{"id":13147769,"identifier":"DVN/BISM0N","persistentUrl":"https://doi.org/10.7910/DVN/BISM0N","protocol":"doi","authority":"10.7910","separator":"/","publisher":"Harvard Dataverse","publicationDate":"2025-11-12","storageIdentifier":"s3://10.7910/DVN/BISM0N","datasetType":"dataset","datasetVersion":{"id":561641,"datasetId":13147769,"datasetPersistentId":"doi:10.7910/DVN/BISM0N","datasetType":"dataset","storageIdentifier":"s3://10.7910/DVN/BISM0N","versionNumber":1,"internalVersionNumber":8,"versionMinorNumber":0,"versionState":"RELEASED","latestVersionPublishingState":"RELEASED","lastUpdateTime":"2025-11-12T16:15:56Z","releaseTime":"2025-11-12T16:15:56Z","createTime":"2025-11-12T06:25:57Z","publicationDate":"2025-11-12","citationDate":"2025-11-12","license":{"name":"CC0 1.0","uri":"http://creativecommons.org/publicdomain/zero/1.0","iconUri":"https://licensebuttons.net/p/zero/1.0/88x31.png","rightsIdentifier":"CC0-1.0","rightsIdentifierScheme":"SPDX","schemeUri":"https://spdx.org/licenses/","languageCode":"en"},"fileAccessRequest":true,"metadataBlocks":{"citation":{"displayName":"Citation Metadata","name":"citation","fields":[{"typeName":"title","multiple":false,"typeClass":"primitive","value":"Data and Code for: \"Universal Adaptive Normalization Scale (AMIS): Integration of Heterogeneous Metrics into a Unified System\""},{"typeName":"author","multiple":true,"typeClass":"compound","value":[{"authorName":{"typeName":"authorName","multiple":false,"typeClass":"primitive","value":"Kravtsov, Gennady"},"authorAffiliation":{"typeName":"authorAffiliation","multiple":false,"typeClass":"primitive","value":"Research Center for Applied Statistics"}}]},{"typeName":"datasetContact","multiple":true,"typeClass":"compound","value":[{"datasetContactName":{"typeName":"datasetContactName","multiple":false,"typeClass":"primitive","value":"Kravtsov, Gennady"},"datasetContactAffiliation":{"typeName":"datasetContactAffiliation","multiple":false,"typeClass":"primitive","value":"Research Center for Applied Statistics"},"datasetContactEmail":{"typeName":"datasetContactEmail","multiple":false,"typeClass":"primitive","value":"62abc@mail.ru"}}]},{"typeName":"dsDescription","multiple":true,"typeClass":"compound","value":[{"dsDescriptionValue":{"typeName":"dsDescriptionValue","multiple":false,"typeClass":"primitive","value":"Dataset Title: Data and Code for: \"Universal Adaptive Normalization Scale (AMIS): Integration of Heterogeneous Metrics into a Unified System\"\n\nDescription:\nThis dataset contains source data and processing results for validating the Adaptive Multi-Interval Scale (AMIS) normalization method. Includes educational performance data (student grades), economic statistics (World Bank GDP), and Python implementation of the AMIS algorithm with graphical interface.\n\nContents:\n- Source data: educational grades and GDP statistics\n- AMIS normalization results (3, 5, 9, 17-point models)\n- Comparative analysis with linear normalization\n- Ready-to-use Python code for data processing\n\nApplications:\n- Educational data normalization and analysis\n- Economic indicators comparison\n- Development of unified metric systems\n- Methodology research in data scaling\n\nTechnical info:\nPython code with pandas, numpy, scipy, matplotlib dependencies. Data in Excel format."},"dsDescriptionDate":{"typeName":"dsDescriptionDate","multiple":false,"typeClass":"primitive","value":"2025-11-12"}}]},{"typeName":"subject","multiple":true,"typeClass":"controlledVocabulary","value":["Computer and Information Science","Social Sciences"]},{"typeName":"keyword","multiple":true,"typeClass":"compound","value":[{"keywordValue":{"typeName":"keywordValue","multiple":false,"typeClass":"primitive","value":"data normalization"}},{"keywordValue":{"typeName":"keywordValue","multiple":false,"typeClass":"primitive","value":"adaptive scaling"}},{"keywordValue":{"typeName":"keywordValue","multiple":false,"typeClass":"primitive","value":"educational analytics"}},{"keywordValue":{"typeName":"keywordValue","multiple":false,"typeClass":"primitive","value":"metric integration"}},{"keywordValue":{"typeName":"keywordValue","multiple":false,"typeClass":"primitive","value":"heterogeneous data"}},{"keywordValue":{"typeName":"keywordValue","multiple":false,"typeClass":"primitive","value":"statistical distribution"}},{"keywordValue":{"typeName":"keywordValue","multiple":false,"typeClass":"primitive","value":"Python implementation"}},{"keywordValue":{"typeName":"keywordValue","multiple":false,"typeClass":"primitive","value":"educational assessment"}},{"keywordValue":{"typeName":"keywordValue","multiple":false,"typeClass":"primitive","value":"GDP analysis"}},{"keywordValue":{"typeName":"keywordValue","multiple":false,"typeClass":"primitive","value":"AMIS"}}]},{"typeName":"publication","multiple":true,"typeClass":"compound","value":[{"publicationRelationType":{"typeName":"publicationRelationType","multiple":false,"typeClass":"controlledVocabulary","value":"References"},"publicationCitation":{"typeName":"publicationCitation","multiple":false,"typeClass":"primitive","value":"Кравцов, Г. (2025). НОРМАЛИЗАЦИЯ ШКАЛЫ ИНТЕНСИВНОСТИ УЧЕБНЫХ ЗАНЯТИЙ В АНАЛИТИЧЕСКОМ МЕТОДЕ КОНТРОЛЯ ОБРАЗОВАНИЯ (Version v1) [Data set]. НИЦ Прикладная статистика. https://doi.org/10.5281/zenodo.17374975"},"publicationIDType":{"typeName":"publicationIDType","multiple":false,"typeClass":"controlledVocabulary","value":"doi"},"publicationIDNumber":{"typeName":"publicationIDNumber","multiple":false,"typeClass":"primitive","value":"https://doi.org/10.5281/zenodo.17588054"}}]},{"typeName":"notesText","multiple":false,"typeClass":"primitive","value":"Technical Notes:\n- All Excel files contain original data and AMIS normalization results\n- Python code requires pandas, numpy, scipy, matplotlib libraries\n- Includes examples for educational data (grades) and economic data (GDP)\n- Fixed boundary (2-5) and empirical boundary normalization demonstrated\n- Ready-to-use implementations for 3, 5, 9, 17-point AMIS models\n\nUsage: See 01_README.txt for complete documentation and examples.\n\nТехнические примечания:\n- Все Excel-файлы содержат исходные данные и результаты нормализации AMIS\n- Python-код требует установки библиотек: pandas, numpy, scipy, matplotlib\n- Включены примеры для образовательных данных (оценки) и экономических данных (ВВП)\n- Продемонстрированы нормализация с фиксированными (2-5) и эмпирическими границами\n- Готовые реализации 3, 5, 9, 17-точечных моделей AMIS\n\nИспользование: Полная документация и примеры в файле 01_README.txt."},{"typeName":"depositor","multiple":false,"typeClass":"primitive","value":"Kravtsov, Gennady"},{"typeName":"dateOfDeposit","multiple":false,"typeClass":"primitive","value":"2025-11-12"}]}},"files":[{"description":"Complete dataset description and user guide","label":"01_README.txt","restricted":false,"version":2,"datasetVersionId":561641,"dataFile":{"id":13147777,"persistentId":"","filename":"01_README.txt","contentType":"text/plain","friendlyType":"Plain Text","filesize":3750,"description":"Complete dataset description and user guide","storageIdentifier":"s3://dvn-cloud:19a76b6320b-d4876e2ffd92","rootDataFileId":-1,"md5":"e49479ec11909461863c4daac3dbfb42","checksum":{"type":"MD5","value":"e49479ec11909461863c4daac3dbfb42"},"tabularData":false,"creationDate":"2025-11-12","publicationDate":"2025-11-12","lastUpdateTime":"2025-11-12T16:15:56Z","fileAccessRequest":true}},{"description":"This code implements the Universal Adaptive Normalization Scale (AMIS). \nAMIS is designed for transforming and normalizing heterogeneous data based on adaptive partitioning of the measurement range into multiple intervals using statistical characteristics of the sample. 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Excel file containing raw data on nominal GDP of countries worldwide for 2024\n   - Source:World Bank Open Data, indicator \"GDP (current US$)\"\n   - Source link: https://data.worldbank.org/indicator/NY.GDP.MKTP.CD\n   - Used to demonstrate AMIS effectiveness on data with extreme distribution asymmetry","storageIdentifier":"s3://dvn-cloud:19a76ae7ecf-2ab9ef6686b8","rootDataFileId":-1,"md5":"26027d16af8788d3ecd66388f1813ca8","checksum":{"type":"MD5","value":"26027d16af8788d3ecd66388f1813ca8"},"tabularData":false,"creationDate":"2025-11-12","publicationDate":"2025-11-12","lastUpdateTime":"2025-11-12T16:15:56Z","fileAccessRequest":true}}],"citation":"Kravtsov, Gennady, 2025, \"Data and Code for: \"Universal Adaptive Normalization Scale (AMIS): Integration of Heterogeneous Metrics into a Unified System\"\", https://doi.org/10.7910/DVN/BISM0N, Harvard Dataverse, V1"}}