Serendipity prospecção semântica de dados qualitativos em Educação Especial
Autor(a) principal: | |
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Data de Publicação: | 2016 |
Tipo de documento: | Tese |
Idioma: | por |
Título da fonte: | Repositório Institucional da UFSCAR |
Texto Completo: | https://repositorio.ufscar.br/handle/ufscar/8576 |
Resumo: | In the past decades, there has been a revolution in the way science has been conducted. The current context has demanded more collaborative work such as, studies in research networks of large scale. One of the many essential marks of change in this new way of making science has been the intense usage of Information and Communication Technologies (ICT), or “eScience”. Nowadays, it plays a fundamental role in the methodology adopted by many research groups around the world. Analyses of the qualitative data evidenced in researches about Special Education were done then. The biggest challenge that was noticed would be to advance in the analysis of qualitative data using information technologies without losing the subjectivity involved in the research and to broaden the capability of going over the data without losing the right to come and go, the right to critique and establish proper reflexions, respecting subjective positioning and, above all, maintaining the research's critic criteria. In this sense, this work establishes as its main objective to evaluate the proposed technological architecture of qualitative analyses of data. This analysis was based upon data mining theories, researches in ontology and techniques of semantic notation in the field of special education aiming to analyze the thresholds and possibilities this methodological approach permits. We used as methodology the construction of a prototype, named Serendipity, based on the perspective of software engineering, in order to extract the main techniques that could set as a safe method for design, implementation and deployment of the solution. Cyclically, the methodology allowed us to modify requirements and establish improvements, allowing the feedback process from new analyses. The text mining process relied on gaining knowledge from textual databases that have little or no data structure. The computational ontology was the element able to reconstruct the syntactic representation, giving it direction. The words (data) are related and are set within a context of formal knowledge, providing them with a semantic and cognitive ability, building concepts, open to interpretation, comprehension and common understanding; as a result, we built up a specific ontology for Special Education. The semantic annotation helped attach content to the text to describe their semantics, allowing that software agents could retrieve information in a more precise manner through the association of the document to the ontology in a conception of semantic fields. We built a customized dictionary for special education to relate terms to synonyms and expressions associated with the ontology. To view beyond the semantic classes, we used automatic concept maps to establish relationships between concepts included in a hierarchical structure of propositions. Finally, to assess the proposal, we made use of part of the data collected from the National Observatory of Special Education in transcribed texts about the formation of five cities, one from each region of Brazil. The results show limits already recognized in the proposal and; in this respect, did not aim to establish a subjective and deep analysis that would permit extreme precision results. It points out that the researcher is and will always be the driving factor that operates the process’ flow and relying, or not, on computing tools is not entirely immune to err. The proposal of serendipity has given a step forward in the automatic process of data analysis and can be used in big data without losing the subjectivity of the researcher. However, we must add new human and technological resources to contribute to its improvement and encourage other areas to develop domain ontologies with their experts and the development of specific dictionaries. Therefore, despite its limitations, the approach has shown significant advances in semantic exploration of qualitative data in the Special Education field and it is capable of being adapted to other areas and fields of knowledge. |
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Fernandes, Woquiton LimaMendes, Enicéia Gonçalveshttp://lattes.cnpq.br/3897627554738983Santos, Marilde Terezinha Pradohttp://lattes.cnpq.br/9826026025118073http://lattes.cnpq.br/59631182513826556d1144b4-770d-4d29-9ec1-cfd30892d0922017-03-20T13:54:25Z2017-03-20T13:54:25Z2016-08-22FERNANDES, Woquiton Lima. Serendipity prospecção semântica de dados qualitativos em Educação Especial. 2016. Tese (Doutorado em Educação Especial) – Universidade Federal de São Carlos, São Carlos, 2016. Disponível em: https://repositorio.ufscar.br/handle/ufscar/8576.https://repositorio.ufscar.br/handle/ufscar/8576In the past decades, there has been a revolution in the way science has been conducted. The current context has demanded more collaborative work such as, studies in research networks of large scale. One of the many essential marks of change in this new way of making science has been the intense usage of Information and Communication Technologies (ICT), or “eScience”. Nowadays, it plays a fundamental role in the methodology adopted by many research groups around the world. Analyses of the qualitative data evidenced in researches about Special Education were done then. The biggest challenge that was noticed would be to advance in the analysis of qualitative data using information technologies without losing the subjectivity involved in the research and to broaden the capability of going over the data without losing the right to come and go, the right to critique and establish proper reflexions, respecting subjective positioning and, above all, maintaining the research's critic criteria. In this sense, this work establishes as its main objective to evaluate the proposed technological architecture of qualitative analyses of data. This analysis was based upon data mining theories, researches in ontology and techniques of semantic notation in the field of special education aiming to analyze the thresholds and possibilities this methodological approach permits. We used as methodology the construction of a prototype, named Serendipity, based on the perspective of software engineering, in order to extract the main techniques that could set as a safe method for design, implementation and deployment of the solution. Cyclically, the methodology allowed us to modify requirements and establish improvements, allowing the feedback process from new analyses. The text mining process relied on gaining knowledge from textual databases that have little or no data structure. The computational ontology was the element able to reconstruct the syntactic representation, giving it direction. The words (data) are related and are set within a context of formal knowledge, providing them with a semantic and cognitive ability, building concepts, open to interpretation, comprehension and common understanding; as a result, we built up a specific ontology for Special Education. The semantic annotation helped attach content to the text to describe their semantics, allowing that software agents could retrieve information in a more precise manner through the association of the document to the ontology in a conception of semantic fields. We built a customized dictionary for special education to relate terms to synonyms and expressions associated with the ontology. To view beyond the semantic classes, we used automatic concept maps to establish relationships between concepts included in a hierarchical structure of propositions. Finally, to assess the proposal, we made use of part of the data collected from the National Observatory of Special Education in transcribed texts about the formation of five cities, one from each region of Brazil. The results show limits already recognized in the proposal and; in this respect, did not aim to establish a subjective and deep analysis that would permit extreme precision results. It points out that the researcher is and will always be the driving factor that operates the process’ flow and relying, or not, on computing tools is not entirely immune to err. The proposal of serendipity has given a step forward in the automatic process of data analysis and can be used in big data without losing the subjectivity of the researcher. However, we must add new human and technological resources to contribute to its improvement and encourage other areas to develop domain ontologies with their experts and the development of specific dictionaries. Therefore, despite its limitations, the approach has shown significant advances in semantic exploration of qualitative data in the Special Education field and it is capable of being adapted to other areas and fields of knowledge.Nas últimas décadas, tem ocorrido uma revolução no modo como a ciência tem sido conduzida, o atual contexto tem demandado cada vez mais o trabalho colaborativo, tais como os estudos em redes de pesquisa de ampla escala. Um dos pontos essenciais de mudança nessa nova forma de se fazer ciência tem sido o uso intenso de Tecnologias de Informação e Comunicação (TIC), chamada como “eScience”, que desempenha hoje um papel fundamental na metodologia adotada por muitos grupos de pesquisa ao redor do mundo. Partiu-se então para uma reflexão acerca do aprofundamento de dados qualitativos evidenciadas principalmente nas pesquisas em Educação Especial. O grande desafio seria avançar na qualidade da análise de dados qualitativos com uso das tecnologias da informação sem perder a subjetividade envolvida na pesquisa e ampliar a capacidade de esmiuçar os dados sem perder a liberdade de ir e vir, de criticar e estabelecer reflexões próprias, respeitando posicionamentos e, sobretudo, mantendo o rigor científico na pesquisa. Neste sentido, o presente estudo estabeleceu como objetivo principal avaliar a arquitetura tecnológica proposta de análise qualitativa de dados, tendo como base as teorias de mineração de textos, ontologia computacional e técnicas de anotação semântica, em pesquisa da educação especial, a fim de analisar os limites e possibilidades desta abordagem metodológica. Utilizamos como metodologia baseada na construção de um protótipo, denominado Serendipity, fundamentado na perspectiva da engenharia de software, de maneira que extraímos as principais técnicas que puderam definir um método seguro para a concepção, implementação e implantação da solução. De forma cíclica a metodologia permitia modificar requisitos e estabelecer melhorias, permitindo a retroalimentação do processo a partir de novas análises. Para isto, a mineração de textos apoiou-se na obtenção de conhecimento a partir de bases de dados textuais que possuem pouca ou nenhuma estrutura de dados. A ontologia computacional foi o elemento capaz de reconstruir a representação sintática, dando a ela sentido. As palavras (dados) se relacionam e são postas dentro de um contexto, de um conhecimento formal, dotando-as de uma capacidade semântica e cognitiva, construindo conceitos, passível de interpretação, compreensão e entendimento comum; para isto construiu-se uma ontologia específica para Educação Especial. A anotação semântica ajudou a anexar conteúdos ao texto para descrever a sua semântica, permitindo que agentes de software pudessem recuperar informações de forma mais precisa, através da associação do documento à ontologia, numa concepção de campos semânticos. Construiu-se também um dicionário da Educação Especial customizado para relacionar termos a sinônimos e expressões associadas à ontologia. Para visualização, além das classes semânticas, utilizou-se de mapas conceituais automáticos para estabelecer relações entre conceitos incluídos numa estrutura hierárquica de proposições. Por fim, para a avaliação da proposta utilizou-se de parte dos dados coletados no Observatório Nacional da Educação Especial de textos transcritos acerca da Formação em cinco cidades, sendo uma de cada região do Brasil. Os resultados evidenciam limites já reconhecidos na proposta e, neste aspecto, não teve a pretensão de determinar uma análise subjetiva e detalhista, que a rigor, permita resultados de extrema precisão. Destaca que o pesquisador é e sempre será o condutor livre do funcionamento do processo e contando, ou não, com ferramentas computacionais ele pode cometer erros. A proposta do serendipity deu um passo no processo automático de análise de dados, podendo ser aproveitada em big data, pesquisas de nível nacional, sem perder a subjetividade do pesquisador. Para isto é preciso agregar novos recursos humanos e tecnológicos que contribuam em seu aprimoramento. Estimular outras áreas a desenvolverem ontologias de domínio com seus especialistas e a evolução dos dicionários específicos. Portanto, apesar de seus limites, a abordagem possui avanços significativos na prospecção semântica de dados qualitativos em Educação Especial e passível de adaptação a outras áreas de conhecimento.Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)porUniversidade Federal de São CarlosCâmpus São CarlosPrograma de Pós-Graduação em Educação Especial - PPGEEsUFSCarEducação especialAnálise qualitativaOntologia computacionalMineração de textosAnotação semânticaSpecial educationQualitative analysisComputational ontologyText miningSemantic annotationCIENCIAS HUMANAS::EDUCACAOSerendipity prospecção semântica de dados qualitativos em Educação Especialinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/doctoralThesisOnline6006003ed1db7c-9efd-477c-babb-fe4fa24cbf3cinfo:eu-repo/semantics/openAccessreponame:Repositório Institucional da UFSCARinstname:Universidade Federal de São Carlos (UFSCAR)instacron:UFSCARORIGINALTeseWLF.pdfTeseWLF.pdfapplication/pdf10494807https://repositorio.ufscar.br/bitstream/ufscar/8576/1/TeseWLF.pdfdf4332346794cb6528875bef5e9313c4MD51LICENSElicense.txtlicense.txttext/plain; charset=utf-81957https://repositorio.ufscar.br/bitstream/ufscar/8576/2/license.txtae0398b6f8b235e40ad82cba6c50031dMD52TEXTTeseWLF.pdf.txtTeseWLF.pdf.txtExtracted texttext/plain369982https://repositorio.ufscar.br/bitstream/ufscar/8576/3/TeseWLF.pdf.txtc4df68f12c03b0390e3320c19dc97948MD53THUMBNAILTeseWLF.pdf.jpgTeseWLF.pdf.jpgIM Thumbnailimage/jpeg5321https://repositorio.ufscar.br/bitstream/ufscar/8576/4/TeseWLF.pdf.jpg2efdbd14e8c21477da4b492e9aea8ff1MD54ufscar/85762023-09-18 18:31:08.749oai:repositorio.ufscar.br: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Repositório InstitucionalPUBhttps://repositorio.ufscar.br/oai/requestopendoar:43222023-09-18T18:31:08Repositório Institucional da UFSCAR - Universidade Federal de São Carlos (UFSCAR)false |
dc.title.por.fl_str_mv |
Serendipity prospecção semântica de dados qualitativos em Educação Especial |
title |
Serendipity prospecção semântica de dados qualitativos em Educação Especial |
spellingShingle |
Serendipity prospecção semântica de dados qualitativos em Educação Especial Fernandes, Woquiton Lima Educação especial Análise qualitativa Ontologia computacional Mineração de textos Anotação semântica Special education Qualitative analysis Computational ontology Text mining Semantic annotation CIENCIAS HUMANAS::EDUCACAO |
title_short |
Serendipity prospecção semântica de dados qualitativos em Educação Especial |
title_full |
Serendipity prospecção semântica de dados qualitativos em Educação Especial |
title_fullStr |
Serendipity prospecção semântica de dados qualitativos em Educação Especial |
title_full_unstemmed |
Serendipity prospecção semântica de dados qualitativos em Educação Especial |
title_sort |
Serendipity prospecção semântica de dados qualitativos em Educação Especial |
author |
Fernandes, Woquiton Lima |
author_facet |
Fernandes, Woquiton Lima |
author_role |
author |
dc.contributor.authorlattes.por.fl_str_mv |
http://lattes.cnpq.br/5963118251382655 |
dc.contributor.author.fl_str_mv |
Fernandes, Woquiton Lima |
dc.contributor.advisor1.fl_str_mv |
Mendes, Enicéia Gonçalves |
dc.contributor.advisor1Lattes.fl_str_mv |
http://lattes.cnpq.br/3897627554738983 |
dc.contributor.advisor-co1.fl_str_mv |
Santos, Marilde Terezinha Prado |
dc.contributor.advisor-co1Lattes.fl_str_mv |
http://lattes.cnpq.br/9826026025118073 |
dc.contributor.authorID.fl_str_mv |
6d1144b4-770d-4d29-9ec1-cfd30892d092 |
contributor_str_mv |
Mendes, Enicéia Gonçalves Santos, Marilde Terezinha Prado |
dc.subject.por.fl_str_mv |
Educação especial Análise qualitativa Ontologia computacional Mineração de textos Anotação semântica |
topic |
Educação especial Análise qualitativa Ontologia computacional Mineração de textos Anotação semântica Special education Qualitative analysis Computational ontology Text mining Semantic annotation CIENCIAS HUMANAS::EDUCACAO |
dc.subject.eng.fl_str_mv |
Special education Qualitative analysis Computational ontology Text mining Semantic annotation |
dc.subject.cnpq.fl_str_mv |
CIENCIAS HUMANAS::EDUCACAO |
description |
In the past decades, there has been a revolution in the way science has been conducted. The current context has demanded more collaborative work such as, studies in research networks of large scale. One of the many essential marks of change in this new way of making science has been the intense usage of Information and Communication Technologies (ICT), or “eScience”. Nowadays, it plays a fundamental role in the methodology adopted by many research groups around the world. Analyses of the qualitative data evidenced in researches about Special Education were done then. The biggest challenge that was noticed would be to advance in the analysis of qualitative data using information technologies without losing the subjectivity involved in the research and to broaden the capability of going over the data without losing the right to come and go, the right to critique and establish proper reflexions, respecting subjective positioning and, above all, maintaining the research's critic criteria. In this sense, this work establishes as its main objective to evaluate the proposed technological architecture of qualitative analyses of data. This analysis was based upon data mining theories, researches in ontology and techniques of semantic notation in the field of special education aiming to analyze the thresholds and possibilities this methodological approach permits. We used as methodology the construction of a prototype, named Serendipity, based on the perspective of software engineering, in order to extract the main techniques that could set as a safe method for design, implementation and deployment of the solution. Cyclically, the methodology allowed us to modify requirements and establish improvements, allowing the feedback process from new analyses. The text mining process relied on gaining knowledge from textual databases that have little or no data structure. The computational ontology was the element able to reconstruct the syntactic representation, giving it direction. The words (data) are related and are set within a context of formal knowledge, providing them with a semantic and cognitive ability, building concepts, open to interpretation, comprehension and common understanding; as a result, we built up a specific ontology for Special Education. The semantic annotation helped attach content to the text to describe their semantics, allowing that software agents could retrieve information in a more precise manner through the association of the document to the ontology in a conception of semantic fields. We built a customized dictionary for special education to relate terms to synonyms and expressions associated with the ontology. To view beyond the semantic classes, we used automatic concept maps to establish relationships between concepts included in a hierarchical structure of propositions. Finally, to assess the proposal, we made use of part of the data collected from the National Observatory of Special Education in transcribed texts about the formation of five cities, one from each region of Brazil. The results show limits already recognized in the proposal and; in this respect, did not aim to establish a subjective and deep analysis that would permit extreme precision results. It points out that the researcher is and will always be the driving factor that operates the process’ flow and relying, or not, on computing tools is not entirely immune to err. The proposal of serendipity has given a step forward in the automatic process of data analysis and can be used in big data without losing the subjectivity of the researcher. However, we must add new human and technological resources to contribute to its improvement and encourage other areas to develop domain ontologies with their experts and the development of specific dictionaries. Therefore, despite its limitations, the approach has shown significant advances in semantic exploration of qualitative data in the Special Education field and it is capable of being adapted to other areas and fields of knowledge. |
publishDate |
2016 |
dc.date.issued.fl_str_mv |
2016-08-22 |
dc.date.accessioned.fl_str_mv |
2017-03-20T13:54:25Z |
dc.date.available.fl_str_mv |
2017-03-20T13:54:25Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/doctoralThesis |
format |
doctoralThesis |
status_str |
publishedVersion |
dc.identifier.citation.fl_str_mv |
FERNANDES, Woquiton Lima. Serendipity prospecção semântica de dados qualitativos em Educação Especial. 2016. Tese (Doutorado em Educação Especial) – Universidade Federal de São Carlos, São Carlos, 2016. Disponível em: https://repositorio.ufscar.br/handle/ufscar/8576. |
dc.identifier.uri.fl_str_mv |
https://repositorio.ufscar.br/handle/ufscar/8576 |
identifier_str_mv |
FERNANDES, Woquiton Lima. Serendipity prospecção semântica de dados qualitativos em Educação Especial. 2016. Tese (Doutorado em Educação Especial) – Universidade Federal de São Carlos, São Carlos, 2016. Disponível em: https://repositorio.ufscar.br/handle/ufscar/8576. |
url |
https://repositorio.ufscar.br/handle/ufscar/8576 |
dc.language.iso.fl_str_mv |
por |
language |
por |
dc.relation.confidence.fl_str_mv |
600 600 |
dc.relation.authority.fl_str_mv |
3ed1db7c-9efd-477c-babb-fe4fa24cbf3c |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.publisher.none.fl_str_mv |
Universidade Federal de São Carlos Câmpus São Carlos |
dc.publisher.program.fl_str_mv |
Programa de Pós-Graduação em Educação Especial - PPGEEs |
dc.publisher.initials.fl_str_mv |
UFSCar |
publisher.none.fl_str_mv |
Universidade Federal de São Carlos Câmpus São Carlos |
dc.source.none.fl_str_mv |
reponame:Repositório Institucional da UFSCAR instname:Universidade Federal de São Carlos (UFSCAR) instacron:UFSCAR |
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Universidade Federal de São Carlos (UFSCAR) |
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UFSCAR |
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UFSCAR |
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Repositório Institucional da UFSCAR |
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Repositório Institucional da UFSCAR |
bitstream.url.fl_str_mv |
https://repositorio.ufscar.br/bitstream/ufscar/8576/1/TeseWLF.pdf https://repositorio.ufscar.br/bitstream/ufscar/8576/2/license.txt https://repositorio.ufscar.br/bitstream/ufscar/8576/3/TeseWLF.pdf.txt https://repositorio.ufscar.br/bitstream/ufscar/8576/4/TeseWLF.pdf.jpg |
bitstream.checksum.fl_str_mv |
df4332346794cb6528875bef5e9313c4 ae0398b6f8b235e40ad82cba6c50031d c4df68f12c03b0390e3320c19dc97948 2efdbd14e8c21477da4b492e9aea8ff1 |
bitstream.checksumAlgorithm.fl_str_mv |
MD5 MD5 MD5 MD5 |
repository.name.fl_str_mv |
Repositório Institucional da UFSCAR - Universidade Federal de São Carlos (UFSCAR) |
repository.mail.fl_str_mv |
|
_version_ |
1802136320928120832 |