GLAUBER MAUCH DE CARVALHO

GLAUBER MAUCH DE CARVALHO

Página do item completo

Resultados de Busca

Agora exibindo 1 - 5 de 5

Desenvolvimento de uma camada semântica para um protótipo de repositório de dados de pesquisas de análise por ativação neutrônica
2020 - CARVALHO, GLAUBER M. de
Um dos pilares da ciência é a possibilidade de reprodução dos resultados de pesquisas científicas por pesquisadores independentes, tornando possível a validação dos métodos, dos resultados e suas conclusões. Para que isto seja possível no cenário atual, onde a produção de dados científicos tomou uma proporção gigantesca (Big Data), métodos sistemáticos de armazenamento, curadoria e disponibilização dos dados precisam ser implementados. Diante do grande volume de dados disponíveis, todo o processo científico é impactado, possibilitando o surgimento de um novo paradigma científico: a e-Science ou e-Ciência. Neste trabalho foram desenvolvidos uma ontologia para o domínio dos dados da área de Análise por Ativação Neutrônica e de um protótipo de repositório de dados de pesquisa. A metodologia adotada para a construção da ontologia foram o Léxico Aplicado da Linguagem (LAL) e a Ontology Development 101 (Método 101). A integração da camada semântica com o SGBD PostgreSQL foi emulada através do Protégé e sua ferramenta Ontop, realizando uma conexão direta com o banco de dados relacional. Nesta emulação, consultas semânticas foram realizadas em SPARQL. Os resultados apresentados demonstram os ganhos oriundos desta integração e apontam para vantagens de se ter uma camada semântica em um repositório de dados, incluindo, mas não se limitando, à maior possibilidade de reuso dos dados visto que podem ser melhor entendidos a partir da ontologia que os descreve. O protótipo de repositório foi desenvolvido utilizando-se um framework de desenvolvimento Web de código aberto - Django, com a linguagem de programação Python, o que possibilitou bastante flexibilidade e agilidade neste processo.
Development of a semantic layer for a data repository prototype for neutron activation analysis domain data
2019 - CARVALHO, GLAUBER M. de; SEMMLER, RENATO; MENEZES, MARIO O. de
In order to provide greater transparency for scienti c research and the results achieved, a great e ort is ongoing to make available scienti c data repositories, which allow for di erent researchers to validate, reproduce and reuse third party scienti c data. With the always increasing use of technology in all kinds of scienti c facilities, a growing amount of data is collected even from simple experiments. This scenario presents a new paradigm: the understanding of third party data easily found on data repositories. Consequently, being able to do useful searches on these data repositories poses a new challenge for traditional search engines. In this work, the approach taken to help solve these problems was to propose a semantic layer for scienti c data repository. By using ontologies, with appropriated integration of traditional search mechanisms, it will be easier for users to nd related data that could be used in their work, improving the overall scienti c yield. In order to achieve this goal, a ontology was developed, using the Prot eg e software, for the Neutron Activation Analysis (NAA) data domain. This ontology was validated by experts from NAA Laboratory of the Reactor Research Center (CERPq) at the Nuclear and Energy Research Institute (IPEN-CNEN/SP). A prototype of a semantic data repository is, thus, being developed using the Django web development framework. RDFlib, a software library written in Python is being used to allow the integration of semantic operations, based on the NAA ontology, with the relational database layer provided by Django.
Repositório semântico de dados de análise por ativação neutrônica
2018 - CARVALHO, GLAUBER M. de; SEMMLER, RENATO; MENEZES, MARIO O. de
Scientific Data Repositories are being made available each time more often, in a search for more transparency for scientific research and its results, making, in this way, possible to validate, reproduce and reuse the data in other studies. In this work, we present the ongoing research, part of a master dissertation, being developed at IPEN-CNEN/SP, seeking to build a semantic repository for Neutron Activation Analysis research data. The study began with the ontology construction and some of the preliminar results of this phase are presented.
E-science, data science and scientific computing
2017 - MENEZES, M.O.; SEMMLER, R.; CARVALHO, G.M. de; LANDULFO, E.; DIAS, M.S.
The publication of papers in scientific journals or conference proceedings, has being the main way of summarization of experimental results obtained by the researchers over the time. However, the sharing of the experimental data in raw format or after some processing, is also equally important for the scientific community, as they provide the necessary input to reproducible experiments and also to independent validation of scientific results. Nowadays, the volume of scientific data production has increased to giant amounts, demanding new means of storage and curation as well as processes and technologies to make them available in durable ways. As a consequence, and at the same time a response, to those demands, a new scientific paradigm has emerged: the e-Science. This new paradigm distinguished itself from the traditional science, being characterized by intense computational activity, required to process the large volume of data that can be obtained from modern scientific experiments. e-Science, ultimately, is related to knowledge discovery and sharing not only as scientific publications, but also as experimental data, rich theoretic vocabularies, and several reusable services useful to the scientific community. The great availability of scientific data, both in raw or processed formats, leveraged by the adoption of transparency and accessibility politics by scientists all over the globe which publish their data on institutional or private repositories, are making possible also the reutilization of such data for new analysis by other scientists, who, employing new statistical approaches, such as machine learning algorithms suited to large amount of data, are also obtaining new results, not only from old data, but also, from the big amount of data originated from modern experimental facilities, doing what is known as "data science". The demand for intense computational utilization by e-Science related activities include not only the traditional simulation methods, but also the development of new tools that can operate in these new environments, such as, cloud based storage, cloud based access and analysis, mobile access to their research data, equipment monitoring and management, etc. All these activities are the scope of Scientific Computing being conducted at the Research Reactor Center - CRPq (IPEN-CNEN/SP).
IPEN e-science semantic repository – neutron activation analysis data
2017 - CARVALHO, G.M.; SEMMLER, R.; MENEZES, M.O.
Scientific knowledge production has been characterized over the time by the publication of papers in scientific journals or conference proceedings, which summarize the experimental results obtained by the researchers. However, the sharing of the experimental data in raw format or after some processing, is also equally important for the scientific community, as they provide the necessary input to reproducible experiments and also to independent validation of scientific results. In the current scenario, the volume of scientific data production has increased to giant amounts, demanding new means of storage and curation as well as processes and technologies to make them available in durable ways. As a consequence, and at the same time a response, to those demands, a new scientific paradigm has emerged: the e-Science. This new paradigm distinguished itself from the traditional science, being characterized by intense computational activity, required to process the large volume of data that can be obtained from modern scientific experiments. e- Science, ultimately, is related to knowledge discovery and sharing not only as scientific publications, but also as experimental data, rich theoretic vocabularies, and several reusable services useful to the scientific community. The main objective of this project is to create a semantic data repository for all the investigations done at the Neutron Activation Analysis Laboratory of the Research Reactor Center – CRPq (IPEN-CNEN/SP). Our primary goal is to provide a platform that supports the preservation of all data originated from all investigations carried out at our research center, increasing the reproductibility and also providing new integrated solutions to e-Science applications. The data repository has as its main characteristics and goals, from the researcher point of view: access control to all scientific data for all its life cycle, experimental data acquisition integration, research data filtering and storage. For the general public, the data repository will offer a unified location for all research data produced at IPEN, a searchable interface and links to publications related to the accessed data. This search capability will be improved and extended by the utilisation of a semantic layer supported by a data/domain ontology. The resulting semantic data repository will then be able to increase the search efficiency, with more accurate information, due to the controlled vocabulary provided by ontology as well as due to the possibility of the use of an inference engine together with the search engine.