archive-date=2021-08-28|archive-url=https://web.archive.org/web/20210828133913/https://serpconnect.readthedocs.io/en/latest/index.html|url-status=live}}</ref> to facilitate and encourage the use of the taxonomy. The tool and its source code are available for public use.<ref>{{cite web|last1=Engstrom|first1=Emelie|url=https://github.com/emenlu/connect|title=SERP-connect backend|website=[[GitHub]]|date=4 December 2019|access-date=25 October 2016|archive-date=10 December 2019|archive-url=https://web.archive.org/web/20191210135856/https://github.com/emenlu/connect|url-status=live}}</ref>

====Other uses of taxonomy in computing====
*[[Flynn's taxonomy]], a classification for instruction-level parallelism methods
*[[Folksonomy]], classification based on user's tags
*[[Taxonomy for search engines]], considered as a tool to improve relevance of search within a vertical domain
*[[ACM Computing Classification System]], a subject classification system for computing devised by the Association for Computing Machinery

===Education and academia===
Uses of taxonomy in education include:
*[[Bloom's taxonomy]], a standardized categorization of learning objectives in an educational context
*[[Classification of Instructional Programs]], a taxonomy of academic disciplines at institutions of higher education in the United States
*[[Mathematics Subject Classification]], an alphanumerical classification scheme based on the coverage of Mathematical Reviews and Zentralblatt MATH
*[[SOLO taxonomy]], Structure of Observed Learning Outcome, proposed by Biggs and Collis Tax

===Safety===
Uses of taxonomy in safety include:
*[[Safety taxonomy]], a standardized set of terminologies used within the fields of safety and health care
**[[Human Factors Analysis and Classification System]], a system to identify the human causes of an accident
**[[Swiss cheese model]], a model used in risk analysis and risk management propounded by Dante Orlandella and James T. Reason
**A taxonomy of rail incidents in [[Confidential Incident Reporting & Analysis System]] (CIRAS)

===Other taxonomies===
*[[Military taxonomy]], a set of terms that describe various types of military operations and equipment
*[[Moys Classification Scheme]], a subject classification for law devised by Elizabeth Moys

=== Research publishing ===
Citing inadequacies with current practices in listing authors of papers in medical research journals, Drummond Rennie and co-authors called in a 1997 article in ''JAMA'', the ''[[Journal of the American Medical Association]]'' for
<blockquote>
''a radical conceptual and systematic change, to reflect the realities of multiple authorship and to buttress accountability. We propose dropping the outmoded notion of author in favor of the more useful and realistic one of contributor.''<ref name="CRediT">{{cite journal|author-link1=Amy Brand|author-link3=Micah Altman |last1=Brand |first1=Amy |last2=Allen |first2=Liz |last3=Altman |first3=Micah |last4=Hlava |first4=Marjorie |last5=Scott |first5=Jo |title=Beyond authorship: attribution, contribution, collaboration, and credit |journal=Learned Publishing |volume=28 |issue=2 |pages=151–155 |ref=CRediT |doi=10.1087/20150211|date=1 April 2015|s2cid=45167271 |doi-access=free }}</ref>{{rp|152}}
</blockquote>
Since 2012, several major academic and scientific publishing bodies have mounted ''Project CRediT'' to develop a [[controlled vocabulary]] of contributor roles.<ref name="CASRAI_CRediT">{{cite web |title=CRediT |url=http://docs.casrai.org/CRediT |website=CASRAI |publisher=[[CASRAI]] |access-date=13 June 2018 |ref=CASRAI_CRediT |format=online |date=2 May 2018 |archive-url=https://web.archive.org/web/20180612102958/http://docs.casrai.org/CRediT |archive-date=12 June 2018 |url-status=dead }}</ref> Known as ''[[CRediT]] (Contributor Roles Taxonomy)'', this is an example of a flat, non-hierarchical taxonomy; however, it does include an optional, broad classification of the degree of contribution: ''lead'', ''equal'' or ''supporting''. [[Amy Brand]] and co-authors summarise their intended outcome as:
<blockquote>
Identifying specific contributions to published research will lead to appropriate credit, fewer author disputes, and fewer disincentives to collaboration and the sharing of data and code.<ref name="CRediT" />{{rp|151}}
</blockquote>
As of mid-2018, this taxonomy apparently restricts its scope to ''research outputs'', specifically journal articles; however, it does rather unusually "hope to … support identification of peer reviewers".<ref name="CASRAI_CRediT" /> (As such, it has not yet defined terms for such roles as editor or author of a chapter in a ''book'' of research results.) Version 1, established by the first Working Group in the (northern) autumn of 2014, identifies 14 specific contributor roles using the following defined terms:
*Conceptualization
*Methodology
*Software
*Validation
*Formal Analysis
*Investigation
*Resources
*Data curation
*Writing – Original Draft
*Writing – Review & Editing
*Visualization
*Supervision
*Project Administration
*Funding acquisition

Reception has been mixed, with several major publishers and journals planning to have implemented CRediT by the end of 2018, whilst almost as many are not persuaded of the need or value of using it. For example,
<blockquote>
The [[National Academy of Sciences]] has created a ''TACS (Transparency in Author Contributions in Science)'' webpage to list the journals that commit to setting authorship standards, defining responsibilities for corresponding authors, requiring ORCID iDs, and adopting the CRediT taxonomy.<ref name="NAS_TACS">{{cite web |title=Transparency in Author Contributions in Science (TACS) |url=http://www.nasonline.org/publications/Transparency_Author_Contributions.html |website=National Academy of Sciences |access-date=13 June 2018 |ref=NAS_TACS |format=online |date=2018 |archive-date=19 May 2019 |archive-url=https://web.archive.org/web/20190519175553/http://www.nasonline.org/publications/Transparency_Author_Contributions.html |url-status=live }}</ref>
</blockquote>
The same webpage has a table listing 21 journals (or families of journals), of which:
* 5 have, or by end 2018 will have, implemented CRediT,
* 6 require an author contribution statement and suggest using CRediT,
* 8 do not use CRediT, of which 3 give reasons for not doing so, and
* 2 are uninformative.

The taxonomy is an open standard conforming to the [[OpenStand]] principles,<ref name="OpenStand">{{cite web |title=OpenStand |url=https://open-stand.org/about-us/principles/ |website=OpenStand |access-date=13 June 2018 |archive-date=18 September 2019 |archive-url=https://web.archive.org/web/20190918005111/https://open-stand.org/about-us/principles/ |url-status=live }}</ref> and is published under a [[Creative Commons]] licence.<ref name="CASRAI_CRediT" />

=== Taxonomy for the web ===
Websites with a well designed taxonomy or hierarchy are easily understood by users, due to the possibility of users developing a mental model of the site structure.<ref name=":0">{{Cite book|title=Information architecture for the World Wide Web|last=Peter.|first=Morville|date=2007|publisher=O'Reilly|others=Rosenfeld, Louis., Rosenfeld, Louis.|isbn=9780596527341|edition=3rd|location=Sebastopol, CA|oclc=86110226|url=https://archive.org/details/informationarchi00morv}}</ref>

Guidelines for writing taxonomy for the web include:

* Mutually exclusive categories can be beneficial. If categories appear several places, it's called cross-listing or polyhierarchical. The hierarchy will lose its value if cross-listing appears too often. Cross-listing often appears when working with ambiguous categories that fits more than one place.<ref name=":0" />
* Having a balance between breadth and depth in the taxonomy is beneficial. Too many options (breadth), will overload the users by giving them too many choices. At the same time having a too narrow structure, with more than two or three levels to click-through, will make users frustrated and might give up.<ref name=":0" />

== Is-a and has-a relationships, and hyponymy ==
{{Main|Is-a|Hyponymy}}

Two of the predominant types of relationships in [[Knowledge representation and reasoning|knowledge-representation]] systems are [[Predicate (mathematical logic)|predication]] and the universally quantified [[Indicative conditional|conditional]]. Predication relationships express the notion that an individual entity is an example of a certain type (for example, ''John is a bachelor''), while universally quantified conditionals express the notion that a type is a subtype of another type (for example, "''A dog is a mammal"'', which means the same as "''All dogs are mammals"'').<ref name="Brachman">[[Ronald J. Brachman]]; [http://dblp.uni-trier.de/rec/bibtex/journals/computer/Brachman83 What IS-A is and isn't. An Analysis of Taxonomic Links in Semantic Networks] {{Webarchive|url=https://web.archive.org/web/20200630035007/http://dblp.uni-trier.de/rec/bibtex/journals/computer/Brachman83 |date=2020-06-30 }}. IEEE Computer, 16 (10); October 1983.</ref>

The "has-a" relationship is quite different: an elephant ''has'' a trunk; a trunk is a part, not a subtype of elephant. The study of part-whole relationships is [[mereology]].

Taxonomies are often represented as [[Is-a|''is-a'' hierarchies]] where each level is more specific than the level above it (in mathematical language is "a subset of" the level above). For example, a basic biology taxonomy would have concepts such as ''mammal'', which is a subset of ''animal'', and ''dogs'' and ''cats'', which are subsets of ''mammal''. This kind of taxonomy is called an is-a model because the specific objects are considered as instances of a concept. For example, ''Fido'' is-an instance of the concept ''dog'' and ''Fluffy'' is-a ''cat''.<ref>{{cite journal|last1=Brachman|first1=Ronald|title=What IS-A is and isn't. An Analysis of Taxonomic Links in Semantic Networks|journal=IEEE Computer|date=October 1983|volume=16|issue=10|pages=30–36|doi=10.1109/MC.1983.1654194|s2cid=16650410}}</ref><br />

In [[linguistics]], is-a relations are called [[hyponymy]]. When one word describes a category, but another describe some subset of that category, the larger term is called a ''hypernym'' with respect to the smaller, and the smaller is called a "hyponym" with respect to the larger. Such a hyponym, in turn, may have further subcategories for which it is a hypernym. In the simple biology example, ''dog'' is a hypernym with respect to its subcategory ''collie'', which in turn is a hypernym with respect to ''Fido'' which is one of its hyponyms. Typically, however, ''hypernym'' is used to refer to subcategories rather than single individuals.

== Research ==
[[File:Larger populations promote category convergence across populations.webp|thumb|250px|Comparison of categories of small and large populations]]
Researchers reported that large populations consistently develop highly similar category systems. This may be relevant to lexical aspects of large communication networks and cultures such as [[folksonomy|folksonomies]] and [[linguistics|language]] or human communication, and sense-making in general.<ref name="phys-cattaxo">{{cite news |title=Why independent cultures think alike when it comes to categories: It's not in the brain |url=https://phys.org/news/2021-01-independent-cultures-alike-categories-brain.html |access-date=13 February 2021 |work=phys.org |language=en |archive-date=25 January 2021 |archive-url=https://web.archive.org/web/20210125212957/https://phys.org/news/2021-01-independent-cultures-alike-categories-brain.html |url-status=live }}</ref><ref>{{cite journal |last1=Guilbeault |first1=Douglas |last2=Baronchelli |first2=Andrea |last3=Centola |first3=Damon |title=Experimental evidence for scale-induced category convergence across populations |journal=Nature Communications |date=12 January 2021 |volume=12 |issue=1 |pages=327 |doi=10.1038/s41467-020-20037-y |pmid=33436581 |pmc=7804416 |bibcode=2021NatCo..12..327G |language=en |issn=2041-1723|doi-access=free }} [[File:CC-BY icon.svg|50px]] Available under [https://creativecommons.org/licenses/by/4.0/ CC BY 4.0] {{Webarchive|url=https://web.archive.org/web/20171016050101/https://creativecommons.org/licenses/by/4.0/ |date=2017-10-16 }}.</ref>

==See also==
* {{Intitle}}
* {{Wiktionary-inline|taxonomy}}
* {{Wiktionary-inline|classification scheme}}
* [[Categorization]], the process of dividing things into groups
* [[Classification (general theory)]]
* [[Celestial Emporium of Benevolent Recognition]], a fictional Chinese encyclopedia with an "impossible" taxonomic scheme
* [[Conflation]]
* [[Faceted classification]]
* [[Folksonomy]]
* [[Gellish English dictionary]], a taxonomy in which the concepts are arranged as a subtype–supertype hierarchy
* [[Hypernym]]
* [[Knowledge representation]]
* [[Lexicon]]
* [[Ontology (information science)]], formal representation of knowledge as a set of concepts within a domain
* [[Philosophical language]]
* [[Protégé (software)]]
* [[Semantic network]]
* [[Semantic similarity network]]
* [[Structuralism]]
* [[Systematics]]
* [[Taxon]], a population of organisms that a taxonomist adjudges to be a unit
* [[Taxonomy for search engines]]
* [[Thesaurus (information retrieval)]]
* [[Typology (disambiguation)]]

==Notes==
{{Reflist|30em}}

==References==
* Atran, S. (1993) ''Cognitive Foundations of Natural History: Towards an Anthropology of Science.'' Cambridge: [[Cambridge University Press]]. {{ISBN|978-0-521-43871-1}}
* Carbonell, J. G. and J. Siekmann, eds. (2005). [https://archive.today/20130105000444/http://www.springerlink.com/content/fb5lq38pu0c7/?p=55d6f2e6622046f5909b8b3d31994ddb&pi=0 ''Computational Logic in Multi-Agent Systems,'' Vol. 3487.] Berlin: [[Springer-Verlag]].{{ISBN|978-3-540-28060-6}}
* Malone, Joseph L. (1988). [https://books.google.com/books?id=PEY0U3umLRkC ''The Science of Linguistics in the Art of Translation: Some Tools from Linguistics for the Analysis and Practice of Translation.''] Albany, New York: [[State University of New York Press]]. {{ISBN|978-0-887-06653-5}}; [http://www.worldcat.org/wcpa/oclc/15856738 OCLC 15856738]
* *Marcello Sorce Keller, "The Problem of Classification in Folksong Research: a Short History", ''Folklore'', XCV(1984), no. 1, 100–104.
* Chester D Rowe and Stephen M Davis, 'The Excellence Engine Tool Kit'; {{ISBN|978-0-615-24850-9}}
* {{cite journal|author1=Härlin, M. |author2=Sundberg, P. |year=1998|title=Taxonomy and Philosophy of Names|journal=Biology and Philosophy|volume=13|issue=2|pages=233–244|doi=10.1023/a:1006583910214|s2cid=82878147 }}
* {{cite book|author1=Lamberts, K. |author2=Shanks, D.R. |year=1997|title=Knowledge, Concepts, and Categories|publisher=Psychology Press|isbn=9780863774911|url=https://books.google.com/books?id=mlYVAAAAIAAJ}}

==External links==
*{{Commons category-inline|Taxonomy}}
*{{Wiktionary-inline|taxonomy}}
* ''[http://www.kmworld.com/Articles/Editorial/What-Is/Taxonomy-101-The-Basics-and-Getting-Started-with-Taxonomies-98787.aspx Taxonomy 101: The Basics and Getting Started with Taxonomies]''

{{Authority control}}

[[Category:Taxonomy| ]]
[[Category:Scientific nomenclature]]
[[Category:Hierarchy]]
[[Category:Ontology]]

১৮:৪৮, ১ জানুয়ারি ২০২৪ তারিখে সংশোধিত সংস্করণ

Taxonomy is the practice and science of categorization or classification.

A taxonomy (or taxonomical classification) is a scheme of classification, especially a hierarchical classification, in which things are organized into groups or types. Among other things, a taxonomy can be used to organize and index knowledge (stored as documents, articles, videos, etc.), such as in the form of a library classification system, or a search engine taxonomy, so that users can more easily find the information they are searching for. Many taxonomies are hierarchies (and thus, have an intrinsic tree structure), but not all are.

Originally, taxonomy referred only to the categorisation of organisms or a particular categorisation of organisms. In a wider, more general sense, it may refer to a categorisation of things or concepts, as well as to the principles underlying such a categorisation. Taxonomy organizes taxonomic units known as "taxa" (singular "taxon")."

Taxonomy is different from meronomy, which deals with the categorisation of parts of a whole.

Etymology

The word was coined in 1813 by the Swiss botanist A. P. de Candolle and is irregularly compounded from the Greek τάξις, taxis 'order' and νόμος, nomos 'law', connected by the French form -o-; the regular form would be taxinomy, as used in the Greek reborrowing ταξινομία.[][]

Applications

Wikipedia categories form a taxonomy,[] which can be extracted by automatic means.[] ২০০৯-এর হিসাব অনুযায়ী, it has been shown that a manually-constructed taxonomy, such as that of computational lexicons like WordNet, can be used to improve and restructure the Wikipedia category taxonomy.[]

In a broader sense, taxonomy also applies to relationship schemes other than parent-child hierarchies, such as network structures. Taxonomies may then include a single child with multi-parents, for example, "Car" might appear with both parents "Vehicle" and "Steel Mechanisms"; to some however, this merely means that 'car' is a part of several different taxonomies.[] A taxonomy might also simply be organization of kinds of things into groups, or an alphabetical list; here, however, the term vocabulary is more appropriate. In current usage within knowledge management, taxonomies are considered narrower than ontologies since ontologies apply a larger variety of relation types.[]

Mathematically, a hierarchical taxonomy is a tree structure of classifications for a given set of objects. It is also named containment hierarchy. At the top of this structure is a single classification, the root node, that applies to all objects. Nodes below this root are more specific classifications that apply to subsets of the total set of classified objects. The progress of reasoning proceeds from the general to the more specific.

By contrast, in the context of legal terminology, an open-ended contextual taxonomy is employed—a taxonomy holding only with respect to a specific context. In scenarios taken from the legal domain, a formal account of the open-texture of legal terms is modeled, which suggests varying notions of the "core" and "penumbra" of the meanings of a concept. The progress of reasoning proceeds from the specific to the more general.[]

History

Anthropologists have observed that taxonomies are generally embedded in local cultural and social systems, and serve various social functions. Perhaps the most well-known and influential study of folk taxonomies is Émile Durkheim's The Elementary Forms of Religious Life. A more recent treatment of folk taxonomies (including the results of several decades of empirical research) and the discussion of their relation to the scientific taxonomy can be found in Scott Atran's Cognitive Foundations of Natural History. Folk taxonomies of organisms have been found in large part to agree with scientific classification, at least for the larger and more obvious species, which means that it is not the case that folk taxonomies are based purely on utilitarian characteristics.[]

In the seventeenth century the German mathematician and philosopher Gottfried Leibniz, following the work of the thirteenth-century Majorcan philosopher Ramon Llull on his Ars generalis ultima, a system for procedurally generating concepts by combining a fixed set of ideas, sought to develop an alphabet of human thought. Leibniz intended his characteristica universalis to be an "algebra" capable of expressing all conceptual thought. The concept of creating such a "universal language" was frequently examined in the 17th century, also notably by the English philosopher John Wilkins in his work An Essay towards a Real Character and a Philosophical Language (1668), from which the classification scheme in Roget's Thesaurus ultimately derives.

Taxonomy in various disciplines

Natural sciences

Taxonomy in biology encompasses the description, identification, nomenclature, and classification of organisms. Uses of taxonomy include:

Business and economics

Uses of taxonomy in business and economics include:

Computing

Software engineering

Vegas et al.[১০] make a compelling case to advance the knowledge in the field of software engineering through the use of taxonomies. Similarly, Ore et al.[১১] provide a systematic methodology to approach taxonomy building in software engineering related topics.

Several taxonomies have been proposed in software testing research to classify techniques, tools, concepts and artifacts. The following are some example taxonomies:

  1. A taxonomy of model-based testing techniques[১২]
  2. A taxonomy of static-code analysis tools[১৩]

Engström et al.[১৪] suggest and evaluate the use of a taxonomy to bridge the communication between researchers and practitioners engaged in the area of software testing. They have also developed a web-based tool[১৫] to facilitate and encourage the use of the taxonomy. The tool and its source code are available for public use.[১৬]

Other uses of taxonomy in computing

Education and academia

Uses of taxonomy in education include:

Safety

Uses of taxonomy in safety include:

Other taxonomies

Research publishing

Citing inadequacies with current practices in listing authors of papers in medical research journals, Drummond Rennie and co-authors called in a 1997 article in JAMA, the Journal of the American Medical Association for

a radical conceptual and systematic change, to reflect the realities of multiple authorship and to buttress accountability. We propose dropping the outmoded notion of author in favor of the more useful and realistic one of contributor.[১৭]:১৫২

Since 2012, several major academic and scientific publishing bodies have mounted Project CRediT to develop a controlled vocabulary of contributor roles.[১৮] Known as CRediT (Contributor Roles Taxonomy), this is an example of a flat, non-hierarchical taxonomy; however, it does include an optional, broad classification of the degree of contribution: lead, equal or supporting. Amy Brand and co-authors summarise their intended outcome as:

Identifying specific contributions to published research will lead to appropriate credit, fewer author disputes, and fewer disincentives to collaboration and the sharing of data and code.[১৭]:১৫১

As of mid-2018, this taxonomy apparently restricts its scope to research outputs, specifically journal articles; however, it does rather unusually "hope to … support identification of peer reviewers".[১৮] (As such, it has not yet defined terms for such roles as editor or author of a chapter in a book of research results.) Version 1, established by the first Working Group in the (northern) autumn of 2014, identifies 14 specific contributor roles using the following defined terms:

  • Conceptualization
  • Methodology
  • Software
  • Validation
  • Formal Analysis
  • Investigation
  • Resources
  • Data curation
  • Writing – Original Draft
  • Writing – Review & Editing
  • Visualization
  • Supervision
  • Project Administration
  • Funding acquisition

Reception has been mixed, with several major publishers and journals planning to have implemented CRediT by the end of 2018, whilst almost as many are not persuaded of the need or value of using it. For example,

The National Academy of Sciences has created a TACS (Transparency in Author Contributions in Science) webpage to list the journals that commit to setting authorship standards, defining responsibilities for corresponding authors, requiring ORCID iDs, and adopting the CRediT taxonomy.[১৯]

The same webpage has a table listing 21 journals (or families of journals), of which:

  • 5 have, or by end 2018 will have, implemented CRediT,
  • 6 require an author contribution statement and suggest using CRediT,
  • 8 do not use CRediT, of which 3 give reasons for not doing so, and
  • 2 are uninformative.

The taxonomy is an open standard conforming to the OpenStand principles,[২০] and is published under a Creative Commons licence.[১৮]

Taxonomy for the web

Websites with a well designed taxonomy or hierarchy are easily understood by users, due to the possibility of users developing a mental model of the site structure.[২১]

Guidelines for writing taxonomy for the web include:

  • Mutually exclusive categories can be beneficial. If categories appear several places, it's called cross-listing or polyhierarchical. The hierarchy will lose its value if cross-listing appears too often. Cross-listing often appears when working with ambiguous categories that fits more than one place.[২১]
  • Having a balance between breadth and depth in the taxonomy is beneficial. Too many options (breadth), will overload the users by giving them too many choices. At the same time having a too narrow structure, with more than two or three levels to click-through, will make users frustrated and might give up.[২১]

Is-a and has-a relationships, and hyponymy

Two of the predominant types of relationships in knowledge-representation systems are predication and the universally quantified conditional. Predication relationships express the notion that an individual entity is an example of a certain type (for example, John is a bachelor), while universally quantified conditionals express the notion that a type is a subtype of another type (for example, "A dog is a mammal", which means the same as "All dogs are mammals").[২২]

The "has-a" relationship is quite different: an elephant has a trunk; a trunk is a part, not a subtype of elephant. The study of part-whole relationships is mereology.

Taxonomies are often represented as is-a hierarchies where each level is more specific than the level above it (in mathematical language is "a subset of" the level above). For example, a basic biology taxonomy would have concepts such as mammal, which is a subset of animal, and dogs and cats, which are subsets of mammal. This kind of taxonomy is called an is-a model because the specific objects are considered as instances of a concept. For example, Fido is-an instance of the concept dog and Fluffy is-a cat.[২৩]

In linguistics, is-a relations are called hyponymy. When one word describes a category, but another describe some subset of that category, the larger term is called a hypernym with respect to the smaller, and the smaller is called a "hyponym" with respect to the larger. Such a hyponym, in turn, may have further subcategories for which it is a hypernym. In the simple biology example, dog is a hypernym with respect to its subcategory collie, which in turn is a hypernym with respect to Fido which is one of its hyponyms. Typically, however, hypernym is used to refer to subcategories rather than single individuals.

Research

Comparison of categories of small and large populations

Researchers reported that large populations consistently develop highly similar category systems. This may be relevant to lexical aspects of large communication networks and cultures such as folksonomies and language or human communication, and sense-making in general.[২৪][২৫]

See also

Notes

  1. Oxford English Dictionary। Oxford University Press। ১৯১০।  (partially updated December 2021), s.v.
  2. review of Aperçus de Taxinomie Générale in Nature 60:489–490 ওয়েব্যাক মেশিনে আর্কাইভকৃত ২০২৩-০১-২৬ তারিখে (1899)
  3. Zirn, Cäcilia, Vivi Nastase and Michael Strube. 2008. "Distinguishing Between Instances and Classes in the Wikipedia Taxonomy" (video lecture). ওয়েব্যাক মেশিনে আর্কাইভকৃত ২০১৯-১২-২০ তারিখে 5th Annual European Semantic Web Conference (ESWC 2008).
  4. S. Ponzetto and M. Strube. 2007. "Deriving a large scale taxonomy from Wikipedia" ওয়েব্যাক মেশিনে আর্কাইভকৃত ২০১৭-০৮-১৪ তারিখে. Proc. of the 22nd Conference on the Advancement of Artificial Intelligence, Vancouver, B.C., Canada, pp. 1440–1445.
  5. S. Ponzetto, R. Navigli. 2009. "Large-Scale Taxonomy Mapping for Restructuring and Integrating Wikipedia". Proc. of the 21st International Joint Conference on Artificial Intelligence (IJCAI 2009), Pasadena, California, pp. 2083–2088.
  6. Jackson, Joab. "Taxonomy's not just design, it's an art," ওয়েব্যাক মেশিনে আর্কাইভকৃত ২০২০-০২-০৫ তারিখে Government Computer News (Washington, D.C.). September 2, 2004.
  7. Suryanto, Hendra and Paul Compton. "Learning classification taxonomies from a classification knowledge based system." ওয়েব্যাক মেশিনে আর্কাইভকৃত ২০১৭-০৮-০৯ তারিখে University of Karlsruhe; "Defining 'Taxonomy'," ওয়েব্যাক মেশিনে আর্কাইভকৃত ২০১৭-০৮-০৯ তারিখে Straights Knowledge website.
  8. Grossi, Davide, Frank Dignum and John-Jules Charles Meyer. (2005). "Contextual Taxonomies" in Computational Logic in Multi-Agent Systems, pp. 33–51[অকার্যকর সংযোগ].
  9. Kenneth Boulding; Elias Khalil (২০০২)। Evolution, Order and Complexity। Routledge। আইএসবিএন 9780203013151  p. 9
  10. Vegas, S. (২০০৯)। "Maturing software engineering knowledge through classifications: A case study on unit testing techniques."। IEEE Transactions on Software Engineering35 (4): 551–565। এসটুসিআইডি 574495ডিওআই:10.1109/TSE.2009.13সাইট সিয়ারX 10.1.1.221.7589অবাধে প্রবেশযোগ্য 
  11. Ore, S. (২০১৪)। "Critical success factors taxonomy for software process deployment"। Software Quality Journal22 (1): 21–48। এসটুসিআইডি 18047921ডিওআই:10.1007/s11219-012-9190-y 
  12. Utting, Mark (২০১২)। "A taxonomy of model-based testing approaches"Software Testing, Verification & Reliability22 (5): 297–312। এসটুসিআইডি 6782211ডিওআই:10.1002/stvr.456। ২০১৯-১২-২০ তারিখে মূল থেকে আর্কাইভ করা। সংগ্রহের তারিখ ২০১৭-০৪-২৩ 
  13. Novak, Jernej (মে ২০১০)। "Taxonomy of static code analysis tools"Proceedings of the 33rd International Convention MIPRO: 418–422। ২০২২-০৬-২৭ তারিখে মূল থেকে আর্কাইভ করা। সংগ্রহের তারিখ ২০২০-০৩-০৩ 
  14. Engström, Emelie (২০১৬)। "SERP-test: a taxonomy for supporting industry–academia communication"। Software Quality Journal25 (4): 1269–1305। এসটুসিআইডি 34795073ডিওআই:10.1007/s11219-016-9322-x 
  15. "SERP-connect"। ২০২১-০৮-২৮ তারিখে মূল থেকে আর্কাইভ করা। সংগ্রহের তারিখ ২০২১-০৮-২৮ 
  16. Engstrom, Emelie (৪ ডিসেম্বর ২০১৯)। "SERP-connect backend"GitHub। ১০ ডিসেম্বর ২০১৯ তারিখে মূল থেকে আর্কাইভ করা। সংগ্রহের তারিখ ২৫ অক্টোবর ২০১৬ 
  17. Brand, Amy; Allen, Liz; Altman, Micah; Hlava, Marjorie; Scott, Jo (১ এপ্রিল ২০১৫)। "Beyond authorship: attribution, contribution, collaboration, and credit"। Learned Publishing28 (2): 151–155। এসটুসিআইডি 45167271ডিওআই:10.1087/20150211অবাধে প্রবেশযোগ্য 
  18. "CRediT"CASRAICASRAI। ২ মে ২০১৮। ১২ জুন ২০১৮ তারিখে মূল (online) থেকে আর্কাইভ করা। সংগ্রহের তারিখ ১৩ জুন ২০১৮ 
  19. "Transparency in Author Contributions in Science (TACS)"National Academy of Sciences। ২০১৮। ১৯ মে ২০১৯ তারিখে মূল (online) থেকে আর্কাইভ করা। সংগ্রহের তারিখ ১৩ জুন ২০১৮ 
  20. "OpenStand"OpenStand। ১৮ সেপ্টেম্বর ২০১৯ তারিখে মূল থেকে আর্কাইভ করা। সংগ্রহের তারিখ ১৩ জুন ২০১৮ 
  21. Peter., Morville (২০০৭)। Information architecture for the World Wide Web। Rosenfeld, Louis., Rosenfeld, Louis. (3rd সংস্করণ)। Sebastopol, CA: O'Reilly। আইএসবিএন 9780596527341ওসিএলসি 86110226 
  22. Ronald J. Brachman; What IS-A is and isn't. An Analysis of Taxonomic Links in Semantic Networks ওয়েব্যাক মেশিনে আর্কাইভকৃত ২০২০-০৬-৩০ তারিখে. IEEE Computer, 16 (10); October 1983.
  23. Brachman, Ronald (অক্টোবর ১৯৮৩)। "What IS-A is and isn't. An Analysis of Taxonomic Links in Semantic Networks"। IEEE Computer16 (10): 30–36। এসটুসিআইডি 16650410ডিওআই:10.1109/MC.1983.1654194 
  24. "Why independent cultures think alike when it comes to categories: It's not in the brain"phys.org (ইংরেজি ভাষায়)। ২৫ জানুয়ারি ২০২১ তারিখে মূল থেকে আর্কাইভ করা। সংগ্রহের তারিখ ১৩ ফেব্রুয়ারি ২০২১ 
  25. Guilbeault, Douglas; Baronchelli, Andrea; Centola, Damon (১২ জানুয়ারি ২০২১)। "Experimental evidence for scale-induced category convergence across populations"Nature Communications (ইংরেজি ভাষায়)। 12 (1): 327। আইএসএসএন 2041-1723ডিওআই:10.1038/s41467-020-20037-yঅবাধে প্রবেশযোগ্যপিএমআইডি 33436581 |pmid= এর মান পরীক্ষা করুন (সাহায্য)পিএমসি 7804416অবাধে প্রবেশযোগ্য |pmc= এর মান পরীক্ষা করুন (সাহায্য)বিবকোড:2021NatCo..12..327G  Available under CC BY 4.0 ওয়েব্যাক মেশিনে আর্কাইভকৃত ২০১৭-১০-১৬ তারিখে.

References