Sustainability Data Hub for Standardizing Multi-Provider Waste Data
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Solution Overview
Problem
Organizations lack comprehensive tools for aggregating, standardizing, and analyzing waste and recycling data across multiple service providers to set science-based sustainability goals and report accurately to regulatory bodies, facing challenges in data format inconsistencies and benchmarking.
Innovation Solution
A system and method for collecting, converting, and standardizing waste and recycling data through a sustainability data hub, enabling real-time data aggregation, normalization, and generation of decision support models, using standardized formats and protocols to facilitate accurate reporting and benchmarking.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If data is collected from multiple service providers in various formats, then data coverage and comprehensiveness are improved, but data format inconsistencies and standardization difficulties increase
Solution Approach 1:
The patent introduces a centralized data hub as an intermediary component that receives data from multiple waste management service providers in various formats and converts it into standardized formats. This mediator handles the complexity of format conversion internally, allowing organizations to benefit from comprehensive multi-source data without directly managing the standardization complexity.
Solution Approach 2:
The system applies parameter changes by transforming data from various source formats into standardized formats through automated conversion processes. The data hub modifies data parameters (formats, structures, schemas) to ensure consistency across multiple providers while maintaining the original data's informational content and integrity.
2Measurement precision
If comprehensive waste performance data is aggregated across multiple providers, then decision support model accuracy is improved, but data aggregation and processing complexity increase
Solution Approach 1:
The patent merges data from multiple waste management service providers into a unified data structure within the centralized hub. This combining process integrates disparate data sources while applying standardization rules, enabling accurate decision support models without requiring organizations to manually manage the complexity of aggregating data from multiple providers.
Solution Approach 2:
The data hub performs self-service by automatically executing data aggregation, validation, and standardization processes without requiring manual intervention. The system autonomously handles the complexity of data processing across multiple providers, delivering ready-to-use standardized data for decision support modeling.
3Speed
If real-time data access is provided to multiple parties, then reporting speed and responsiveness are improved, but data security and access control requirements increase
Solution Approach 1:
The patent segments data access permissions by implementing role-based access control that divides the centralized data hub into multiple access levels. Different parties (organizations, service providers, regulators) receive tailored access to specific data subsets relevant to their needs, enabling real-time reporting while maintaining security through granular permission management.
Solution Approach 2:
The centralized data hub acts as a secure intermediary that manages real-time data distribution to multiple authorized parties. It implements security protocols and access control mechanisms internally, allowing fast data access for reporting purposes while protecting sensitive information through controlled dissemination channels.
Data Source
AI summary
A system and method for collecting and standardizing data related to the management of waste and recyclable materials are provided. The system and method can be utilized to aggregate, analyze, display and distribute relevant sustainability decision support models, data and metrics. The system and method can also include collecting, converting and standardizing of waste and/or recycling data and developing sustainability decision models and reporting.