Urban Weather Database Integration via Python Standardization
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
The existing urban weather observation networks in Korea face challenges in accessing and utilizing overall urban weather data due to differences in data types and formats, making it difficult to analyze and predict urban meteorological phenomena effectively.
Innovation Solution
A Python-based integrated management method for constructing an urban customized weather database, which involves storing raw data from various networks in a predetermined format, extracting relevant data, masking invalid values, and creating a unified database for easy access and analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If data from multiple urban weather observation networks are collected and stored in different formats, then the quantity of weather data increases, but the difficulty of data access and utilization increases
Solution Approach 1:
The patent merges data from multiple urban weather observation networks (RWI, SEB, IMS, UBG) into a unified database structure. By combining previously separate data sources into a single integrated system, the patent enables centralized access to all weather data while maintaining the diversity and quantity of original data sources.
Solution Approach 2:
The patent creates a universal database structure that can accommodate multiple types of weather observation data from different networks. The unified format serves multiple functions: storing diverse data types, enabling consistent access methods, and supporting various analysis requirements simultaneously.
2Adaptability or versatility
If data from different observation networks are stored with different formats and contents, then the adaptability of the system to various networks is maintained, but the complexity of data management increases
Solution Approach 1:
The patent applies parameter changes by transforming diverse data formats into a unified structure. The standardized database format converts varying data parameters from different networks into consistent fields, enabling uniform processing while preserving the original data characteristics through structured transformation.
3Reliability
If raw data from multiple networks are stored without standardization, then the original data characteristics are preserved, but the precision of weather analysis decreases
Solution Approach 1:
The patent performs preliminary standardization actions on raw data before storage. By pre-processing and formatting data according to a unified structure before it enters the database, the system maintains original data characteristics while preparing them for precise analysis, eliminating the need for repeated formatting operations.
Data Source
AI summary
Disclosed is a Python-based integrated management method of an urban customized weather database for constructing urban weather observation data as an integrated database. The method includes the steps of: storing raw urban weather observation data collected from a plurality of urban weather observation networks as first files of a predetermined format according to an order of observation time at each observation point of the urban weather observation networks; extracting data of each observation point of the urban weather observation networks from the stored first files according to the order of observation time, for a predetermined weather element and analysis period; masking observation values belonging to a predetermined masking condition, among observation values included in the extracted data; and storing the masking-processed data as a second file.