Laboratory Experiment Data Visualization with Machine-Readable Protocols
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Solution Overview
Problem
Current laboratory systems lack the ability to integrate and automate multi-technique, multi-instrument, multi-platform research projects due to the lack of machine-readable experimental protocols, leading to incomplete data analysis and inability to link experimental protocols with data, making it impossible to implement a flexible and scalable general experimentation system.
Innovation Solution
A system is provided with a processor, memory, and program code that includes modules for storing experimental parameters, instrument information, environmental conditions, and data visualization, allowing for integrated laboratory experiment design, adjustment, scheduling, compilation, execution, analysis, and visualization, with support for structured input of experiment specifications using a programming language.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If free text is used to store experimental protocols, then ease of operation is improved, but machine parsability and validation capability deteriorate
Solution Approach 1:
The patent transforms experimental protocols from unstructured free text into structured data with defined parameters and metadata fields. This parameterization enables machine parsing and validation while preserving ease of use through standardized input forms that guide users in entering experimental information systematically.
Solution Approach 2:
The patent introduces an intermediary layer of structured metadata and protocol descriptions that bridge between user-friendly input and machine-processing requirements. This intermediary structure allows the system to both accept easy user input and generate machine-parsable output for validation and integration.
2Adaptability or versatility
If a generalized experimentation platform is designed to accommodate nearly exponentially many combinations of techniques and parameters, then adaptability is improved, but device complexity increases
Solution Approach 1:
The patent creates a universal experimentation platform where a single system can handle diverse experimental techniques and parameters through standardized data structures and metadata schemas. This universal framework allows the system to adapt to many different experiment types without requiring separate specialized systems for each technique.
Solution Approach 2:
The patent segments the experimentation platform into modular components: protocol definitions, parameter specifications, metadata structures, and data integration layers. This segmentation allows complex experimental combinations to be managed through composed modular elements rather than monolithic complexity.
3Ease of operation
If experimental protocols are not specified in machine-readable form, then ease of operation is improved, but the ability to programmatically validate and link protocol information with data deteriorates
Solution Approach 1:
The patent changes the representation of protocols from free text to parameterized structured data with defined schemas. This transformation enables programmatic validation of protocol completeness and correctness while maintaining user-friendly interfaces through standardized input forms and templates.
Solution Approach 2:
The patent implements feedback mechanisms where the system validates protocol information against predefined schemas and provides immediate feedback to users about completeness and correctness. This feedback loop ensures reliability through automated validation while keeping the system easy to use by guiding users through required information entry.
Data Source
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AI summary
The disclosure provides systems and methods for data analysis of experimental data. The analysis can include reference data that are not directly generated from the present experiment, which reference data may be values of the experimental parameters that were either provided by a user, computed by the system with input from a user, or computed by the system without using any input from a user. Another example of such reference data may be information about the instrument, such as the calibration method of the instrument.