Data Harmonization Platform

Harmonize your heterogeneous data with IDS

IDS, Intermediate Data Schema, is an intuitive and powerful data modeling framework to harmonize your heterogeneous R&D data.

Whether CRO report, HPLC injection, plate reader runs or any other data sets, harmonize them into vendor-neutral and data science compatible formats. Connect data across heterogeneous sources and targets at enterprise-scale, leveraging the open data format of choice for data science and big data applications. Quickly define your data validation rules, indexing, partition and embed ontologies of your choice.

How it Works

Select from the TetraScience library or create your own.

Automatically harmonize R&D data to vendor agnostic open data format.

Automatically prepare the data for queries from big data tools like Elasticsearch, Python/R, Spark, Presto, Pandas, Streamlit.

Automatically convert IDS files to other formats of your choice, such as Allotrope Data Format with the Tetra File Converter Application.

Built for Enterprise

Built-In Library

The Tetra Data Platform provides an intuitive, queryable data catalogue of harmonized data for common R&D data types with versioning.

Open Framework and Tooling

IDS is an open framework, with detailed documentation; or, build your own IDS specific to your needs. Comprehensive tooling provides programmatic validation, browse, sharing and publish mechanisms.

Ready to Query

Harmonized IDS files get automatically prepared for query, enabling flexible and powerful search, filter, aggregations and queries.

Future-Proof

IDS files are easy to read, write and consume out-of-the-box, and compatible with big data and web applications. Automated file conversion further transforms data to industry standards.

By clicking “Accept All Cookies”, you agree to the storing of cookies on your device to enhance site navigation, analyze site usage, and assist in our marketing efforts. View our Privacy Policy for more information.

Preferences Deny Accept

Transform and Harmonize Your Scientific Data

Make data findable, accessible, interoperable, and reusable (FAIR)