The Living Human Digital Library Project's Results

The Living Human Digital Library Project (LHDL) is a grass-roots initiative aimed at developing an in silico model of the human neuromusculoskeletal system that can predict how mechanical forces are exchanged internally and externally, from the whole body down to the protein level, consistently with scope of the European Virtual Physiological Human initiative. To pursue this very ambitious objective, it is necessary for large research communities to share highly heterogeneous collections of data and models through a repository fully integrated, and directly accessible by any researcher in the world. Although inspired by the neuromusculoskeletal research community, this problem is very general, and its solution will significantly and positively affect European research, clinical and industrial practices.

LHDL developed and deployed the resource-sharing infrastructure required by the LHP community and by many other groups involved with biomedical research and practice. In particular, the project realised:

  • PhysiomeSpace, the first professional data management & sharing service dedicated to biomedical data (now running in beta version).
  • PSLoader, an application that runs on your PC and let you import virtually any biomedical dataset, organise your collection of data in space and time, and then upload it to the data management service (sign on the PhysiomeSpace service, download it for free).
  • LhpBuilder, an application with a long list of specialised functions for processing and modelling neuro-musculoskeletal system data. The software will be soon commercially distributed by SCS srl.
  • LhpSimul, a powerful architecture of execution web services for the distributed execution of data-intensive algorithms; once stored on PhysiomeSpace your data can processed in batch.
  • LhpSWS, semantic web services with full semantic brokering capable of combining storage and execution services in complex data processing flows; currently hidden, it will provide the necessary scalability as the execution web services and the collection of data increase.
  • LHDL ontologies, a collection of specialised ontologies to annotate the data and service resources available through PhysiomeSpace. All ontologies are freely downloadable in various formats.
  • LHP Data Collection, the largest collection of experimental and modelling data on the descriptive and functional anatomy, and the multiscale biomechanics of the musculoskeletal system; this large collection is progressively being uploaded on PhysiomeSpace, from where it will be freely downloadable.

The client application: PSLoader
PSLoader is a desktop application that, after authentication, allows you to import biomedical data stored in a long list of digital formats (such as DICOM3, STL, JPG, TIFF, ANSYS, and many more), and organise them in space using a hierarchical tree where the pose of one dataset is defined with respect to the parent one. The program provides also long list of interactive views, designed to visualise whatever combination of data you can have. Each dataset is annotated with a long list of metadata that are generated automatically. Additional metadata are available for you to be annotated, so as to provide a coherent set of concepts for the data stored in the digital library and the information framework for resources searching and retrieving.

The Service: PhysiomeSpace
Once you have created the data collection in PSLoader, with a single click the entire collection can be uploaded to the PhysiomeSpace servers, where it is stored in your private space. You can then access it from a simple web interface, with which you can add, remove, annotate data resources, and assign to each resource a different set of access permissions. By default all uploaded data are open only to the data owner, but at any time you can choose with whom to share each dataset.

Alternatively, other PhysiomeSpace users can search every dataset. If the data you need is available, but its owner did not share it with you, you can send a message requesting access. This gives the data owner the possibility to talk directly to anyone willing to download the data, before granting access.

PhysiomeSpace data resources can be searched and browsed in various ways relying on the fact that each data resource is annotated by a set of metadata defined according to the LHDL Master Ontology. In addition, depending on the type of data, you can choose additional sub-ontologies to add to the data special concepts that are specific to a certain data generation modality, and that are related to a chosen way to describe what the dataset "represents". While PSLoader automatically annotates a good part of the master ontology, the user is still requested to do some manual curation. Each data resource stored on PhysiomeSpace has a quality index that scores the resources in terms of how extensive is the annotation.

Once a dataset is shared with you, you can place it in your "basket", ready to be downloaded from PSLoader next time you connect to it. The dataset can then be exported in whatever format, and used with other specialised applications.

Usage terms and conditions, data reuse and privacy policy
During the beta testing phase, the service will be open as a totally free service. The data will be uploaded under complete responsibility of the users, and no guarantee will be provided whatsoever for the continuity of the service, for the storage, the integrity, and the preservation of the data stored. The confidentiality of the data will be protected only through the access limitations of the service, and in principle system administrations are in the condition to access all uploaded data.

For further information, please visit:
http://www.livinghuman.org

Related articles:

  • FP6 Projects: LHDL

Copyright © ICT for Health - European Commission - Information society and Media DG
Office: BU31 06/41 B-1049 Brussels
Tel: +32 (0)2 296 41 94
Fax: 02 296 01 81
Email: This email address is being protected from spambots. You need JavaScript enabled to view it.
http://ec.europa.eu/information_society/eHealth

Most Popular Now

Philips and Medtronic Advocacy Partnersh…

Royal Philips (NYSE: PHG, AEX: PHIA), a global leader in health technology, and Medtronic Neurovascular, a leading innovator in neurovascular therapies, today announced a strategic advocacy partnership. Delivering timely stroke...

New AI Tool Predicts Protein-Protein Int…

Scientists from Cleveland Clinic and Cornell University have designed a publicly-available software and web database to break down barriers to identifying key protein-protein interactions to treat with medication. The computational tool...

AI for Real-Rime, Patient-Focused Insigh…

A picture may be worth a thousand words, but still... they both have a lot of work to do to catch up to BiomedGPT. Covered recently in the prestigious journal Nature...

New Research Shows Promise and Limitatio…

Published in JAMA Network Open, a collaborative team of researchers from the University of Minnesota Medical School, Stanford University, Beth Israel Deaconess Medical Center and the University of Virginia studied...

G-Cloud 14 Makes it Easier for NHS to Bu…

NHS organisations will be able to save valuable time and resource in the procurement of technologies that can make a significant difference to patient experience, in the latest iteration of...

Start-Ups will Once Again Have a Starrin…

11 - 14 November 2024, Düsseldorf, Germany. The finalists in the 16th Healthcare Innovation World Cup and the 13th MEDICA START-UP COMPETITION have advanced from around 550 candidates based in 62...

Hampshire Emergency Departments Digitise…

Emergency departments in three hospitals across Hampshire Hospitals NHS Foundation Trust have deployed Alcidion's Miya Emergency, digitising paper processes, saving clinical teams time, automating tasks, and providing trust-wide visibility of...

MEDICA HEALTH IT FORUM: Success in Maste…

11 - 14 November 2024, Düsseldorf, Germany. How can innovations help to master the great challenges and demands with which healthcare is confronted across international borders? This central question will be...

A "Chemical ChatGPT" for New M…

Researchers from the University of Bonn have trained an AI process to predict potential active ingredients with special properties. Therefore, they derived a chemical language model - a kind of...

Siemens Healthineers co-leads EU Project…

Siemens Healthineers is joining forces with more than 20 industry and public partners, including seven leading stroke hospitals, to improve stroke management for patients all over Europe. With a total...

MEDICA and COMPAMED 2024: Shining a Ligh…

11 - 14 November 2024, Düsseldorf, Germany. Christian Grosser, Director Health & Medical Technologies, is looking forward to events getting under way: "From next Monday to Thursday, we will once again...

In 10 Seconds, an AI Model Detects Cance…

Researchers have developed an AI powered model that - in 10 seconds - can determine during surgery if any part of a cancerous brain tumor that could be removed remains...