Share Biomedical Data in a Free and Easy Way

Super Computing Solutions (SCS) today announces the release of an interactive digital library service, called PhysiomeSpace, designed to manage and share a large collection of heterogeneous biomedical data, such as medical imaging, motion capture, biomedical instrumentation signals, finite element models, etc.

The digital library services are hosted on the Biomed Town community portal and can be accessed from www.physiomespace.com. PhysiomeSpace is currently a totally free service which offers up to 1GB of space: anyone interested in experimenting this innovative approach can register to the BiomedTown portal and use this service under the license agreement that can be found at www.physiomespace.com/public/TermsOfUse. PhysiomeSpace is easy to use: just with few clicks users can manage and curate the existing data resources, upload new ones and eventually share them with other users, following a simply permission system which ensure reliability and control.

PhysiomeSpace is in the process to release the Living Human Digital Library (LHDL) multiscale musculoskeletal data collection that provides a unique systematic quantification of morphological and functional aspects of the musculoskeletal system, at a range of dimensional scales from the whole body down to the tissue constituents. The originality of the collection is that all data corresponds to the same body and are registered into a multiscale hierarchy defined in a global reference framework. The full data collection will be progressively released with a cadence of two weeks, starting from June 29th 2010 and when entirely published will constitute one of the most extensive data collection publicly available of this kind.

About PhysiomeSpace Service
The digital library service is managed using a client–server approach. The client application, called PSLoader© is used to import, fuse and enrich the data information according to the PhysiomeSpace resource ontology and but also to upload and download the resources to the library.

A search service capitalizes on the domain ontology and on the enrichment of metadata for each resource, providing a powerful discovery environment. The metadata are described in an extensible ontology composed of a master ontology and a series of sub-ontologies which can be added by the users’ communities, depending on their needs. If you wish to learn how to use the service you can download the PhysiomeSpace guide from www.physiomespace.com/wikis.

About LHDL project
The Living Human Digital Library (LHDL) research project (www.livinghuman.org, FP6-2004-ICT- 026932) was a STREP Project co-funded by the European Commission's as part of the 6th Framework Programme. The project, under the scientific coordination of the Istituto Ortopedico Rizzoli (IOR, Italy), run for three years from February 2006 to February 2009 and saw the participation of the University of Bedfordshire (U.K.), the Université Libre de Bruxelles (ULB, Belgium), the Open University (U.K.) and the CINECA supercomputing centre (Italy).

About LHDL collection
The collection, generated by researchers at ULB and IOR, is based on two female cadavers obtained from the ULB donation program, and on a group of body-matched volunteers recruited at IOR. The data collection included very different activities starting from the body level to scale down to organ, tissue, sub tissue and cell level. Full details on the LHDL Data collection can be found: http://www.biomedtown.org/biomed_town/LHDL/Reception/lhp-public-repository/public_D/plfng_view.

A complete description of the methods used to collect the various data types can be found: http://www.biomedtown.org/biomed_town/LHDL/Reception/collection/.

Most Popular Now

Is AI in Medicine Playing Fair?

As artificial intelligence (AI) rapidly integrates into health care, a new study by researchers at the Icahn School of Medicine at Mount Sinai reveals that all generative AI models may...

Generative AI's Diagnostic Capabili…

The use of generative AI for diagnostics has attracted attention in the medical field and many research papers have been published on this topic. However, because the evaluation criteria were...

New System for the Early Detection of Au…

A team from the Human-Tech Institute-Universitat Politècnica de València has developed a new system for the early detection of Autism Spectrum Disorder (ASD) using virtual reality and artificial intelligence. The...

AI Tool can Track Effectiveness of Multi…

A new artificial intelligence (AI) tool that can help interpret and assess how well treatments are working for patients with multiple sclerosis (MS) has been developed by UCL researchers. AI uses...

Diagnoses and Treatment Recommendations …

A new study led by Prof. Dan Zeltzer, a digital health expert from the Berglas School of Economics at Tel Aviv University, compared the quality of diagnostic and treatment recommendations...

Dr Jason Broch Joins the Highland Market…

The Highland Marketing advisory board has welcomed a new member - Dr Jason Broch, a GP and director with a strong track record in the NHS and IT-enabled transformation. Dr Broch...

Surrey and Sussex Healthcare NHS Trust g…

Surrey and Sussex Healthcare NHS Trust has marked an important milestone in connecting busy radiologists across large parts of South East England, following the successful go live of Sectra's enterprise...

Multi-Resistance in Bacteria Predicted b…

An AI model trained on large amounts of genetic data can predict whether bacteria will become antibiotic-resistant. The new study shows that antibiotic resistance is more easily transmitted between genetically...

DMEA 2025 Ends with Record Attendance an…

8 - 10 April 2025, Berlin, Germany. DMEA 2025 came to a successful close with record attendance and an impressive program. 20,500 participants attended Europe's leading digital health event over the...