datalab

Attributes
DescriptionThe main aim of datalab is to provide a platform for capturing the significant amounts of long-tail experimental data and metadata produced in a typical lab, and enable storage, filtering and future data re-use by humans and machines. The platform provides researchers with a way to record sample- and cell-specific metadata, attach and sync raw data from instruments, and perform analysis and visualisation of many characterisation techniques in the browser (XRD, NMR, electrochemical cycling, TEM, TGA, Mass Spec, Raman). Importantly, datalab stores a network of interconnected research objects in the lab, such that individual pieces of data are stored with the context needed to make them scientifically useful.
Providerdatalab industries ltd., Matgenix SRL., University of Cambridge
Information on ProviderDeveloped as an academic project at the University of Cambridge, additionally supported by consultancy work via datalab industries ltd. and Matgenix SRL.
URL https://datalab-org.io
Activity Statusactive
Information on Activev0.6.0 (June 2025)
Last checked on
Provider's data safety and data security strategiesPlatform is intended to be self-hosted for/by specific research groups. System requires OAuth login via ORCID or GitHub (with allow lists) with restrictive permissions by default.
Reference usersProf Joshua Bocarsly (UHouston)
Prof Clare Grey (University of Cambridge)
Dr David Waroquiers (Matgenix SRL)
Reviews
Exit strategySystem is typically self-hosted, but full data export is available via a programmatic API
Communityhttps://datalab-org.io
Known users
General
LicenseOpen Source, Core is MIT licensed, alongside the Python API and many plugins.
SubjectNatural Sciences, Chemistry, Chemistry:Experimental Chemistry, Chemistry:Inorganic Chemistry, Chemistry:Electrochemistry, Generic chemical sample-based data model out of the box, but can be used generically for any domain after customisation
PricingFree, Independent of number of users, Chargeable / Paid for / fee-based, Academic, Can be self-hosted for free, managed deployments available at cost for academia, industry deployments available for a fee per deployment
VersionsDemo, https://demo.datalab-org.io
Location of provider
Usability
Customizable user interfaceCustomizable user interface, Aspects of the UI are customisable via plugins. Can also be readily forked and customised per deployment.
LanguagesEnglish
SupportConsulting, Online documentation, Support by provider, User training (online, on site)
Usage statisticsNo usage statistics
Offline functionalities
Core functions (Daily work)
Data inputBarcode Scanner, Browser forms, Plain text editor, Rich text editor, Table editor, With internal links
Data import (formats)Compressed formats, Image formats, Document formats, Structured formats, Scientific formats, Video formats, Table formats, Intentional support for (often proprietary) instrument formats required for a given lab, which can be parsed, indexed and visualised, extensible via plugins and makes use of the platform-agnostic Datatractor registry https://yard.datatractor.org
Data import (method)Drag & Drop / File Chooser, Mobile phone photo (via app)
Data exportComplete content in machine readable format, Formats suitable for long term archiving, Formats suitable for publication
TemplatesNo user-facing templating UI, but data model is customisable per deployment
Search functionsFull text search, Search by command line, Advanced search
CollaborationRole management
Compliance with legal requirements
Preservation of evidenceTimestamping
Compliance
Extended functions (Daily work)
Laboratory management functionsInventory (devices), LIMS connectivity, Sample Tracking, Materials database
Integrations and extensionsCreate own plug-ins, Widgets, On request, Can be integrated with any rclone-compliant fileserver/fileshare system, without specific provider support.
AutomationData analysis, Get data from instrument
Device connectionDevice connection, Connect to device computers for fileshare via SSH/SFTP.
Project management tools
Workflows
Integration in RDM and IT environment
Application programming interfacesPython library, REST API
Controlled vocabularyNot controlled, Controlled Vocabulary, Deployments can be set up with specific controlled vocabulary, but not out-of-the-box.
Data accessBrowser based, Local client, Responsive Design
Data storage locationCloud, Local, Storage decided per deployment, typically cloud but can be on local hardware.
Type of external cloudPublic cloud, Private cloud (e.g. via VPN)
Location of data storage or processing
Level of data protection (e.g. certification)
Transport encryption
Data storage encryption
Access control
Guaranteed SLAs
Interval of Data BackupsDaily (by default)
Number of Data BackupsArbitrary point-in-time rollback via borg.
Data Backups EncryptedYes, Automations provided for encrypted borg backups
Template for data processing agreement (DPA), including the technical and organizational measures (TOM)
Authentication methodsOAuth2, Other, OIDC, Typically via OAuth2, can also enable email magic link based sign-in
User account security measures
Usage optionOn-premises, Software as a Service, Can be self-hosted or a managed deployment can be arranged via datalab industries ltd.
Server operating systemLinux, Windows, MacOS, Any system that can run Docker, but ideally Linux