All Resources - PSDI What We Provide
All Resources
A complete list of resources provided by PSDI - including data sources, services, tools and guidance.
You can narrow down the list of resources on this page by selecting from the filters on the left. Click on a resource of interest to find out more about it, access the resource landing page, and to access related resources in the same Resource Theme for those that have one.
Cambridge Structural Database (CSD)
The Cambridge Structural Database (CSD), maintained by the Cambridge Crystallographic Data Centre (CCDC), is the world's largest curated collection of experimentally determined crystal structures, containing more than 1.3 million accurate 3D structures derived from X ray, neutron, and electron diffraction analyses. It is widely used across research and industry including pharmaceuticals, agrochemicals, and fine chemicals, to support structure prediction, materials design, and data driven discovery. Within PSDI, access to the CSD is available to authenticated users from the UK academic community. Users can search the CSD through the Find a Substance option in the PSDI Cross Data Search service or via the dedicated webCSD interface. CSD software tools are also available through PSDI's Remote Desktop Access. Use the Visit or resource landing page link to search the CSD via PSDI Cross Data Search, and see Linked Resources for links to webCSD and CSD software. Find out more using the links in the Further Information section.
Chemical Availability Search (ChASe)
The Chemical Availability Search (ChASe) data source enables users to search and compare commercially available chemicals using the PSDI Cross Data Search service. Enter product or vendor keywords, CAS number, InChI or SMILES to search pricing and supplier information for over 250,000 unique chemicals from UK suppliers. Search results include product name, supplier name, quantity, purity, prices, CAS number, and catalogue number with a link to the supplier's website.
Check the supplier's website for the most up to date product information.
CSD Software (Remote Desktop Access)
The Cambridge Structural Database (CSD), maintained by the Cambridge Crystallographic Data Centre (CCDC), is the world's largest curated collection of experimentally determined crystal structures, containing more than 1.3 million 3D structures derived from X ray, neutron, and electron diffraction studies. It is widely used across research and industry to support structure prediction, materials design, and data driven discovery. Through PSDI, authenticated users from the UK academic community can access a Remote Desktop environment that provides CCDC software for searching, visualising, and analysing CSD data. The available tools include ConQuest for searching and retrieving CSD entries; Mercury for 3D structure visualisation and analysis, and Mogul for exploring preferred molecular geometries within the CSD; and the now deprecated PreQuest. Use the Visit or resource landing page link for guidance on requesting or obtaining help with access to the CSD Software (Remote Desktop Access) service. See Linked Resources for access to the CSD via the PSDI Cross Data Search service.
Metadata Guidance
This topic collection provides an introduction to metadata and standards, and why they are important for research data. This topic collection also provides information about how PSDI uses metadata to manage and describe our resources, including the terminology used in PSDI; an overview of the PSDI metadata profiles available, vocabulary descriptions, and guidelines for using PSDI metadata.
Propersea (Property Prediction)
Propersea contains calculated predictions for a wide range of molecular and physicochemical properties for small molecules, such as melting and boiling points, density, solubility, polarizability, and more. It employs various algorithms, including RDKit, semi-empirical quantum methods, Bayesian regression trees, and transformer neural networks. Propersea also contains predicted IUPAC names generated using a machine learning model. Propersea can be searched using the PSDI Cross Data Search service using InChIs, SMILES or by drawing a molecule. Results include predicted values, confidence intervals and reliability scores for the prediction.
PSDI Community Data Collections
PSDI Community Data Collections is a collaborative, subject-focused research data repository within the Physical Sciences Data Infrastructure (PSDI). It provides openly accessible datasets, currently serving the BioSim and Data to Knowledge communities, to facilitate the publication, sharing, discovery, and reuse of valuable data. The repository adheres to FAIR principles by implementing a comprehensive metadata schema that incorporates both standard properties and custom fields tailored to scientific needs. Metadata and full datasets are freely available to all users, and plans are in place to expand PSDI Community Data Collections by including additional relevant scientific communities in the future.
PSDI Cross Data Search
The PSDI Cross Data Search service enables users to search for data across data sources provided by PSDI and other relevant data sources from the wider community using our online interface. The service provides a number of different ways to perform a search, for example searching substances by chemical formula, name, or number of elements, with the option to refine searches using a periodic table interface. Specialised searches can also be performed for molecules using molecular structures, crystalline forms, or specific symmetry or periodicity characteristics. There is also an advanced search option, enabling custom queries to be constructed for users who know which fields in the data sources they want to search. The search results provide both a summary of the data and links to the source of the data. Although the majority of data sources are completely open, authentication may be required for some data sources.
PSDI Data Conversion Command Line Application
PSDI Data Conversion is your one stop shop for file format conversion. This enables users to seamlessly convert between different file formats and view information about the quality of the proposed conversion. The PSDI Command Line interface for Data Conversion application can be installed and run on your own computing infrastructure. It contains all of the same file conversion functionality of our online service but without the need to upload your data to PSDI and without any restrictions on file sizes.
PSDI Data Conversion Python Library
PSDI Data Conversion is your one stop shop for file format conversion. This enables users to seamlessly convert between different file formats and view information about the quality of the proposed conversion. The PSDI Python Library for Data Conversion is available via PyPi and can be installed and run on your own computing infrastructure, enabling you to include a data conversion in your own pipelines. It contains all of the same file conversion functionality of our online service but without the need to upload your data to PSDI and without any restrictions on file sizes.
PSDI Data Conversion Python/Flask Application
PSDI Data Conversion is your one stop shop for file format conversion. This enables users to seamlessly convert between different file formats and view information about the quality of the proposed conversion. The PSDI Python/Flask application for Data Conversion can be installed and run on your own computing infrastructure using the Flask framework. It contains all of the same file conversion functionality of our online service, complete with a graphical user interface, but without the need to upload your data to PSDI and without any restrictions on file sizes.
PSDI Data Conversion Service
The PSDI Data Conversion Service is your one stop shop for file format conversion. This online service enables users to seamlessly convert between different file formats and view information about the quality of the proposed conversion. Users can explore possible conversions, identify compatible formats for their data, and access details about the available converters that have been tested and ranked using comprehensive quality measures. While many conversions can be handled directly through the service, users will be guided to external tools for conversions not supported within the platform.
PSDI Data Revival Service
The majority of laboratories and research groups have stacks of paper notebooks filled with valuable data that is difficult and time-consuming to access and use. Data Revival is an AI-driven service that can seamlessly convert your handwritten lab book pages into machine-readable data, unlocking the potential of your chemistry data. Operating with a high degree of accuracy, Data Revival creates relational links across your chemical data and enables users to run semantic searches across potentially millions of data points, including complex chemical structures. PSDI offers users the chance to experience Data Revival's capabilities firsthand.
PSDI Interactive Learning (Moodle)
A range of interactive, self-paced learning modules provided by PSDI.
PSDI Knowledge Base
The PSDI Knowledge Base serves as a comprehensive resource for physical scientists and research support staff, offering guidance on a variety of themes related to research data, PSDI technologies and related resources. It also provides centralized access to a variety of training and learning, including self-paced courses, tutorials, webinar recordings, and in-person sessions such as workshops and summer schools. Additionally, the Knowledge Base offers technical support resources, including FAQs to address common challenges, guidance on how to contact us, and how to raise a support request if you can't find an answer to your question.
PSDI Resources Guidance
This collection of topics provides guidance about selected resources provided by PSDI and how to use them.
Research Data Management Guidance
This collection of topics provides an introduction to research data management, including a discussion of different research data types, how to identify your own research data, and creating a data inventory. Guidance is provided on the different stages of the research data lifecycle and the benefits of data management planning, and the role of the Data Management Plan (DMP) together with an example DMP for physical scientists. This section also includes topics on best practices for managing data when working with others, and where you can get additional help with managing your research data.
Sharing Data and FAIR Guidance
This collection of topics provides guidance on good practices for sharing your research data. This section introduces the FAIR principles and their importance, and provides step by step guidance on what is needed to make your research data and related outputs such as code and methods findable, accessible, interoperable, and reusable, whether or not you share them publicly. Guidance is given on choosing and writing licenses for your data, creating a data package to share or archive, and considerations for choosing a repository.
Web Access to Cambridge Structural Database (webCSD)
The Cambridge Structural Database (CSD), maintained by the Cambridge Crystallographic Data Centre (CCDC), is the world's largest curated collection of experimentally determined crystal structures, containing more than 1.3 million 3D structures derived from X ray, neutron, and electron diffraction studies. It is widely used across research and industry to support structure prediction, materials design, and data driven discovery. Through PSDI, authenticated users from the UK academic community can search the CSD using the dedicated webCSD service interface. Use the Visit or resource landing page link to search the CSD using the dedicated webCSD service. Use the Visit or resource landing page link for guidance on requesting or obtaining help with access to the webCSD service. See Linked Resources for access to the CSD via the PSDI Cross Data Search.
Web Access to Inorganic Crystal Structure Database (ICSD Web)
The Inorganic Crystal Structure Database (ICSD), maintained by FIZ Karlsruhe, is the world's largest collection of fully identified inorganic crystal structures, containing more than 325,000 entries. It includes experimentally determined inorganic and organometallic structures as well as theoretically calculated inorganic structures, and also provides simulated powder diffraction data. Each record contains rich structural information, including unit cell parameters, space group, full atomic coordinates, site occupation factors, Wyckoff positions, molecular and ANX formulas, molecular weight, and mineral group. Access to ICSD through PSDI is available to authenticated users within the UK academic community. The search interface provides a set of tools designed to support efficient discovery and analysis of crystal structure data. Its capabilities include an intuitive search environment, extensive structure type classifications that can be queried using descriptive parameters, and structure standardisation features that make comparison across entries straightforward. Users can explore structures through advanced visualisation and analysis tools, generate and manipulate simulated powder diffraction patterns, and manage queries through a simple but flexible interface. Direct links to the original literature are also provided via an OpenURL server.
AI Ready Datasets
AI ready datasets give physical sciences researchers data they can trust and reuse. These AI-Ready datasets are hosted as a PSDI Community Data Collection and are designed to support AI and machine learning workflows, ranging from general purpose collections that researchers can shape for their own models, to task-specific datasets that already include annotations and predefined training, validation, and test splits. Every record includes one or more datafiles accompanied by a Croissant format metadata description (https://mlcommons.org/working-groups/data/croissant/), ensuring that structure, provenance, and context are captured in a machine readable way.
Amber Plugin for AiiDA
The Amber plugin for AiiDA aims to enable the capture and sharing of the full provenance of data when parameterising and running molecular dynamics simulations.
BioSimDB (Biomolecular Simulations Database)
Topology, trajectory, and AiiDA data provenance files from molecular dynamics simulations of biomolecules are stored in a repository specifically designed for their preservation and accessibility.
Catalysis Data Infrastructure (CDI) Bibliographic Data Web Service
The data of the community portal is accessible programmatically through custom web services (API calls). Each entity can respond to call with JSON data which can be used to create custom views or feed third party applications. For example, the UK catalysis hub uses a web service that delivers filtered bibliographic lists of publications, is used to populate the publications pages on its website and to generate custom reports. We can assist in developing tailored services to meet specific community requirements.
Catalysis Data Infrastructure (CDI) Data Objects
The Catalysis Data Infrastructure (CDI) Data Objects resource provides access to the UK Catalysis Hub (UKCH) published data objects that support research outputs. Through the CDI Portal and the PSDI Cross Data Search, users can search, explore, and reuse these data resources.
In the Catalysis Data Infrastructure (CDI) knowledge graph, data objects are linked with researchers, institutions, publications, and research themes, fostering data discovery, highlighting collaborations, and supporting analysis of data-driven research. CDI Data Objects can be extended to include domain-specific data resources such as chemical entities, materials, or analytical methods.
Catalysis Data Infrastructure (CDI) Portal
The deployed Thematic Portal for the UK Catalysis Hub (CDI) offers summary reports on publications and research impact within this important scientific domain. It provides insights into publications, authors, institutions, top researchers, countries, and themes, while tracking changes over time to identify research trends. This use case illustrates how thematic portals can showcase research productivity, emphasize emerging trends, and simplify access to supporting data.
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