Rubicon has been designed to enable high performing laboratories. It connects laboratory instruments and scientific desktop computers to high performance services such as a secure shared data repository and platform independent visualization. Rubicon expands the capabilities of a standard office network to meet the challenges of current laboratory instrumentation, data generation and data analysis; and provides easy access to data while actively managing user security and data integrity. Rubicon can also automatically convert a range of proprietary data file formats into open, standard formats for visualization, data mining and long term access.
Rubicon has three main components: the Repository, the Data Archiver, and Data Analysis.
Rubicon uses a leading-edge approach to meta-data by storing property-type-value tuples to annotate data stored in the repository. Unlike competing products, Rubicon does not force a particular metaphor or paradigm on users - users build an ontology to describe their data and use the ontology to search and retrieve data items.
| Product Component |
Description |
Requirements Delivered |
| Data Archiver |
An automated data sweeping application that transfers data to the repository |
- Sweeps data locations for new data items
- Applies tracking terms to data
- Converts data from proprietary to open format
- Computes digital signatures
- Executes data transfer to repository
|
| Repository |
A server application which provides security, data integrity, storage, searching and retrieval. |
- Manages users and security
- Makes storage system transparent to the user
- Manages tracking term definitions for each group
- Provides a web-service interface to storage
- Provides a web-browser interface
|
| Data Analysis |
"RDE": A data analysis and project packaging application. |
- Data visualization from open-format data
- Quantitative data analysis
- Quantitative calibration
- Organizes raw and processed data with processing methods and associated files.
|
The Data Archiver performs several key functions: (i) It applies search terms to all data being moved to the repository; (ii) It converts selected proprietary data into an open format; (iii) It computes digital signatures on data to be moved to the repository; (iv) It performs the data transfer to the repository. The operations of the Data Archiver can be triggered via a schedule or an event on the instrument (such as the completion of a batch).
The Repository holds both open and proprietary format files from the instrument. Open format files are used for further processing by vendor-independent quantitative analysis tools. Proprietary files are stored for reuse in related acquisition projects. Using a web browser interface, converted raw data can be visualized and processed directly in the vendor-neutral format using an application called the Data Explorer. Instrument-specific files can also be located using a web browser and loaded onto any instrument data system regardless of operating system or hardware.
The repository is a web-service application which provides both client-server interaction as well as a web-browser interface. The web-application uses a database to store search terms, user credentials, and group information. The web-application requires access to bulk storage to store data sent from the Data Archiver. The bulk storage can be one of several types including database storage, file storage or a content addressable storage system.
The purpose of the web-application is to create a layer between the user and the physical storage. Users interact with the application to gain access to data rather than the physical storage directly. This gives the IT group responsible for storage flexibility in provisioning storage and provides a fixed logical location for all data items in the organization.
To aid in managing data integrity, the Repository checks the digital signature sent by the Data Archiver before it enters data into the Repository.
RDE performs all calculations needed to produce results from raw data. To ensure long-term access and stability, the Data Explorer is designed to perform all numerical calculations in a virtual environment. The virtual environment controls precision and rounding direction for all floating-point calculations. It also allows the exact version of an algorithm to be re-executed when reanalysis is required and exact numerical reproducibility is required.
The basic methods used in quantitative analysis by HPLC and mass spectrometry in bioanalytical laboratories include: chromatogram specification and visualization and chromatographic peak identification, peak integration and normalization; calibration via regression and data reporting.
RDE generates export files needed to load data into systems such as a LIMS for inclusion in formatted results spreadsheets and project reports. The Data Explorer packages result files with raw data and makes them available to anyone given access to the project file.
