Properties of Nanostructures: Data Acquisition, Categorization, and Evaluation
This article is devoted to general problems of development of reference data on properties of nanosized objects. It has been shown that the peculiar features of physical characteristics of nanostructures influence the behavior of an expert engaged in building the relevant computer database of proper...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Ubiquity Press
2012-12-01
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| Series: | Data Science Journal |
| Subjects: | |
| Online Access: | http://datascience.codata.org/articles/55 |
| _version_ | 1811304516697456640 |
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| author | AV Eletskii AO Erkimbaev GA Kobzev MS Trachtengerts VY Zitserman |
| author_facet | AV Eletskii AO Erkimbaev GA Kobzev MS Trachtengerts VY Zitserman |
| author_sort | AV Eletskii |
| collection | DOAJ |
| description | This article is devoted to general problems of development of reference data on properties of nanosized objects. It has been shown that the peculiar features of physical characteristics of nanostructures influence the behavior of an expert engaged in building the relevant computer database of property data. The building procedure includes comprehensive data systematization on the basis of classification of nanostructures and detailed identification of a nano-inherent object within the selected class. The key features of data on nanosized objects are discussed, including variation of property nomenclature, dimensional effects, and a high level of data uncertainty. The approaches to data systematization proposed in the article are considered in terms of ISO recommendations. Along with systematization, we propose a procedure for data certification taking into account a quantitative statement of uncertainty as well as quality indicators. The latter indications address the completeness of the description of both an object and a measurement method as well as the reproducibility of results. As an example, property data of carbon nanoforms (nanotubes, graphene, etc.) are analyzed. |
| first_indexed | 2024-04-13T08:07:27Z |
| format | Article |
| id | doaj.art-e8c36bd7a1d541789bcf12c79a938436 |
| institution | Directory Open Access Journal |
| issn | 1683-1470 |
| language | English |
| last_indexed | 2024-04-13T08:07:27Z |
| publishDate | 2012-12-01 |
| publisher | Ubiquity Press |
| record_format | Article |
| series | Data Science Journal |
| spelling | doaj.art-e8c36bd7a1d541789bcf12c79a9384362022-12-22T02:55:06ZengUbiquity PressData Science Journal1683-14702012-12-011112613910.2481/dsj.010-02555Properties of Nanostructures: Data Acquisition, Categorization, and EvaluationAV Eletskii0AO Erkimbaev1GA Kobzev2MS Trachtengerts3VY Zitserman4National Research Centre “Kurchatov Institute”, Moscow, Russian FederationJoint Institute for High Temperatures, Russian Academy of Sciences, Izhorskaya 13, Bldg. 2, Moscow 125412, Russian FederationJoint Institute for High Temperatures, Russian Academy of Sciences, Izhorskaya 13, Bldg. 2, Moscow 125412, Russian FederationJoint Institute for High Temperatures, Russian Academy of Sciences, Izhorskaya 13, Bldg. 2, Moscow 125412, Russian FederationJoint Institute for High Temperatures, Russian Academy of Sciences, Izhorskaya 13, Bldg. 2, Moscow 125412, Russian FederationThis article is devoted to general problems of development of reference data on properties of nanosized objects. It has been shown that the peculiar features of physical characteristics of nanostructures influence the behavior of an expert engaged in building the relevant computer database of property data. The building procedure includes comprehensive data systematization on the basis of classification of nanostructures and detailed identification of a nano-inherent object within the selected class. The key features of data on nanosized objects are discussed, including variation of property nomenclature, dimensional effects, and a high level of data uncertainty. The approaches to data systematization proposed in the article are considered in terms of ISO recommendations. Along with systematization, we propose a procedure for data certification taking into account a quantitative statement of uncertainty as well as quality indicators. The latter indications address the completeness of the description of both an object and a measurement method as well as the reproducibility of results. As an example, property data of carbon nanoforms (nanotubes, graphene, etc.) are analyzed.http://datascience.codata.org/articles/55NanostructureNanomaterialNano-objectNanostructured materialNumeric properties dataDimensional effectLogical structureSemistructured dataData certificationData evaluation |
| spellingShingle | AV Eletskii AO Erkimbaev GA Kobzev MS Trachtengerts VY Zitserman Properties of Nanostructures: Data Acquisition, Categorization, and Evaluation Data Science Journal Nanostructure Nanomaterial Nano-object Nanostructured material Numeric properties data Dimensional effect Logical structure Semistructured data Data certification Data evaluation |
| title | Properties of Nanostructures: Data Acquisition, Categorization, and Evaluation |
| title_full | Properties of Nanostructures: Data Acquisition, Categorization, and Evaluation |
| title_fullStr | Properties of Nanostructures: Data Acquisition, Categorization, and Evaluation |
| title_full_unstemmed | Properties of Nanostructures: Data Acquisition, Categorization, and Evaluation |
| title_short | Properties of Nanostructures: Data Acquisition, Categorization, and Evaluation |
| title_sort | properties of nanostructures data acquisition categorization and evaluation |
| topic | Nanostructure Nanomaterial Nano-object Nanostructured material Numeric properties data Dimensional effect Logical structure Semistructured data Data certification Data evaluation |
| url | http://datascience.codata.org/articles/55 |
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