What is LORIS
LORIS (Longitudinal Online Research and Imaging System) is web-based data and project management software for neuroimaging research studies. It is an open-source framework for storing and processing behavioural, clinical, neuroimaging and genetics data. LORIS also makes it easy to manage large datasets acquired over time in a longitudinal study, or at different locations in a large multi-site study.
Visit LORIS Website
Why use LORIS?
- Leading data and project management software: For managing data across modalities, including behavioural, clinical, imaging and genetics
- Comprehensive and reliable solution: For small studies or large multi-site studies
- User-friendly: Menu-based software can be accessed anywhere using the web, including over mobile devices
- Open source: Code is freely available to customize for your project
- Extensible: Flexible design enables researchers to adapt data management features to their own study and add new features
- Project management tools: Monitoring and auditing tools to oversee data acquisition and clinical reliability
- Support: Large community of active users and developers
- Global reach: Used in many major brain imaging development projects, with worldwide partner organizations
Project Management and Study design
Project monitoring and auditing tools allow researchers to oversee data acquisition, data validation and clinical reliability verification.
Data entry and data transfer for behavioral, clinical, imaging and genetic datasets. Datasets are validated and cleaned of identifying information. A unique set of anonymized subject identifiers is assigned to every participant, designed to match the requirements of the study. During data entry, strict completion rules, restricted field types and rule checking actively enforce data validity according to project standards.
Data Management and Quality Control
Once data is entered, separate database modules perform data validation and provide feedback based on automated and manual checks.
The Imaging Browser links each subject’s neuroimaging scans (such as MRI images or processed outputs) to their clinical, behavioural and genetics data in LORIS. To facilitate quality control and visualization, LORIS uses BrainBrowser technology for 3D and 4D datasets.
LORIS’ Data Query Tool and Data Dictionary enable users to design, extract and update custom datasets in a simple and intuitive manner without having to write complex database queries. Datasets are downloaded as Excel or CSV files, with imaging files packaged for download. Data can also be exported from LORIS to image processing pipelines and analysis suites.
LORIS is an open source project and is freely available for download through GitHub.
An introductory User Guide to LORIS is also available.
Previous releases of LORIS are available through the Neuroimaging Informatics Tools and Resources Clearinghouse (NITRC).
LORIS installation and basic setup can be completed within minutes on a server that is ready for deployment.
Configuration, project setup, and deployment of specific modules may involve additional steps.
Please feel free to subscribe to the LORIS Developers mailing list to ask any LORIS-related questions.
Projects and publications using LORIS resources are requested to cite :
Das S, Zijdenbos AP, Harlap J, Vins D and Evans AC (2012) LORIS: a web-based data management system for multi-center studies. Front. Neuroinform. 5:37. doi: 10.3389/fninf.2011.00037
The LORIS logo is also available for use on posters and visual presentation materials. For more information, please contact the LORIS team.
- Open source MySQL Database Management System (DBMS)
- PHP front-end with an intuitive graphical user interface
- SSL-encrypted security
- CouchDB-based Data Query Tool enabling fast caching and download of large quantities of scalar and multidimensional data
- WebGL-based BrainBrowser Visualization tools for 3D and 4D neuroimaging data
- Data pipelines automate the conversion of neuroimaging file formats
- Built-in removal of identification information for imaging and behavioural data
LORIS will require installation of the following software:
- LINUX (Optimized for Ubuntu 14.04) or Mac OS X (tested for Mavericks OS X 10.9)
- Apache2 (libapache2-mod-php5)
- MySQL (libmysqlclient15-dev mysql-client mysql-server)
- PHP/Pear 5.3+ (php5 php-pear php5-mysql php5-gd)
- php5-json (for Debian/Ubuntu distributions)
- Smarty 3
- Package manager (for LINUX distributions)
1. How much time does LORIS take to Install?
The initial installation in many cases takes only a few minutes. Configuration and study-specific setup require additional steps.
2. What is needed to run LORIS?
LORIS can run on any Linux server, and has been tested extensively for Ubuntu 14.04. Data storage may be located on the same server, or at a different location. The amount of data storage required is variable depending on study size and imaging data modalities (e.g. MRI, MEG). Software packages such as git, CouchDB and LAMP setup are verified or installed during the LORIS install process. For more information please consult How To Get LORIS? under the “Additional Information” section above.
3. What is LORIS used for?
• Project design, data collection, study management and data sharing
• Synthesis and correlation of data across different modalities (imaging, behavioural and genetics)
4. How easy is it to import data from another data source into LORIS?
LORIS can import data via Excel or CSV upload tools, as well as linking to other data repositories via custom pipelines.
5. How easy is it to export data from LORIS to other software / my analysis tools?
Data is queried and downloaded via the Data Query Tool. Hooks exist to send this data to processing and analysis pipelines.
6. How is LORIS licensed? Is it open source?
LORIS is open source and licensed under GPLv3.0. Please consult How to get LORIS? under the “Additional Information” section above for details on how to download LORIS via GitHub.
7. What imaging data formats can LORIS handle?
LORIS is designed to process MINC, NIfTi, MEG, FreeSurfer, and processed input data, and can be customized for other modalities via fully configurable pipeline and visualization tools. Raw DICOM files are the foundation of the core visualization utilities. Conversion to formats such as MINC and NIfTI can be easily embedded in LORIS data handling pipelines.
8. Can I have custom scoring for clinical/neuropsychological measures?
Yes. Custom scoring can be implemented by script, in a variety of languages including PHP, Python or Matlab.
9. How much coding is required for clinical/neuropsychological measures?
LORIS’ Instrument Builder module enables non-technical staff to create many simple forms. Scoring and field dependencies can be implemented in a wide variety of scripting languages.
10. How fast can LORIS query and extract data for download from large datasets?
LORIS’ CouchDB-based Data Query Tool outperforms traditional MySQL-based cached retrieval by a factor of four for data querying and extraction. (Based on a medium-sized study with 7500 instrument datasets.)
11. How is data validated in LORIS?
LORIS has many Quality Control features enabling study staff to review, flag and track data quality at every level. Additional features in the Statistics module provide at-a-glance outlier identification.