{"@context":{"@language":"en","@vocab":"https://schema.org/","citeAs":"cr:citeAs","column":"cr:column","conformsTo":"dct:conformsTo","cr":"http://mlcommons.org/croissant/","rai":"http://mlcommons.org/croissant/RAI/","data":{"@id":"cr:data","@type":"@json"},"dataType":{"@id":"cr:dataType","@type":"@vocab"},"dct":"http://purl.org/dc/terms/","examples":{"@id":"cr:examples","@type":"@json"},"extract":"cr:extract","field":"cr:field","fileProperty":"cr:fileProperty","fileObject":"cr:fileObject","fileSet":"cr:fileSet","format":"cr:format","includes":"cr:includes","isLiveDataset":"cr:isLiveDataset","jsonPath":"cr:jsonPath","key":"cr:key","md5":"cr:md5","parentField":"cr:parentField","path":"cr:path","recordSet":"cr:recordSet","references":"cr:references","regex":"cr:regex","repeated":"cr:repeated","replace":"cr:replace","sc":"https://schema.org/","separator":"cr:separator","source":"cr:source","subField":"cr:subField","transform":"cr:transform","wd":"https://www.wikidata.org/wiki/"},"@type":"sc:Dataset","conformsTo":"http://mlcommons.org/croissant/1.0","name":"Data and Code for: "Universal Adaptive Normalization Scale (AMIS): Integration of Heterogeneous Metrics into a Unified System"","url":"https://doi.org/10.7910/DVN/BISM0N","creator":[{"@type":"Person","givenName":"Gennady","familyName":"Kravtsov","affiliation":{"@type":"Organization","name":"Research Center for Applied Statistics"},"name":"Kravtsov, Gennady"}],"description":"Dataset Title: Data and Code for: \"Universal Adaptive Normalization Scale (AMIS): Integration of Heterogeneous Metrics into a Unified System\" Description: This 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. Contents: - Source data: educational grades and GDP statistics - AMIS normalization results (3, 5, 9, 17-point models) - Comparative analysis with linear normalization - Ready-to-use Python code for data processing Applications: - Educational data normalization and analysis - Economic indicators comparison - Development of unified metric systems - Methodology research in data scaling Technical info: Python code with pandas, numpy, scipy, matplotlib dependencies. Data in Excel format.","keywords":["Computer and Information Science","Social Sciences","data normalization","adaptive scaling","educational analytics","metric integration","heterogeneous data","statistical distribution","Python implementation","educational assessment","GDP analysis","AMIS"],"license":"http://creativecommons.org/publicdomain/zero/1.0","datePublished":"2025-11-12","dateModified":"2025-11-12","includedInDataCatalog":{"@type":"DataCatalog","name":"Harvard Dataverse","url":"https://dataverse.harvard.edu"},"publisher":{"@type":"Organization","name":"Harvard Dataverse"},"version":"1.0","citeAs":"@data{DVN/BISM0N_2025,author = {Kravtsov, Gennady},publisher = {Harvard Dataverse},title = {Data and Code for: \"Universal Adaptive Normalization Scale (AMIS): Integration of Heterogeneous Metrics into a Unified System\"},year = {2025},url = {https://doi.org/10.7910/DVN/BISM0N}}","citation":[{"@type":"CreativeWork","name":"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"}],"distribution":[{"@type":"cr:FileObject","@id":"01_README.txt","name":"01_README.txt","encodingFormat":"text/plain","md5":"e49479ec11909461863c4daac3dbfb42","contentSize":"3750","description":"Complete dataset description and user guide","contentUrl":"https://dataverse.harvard.edu/api/access/datafile/13147777"},{"@type":"cr:FileObject","@id":"AMIS_Data_Normalization_Converter_EN.py","name":"AMIS_Data_Normalization_Converter_EN.py","encodingFormat":"text/x-python","md5":"a9e2e8010cce9e97574734487f9924bd","contentSize":"7824","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. This enables more accurate and flexible scaling compared to conventional linear normalization.","contentUrl":"https://dataverse.harvard.edu/api/access/datafile/13147775"},{"@type":"cr:FileObject","@id":"AMIS_Normalization_Demonstration_GDP_2024_Countries_EN.xlsx","name":"AMIS_Normalization_Demonstration_GDP_2024_Countries_EN.xlsx","encodingFormat":"application/vnd.openxmlformats-officedocument.spreadsheetml.sheet","md5":"42bf8f2fbc125a054ab326bdd0628246","contentSize":"32411","description":"AMIS_Normalization_Demonstration_GDP_2024_Countries.xlsx\n   - Excel file containing results of GDP data normalization using AMIS method and statistical analysis\n   - Includes comparison of various AMIS models (3, 5, 9, 17 points) with linear normalization","contentUrl":"https://dataverse.harvard.edu/api/access/datafile/13147776"},{"@type":"cr:FileObject","@id":"Student_Grades_History_Grade11_Raw_Data.xlsx","name":"Student_Grades_History_Grade11_Raw_Data.xlsx","encodingFormat":"application/vnd.openxmlformats-officedocument.spreadsheetml.sheet","md5":"7cbf3024d505e07781c785be25056217","contentSize":"22434","description":"Student_Grades_History_Grade11_Raw_Data.xlsx\n   - Excel file containing raw data (average class grades) for History, Grade 11\n   - Used to demonstrate classical AMIS model with empirically determined boundaries\n   - Volume: 879 records","contentUrl":"https://dataverse.harvard.edu/api/access/datafile/13147770"},{"@type":"cr:FileObject","@id":"Student_Grades_History_Grade11_Raw_Data_all_values.xlsx","name":"Student_Grades_History_Grade11_Raw_Data_all_values.xlsx","encodingFormat":"application/vnd.openxmlformats-officedocument.spreadsheetml.sheet","md5":"8201aa4f5de6648a94b858b5192ffa89","contentSize":"63141","description":"Student_Grades_History_Grade11_Raw_Data_all_values.xlsx\n    - Excel file containing AMIS normalization results for History, Grade 11 data\n    - Demonstrates **classical AMIS** with empirically determined boundaries\n    - Contains original grades and converted values using 3, 5, 9, 17-point AMIS models","contentUrl":"https://dataverse.harvard.edu/api/access/datafile/13147773"},{"@type":"cr:FileObject","@id":"Student_Grades_Literature_Grade9_Raw_Data.xlsx","name":"Student_Grades_Literature_Grade9_Raw_Data.xlsx","encodingFormat":"application/vnd.openxmlformats-officedocument.spreadsheetml.sheet","md5":"3c1b71178b0f5857f1488c992a1eb13b","contentSize":"46238","description":"Student_Grades_Literature_Grade9_Raw_Data.xlsx\n   - Excel file containing raw data (average class grades) for Literature, Grade 9\n   - Used to demonstrate AMIS with fixed boundary values (range [2, 5])\n   - Volume: 1,379 records","contentUrl":"https://dataverse.harvard.edu/api/access/datafile/13147771"},{"@type":"cr:FileObject","@id":"Student_Grades_Literature_Grade9_Raw_Data_all_values.xlsx","name":"Student_Grades_Literature_Grade9_Raw_Data_all_values.xlsx","encodingFormat":"application/vnd.openxmlformats-officedocument.spreadsheetml.sheet","md5":"79b0fc7b32ccb53b66fc7e058498657e","contentSize":"94610","description":"Student_Grades_Literature_Grade9_Raw_Data_all_values.xlsx\n    - Excel file containing AMIS normalization results for Literature, Grade 9 data\n    - Demonstrates AMIS with fixed boundary values (range [2, 5])\n    - Contains original grades and converted values using 3, 5, 9, 17-point AMIS models","contentUrl":"https://dataverse.harvard.edu/api/access/datafile/13147772"},{"@type":"cr:FileObject","@id":"World_Bank_Nominal_GDP_All_Countries_2024.xlsx","name":"World_Bank_Nominal_GDP_All_Countries_2024.xlsx","encodingFormat":"application/vnd.openxmlformats-officedocument.spreadsheetml.sheet","md5":"26027d16af8788d3ecd66388f1813ca8","contentSize":"16577","description":"World_Bank_Nominal_GDP_All_Countries_2024.xlsx\n   - 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","contentUrl":"https://dataverse.harvard.edu/api/access/datafile/13147774"}]}