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Commercial
Materials Platform for Data Science (MPDS) Dataset
Highly curated inorganic materials dataset with a 30-year track record, built from about half a million scientific publications and powering several commercial products. It integrates data from 405,100 publications, linking 139,005 phase diagrams, 409,771 crystalline nanostructures, and 1,075,676 physical property sets into 189,682 materials phases, making it a comprehensive materials platform for data science and a valuable materials project database.
-
- Publications
- 405,100
-
- Phase diagrams
- 139,005
-
- Crystalline nanostructures
- 409,771
-
- Property sets
- 1,075,676
-
- Material phases
- 189,682
- Materials Science
- Chemistry
- Physics
- Data Science
- Machine Learning
- Materials Science
- Chemistry
- Physics
- Data Science
- Machine Learning
Highly curated inorganic materials dataset with a 30-year track record, built from about half a million scientific publications and powering several commercial products. It integrates data from 405,100 publications, linking 139,005 phase diagrams, 409,771 crystalline nanostructures, and 1,075,676 physical property sets into 189,682 materials phases, making it a comprehensive materials platform for data science and a valuable materials project database.
- Materials Science
- Chemistry
- Physics
- Data Science
- Machine Learning
-
- Publications
- 405,100
-
- Phase diagrams
- 139,005
-
- Crystalline nanostructures
- 409,771
-
- Property sets
- 1,075,676
-
- Material phases
- 189,682
Dataset Info
| Characteristic | Data |
| Description | Inorganic materials with a 30-year history, powering academic research and commercial applications |
| Data types | Relational SQL database, JSON export |
| Tasks | Academic and industrial R&D, materials discovery, ML modeling |
| Labeling | 100+ categories: elements, formulas, properties, symmetry, etc. |
| Language | Controlled scientific English |
Technical
Characteristics
| Characteristic | Data |
| Format | JSON, schema |
| Searchable fields | Physical properties, chemical elements, material classes, crystal system, formula, space group, etc. |
Dataset Use Cases
FAQs
Can I request a sample of the MPDS dataset before purchasing?
Yes. Free samples are available so researchers can review data quality, schema structure, and searchable material properties. This allows evaluation of compatibility with analytics platforms, learning models, and scientific research workflows.
What types of annotations and metadata are provided?
The dataset contains over 100 standardized metadata categories, including elements, formulas, symmetry, space groups, and physical properties. These annotations enable structured querying, materials informatics analysis, and model training.
What data formats are available in the MPDS dataset?
Data is available as a relational SQL database with JSON exports and a defined schema.
What language and terminology does the dataset use?
The dataset uses controlled scientific English and standardized materials science terminology. This consistency improves interoperability with research software and reduces ambiguity during data analysis.
Why is this materials dataset valuable for AI-driven materials discovery?
The dataset combines 30 years of expert curation with information extracted from approximately 405,100 scientific publications, creating a reliable foundation for materials discovery, machine learning, and computational materials science. Its consistent structure and extensive coverage make it suitable for developing predictive AI models for inorganic materials.
How was the data collected and curated?
Data has been manually curated by domain experts from peer-reviewed publications for over 30 years. This expert-driven process ensures high data quality, consistency, and reliability for scientific research and engineering applications.
How are Unidata datasets licensed?
Unidata follows a dual-licensing model. Free samples are provided for testing and evaluation, while full datasets are available exclusively through purchase.
Do Unidata datasets comply with GDPR and data privacy regulations?
Yes. All datasets are curated in compliance with GDPR and applicable data protection laws. Data is sourced from legally permissible and ethical scientific publications.
How are Unidata datasets stored and managed?
All datasets are securely stored on AWS cloud infrastructure and managed according to ISO 27001 and ISO 27701 standards. This ensures secure access, scalability, and long-term reliability of materials databases.
Still have questions about using Unidata datasets?
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