FieldML: concepts and implementation

246

311

One contribution of 11 to a Theme Issue 'Towards the virtual physiological human: mathematical and computational case studies'. Ongoing developments in cardiac modelling have resulted, in particular, in the development of advanced and increasingly complex computational frameworks for simulating cardiac tissue electrophysiology. The goal of these simulations is often to represent the detailed physiology and pathologies of the heart using codes that exploit the computational potential of high-performance computing architectures. These developments have rapidly progressed the simulation capacity of cardiac virtual physiological human style models; however, they have also made it increasingly challenging to verify that a given code provides a faithful representation of the purported governing equations and corresponding solution techniques. This study provides the first cardiac tissue electrophysiology simulation benchmark to allow these codes to be verified. The benchmark was successfully evaluated on 11 simulation platforms to generate a consensus gold-standard converged solution. The benchmark definition in combination with the gold-standard solution can now be used to verify new simulation codes and numerical methods in the future.

Section: (C) Benchmark Evolutionmentioning

confidence: 99%

Verification of cardiac tissue electrophysiology simulators using an N -version benchmark

Niederer

Kerfoot

Benson

et al. 2011

246

311

“…This work is beyond the scope of the present manuscript, but Beard et al (2009) and Christie et al (2009) provide further information on the integration of such ontologies with CellML and FieldML, respectively.…”

Section: (B ) Physiome Standardsmentioning

confidence: 99%

“…An example of a domain of interest would be the cardiac left ventricle, with various cellular physiology models spatially located in different regions, and certain material parameters varying within each of those regions . To address this requirement, FieldML is currently under development within the physiome community (see Christie et al 2009). FieldML is designed to provide a standardized framework for the description of domains of interest and the fields defined over those domains.…”

Section: (B ) Physiome Standardsmentioning

confidence: 99%

A physiome standards-based model publication paradigm

Nickerson

Buist

2009

In this era of widespread broadband Internet penetration and powerful Web browsers on most desktops, a shift in the publication paradigm for physiome-style models is envisaged. No longer will model authors simply submit an essentially textural description of the development and behaviour of their model. Rather, they will submit a complete working implementation of the model encoded and annotated according to the various standards adopted by the physiome project, accompanied by a traditional humanreadable summary of the key scientific goals and outcomes of the work. While the final published, peer-reviewed article will look little different to the reader, in this new paradigm, both reviewers and readers will be able to interact with, use and extend the models in ways that are not currently possible. Here, we review recent developments that are laying the foundations for this new model publication paradigm. Initial developments have focused on the publication of mathematical models of cellular electrophysiology, using technology based on a CellML-or Systems Biology Markup Language (SBML)-encoded implementation of the mathematical models. Here, we review the current state of the art and what needs to be done before such a model publication becomes commonplace.

“…In addition, the search function should also be supported by graphical methods providing human users with a three-dimensional interactive visualization of the models before downloading the required model in an interoperable and standard XML data format (http://www.w3c.org/XML). Within the VPH, the FieldML markup language is currently being developed to meet this need of describing models that include spatial information (Christie et al 2009). The goal is for FieldML files to contain all the parameters needed to mathematically specify spatial fields.…”

Section: Research Needs and Requirementsmentioning

confidence: 99%

“…By taking such an approach, euHeartDB establishes a knowledge link, and thus provides an integrative view of the anatomical models and of the related applications within simulation contexts. Moreover, euHeartDB adopts the exFormat, a preliminary version of FieldML (Christie et al 2009), as an interoperable XML data format to effectively promote the reuse of models, and uses the Continuum Mechanics, Image Analysis, Signal Processing and System Identification Graphical User Interface (CMGUI; http://www.cmiss.org/cmgui), a VPH rendering engine, to provide graphical representations of the available geometries. Currently, the database is populated with 11 models from partners in the euHeart project consortium (http://www.euheart.eu) (Ecabert & Smith 2008 This paper is organized as follows.…”

Section: Introductionmentioning

confidence: 99%

Sharing and reusing cardiovascular anatomical models over the Web: a step towards the implementation of the virtual physiological human project

Gianni

McKeever

et al. 2010

Sharing and reusing anatomical models over the Web offers a significant opportunity to progress the investigation of cardiovascular diseases. However, the current sharing methodology suffers from the limitations of static model delivery (i.e. embedding static links to the models within Web pages) and of a disaggregated view of the model metadata produced by publications and cardiac simulations in isolation. In the context of euHearta research project targeting the description and representation of cardiovascular models for disease diagnosis and treatment purposes-we aim to overcome the above limitations with the introduction of euHeartDB, a Web-enabled database for anatomical models of the heart. The database implements a dynamic sharing methodology by managing data access and by tracing all applications. In addition to this, euHeartDB establishes a knowledge link with the physiome model repository by linking geometries to CellML models embedded in the simulation of cardiac behaviour. Furthermore, euHeartDB uses the exFormat-a preliminary version of the interoperable FieldML data format-to effectively promote reuse of anatomical models, and currently incorporates Continuum Mechanics, Image Analysis, Signal Processing and System Identification Graphical User Interface (CMGUI), a rendering engine, to provide three-dimensional graphical views of the models populating the database. Currently, euHeartDB stores 11 cardiac geometries developed within the euHeart project consortium.