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David Keator

Publications and source records attributed to David Keator.

3 recordsLinked to original sources

Building a Web of Linked Data Resources to Advance Neuroscience Research

The fundamental goal of neuroscience is to understand the nervous system at all levels of description, from molecular components to behavior. The complexity of achieving this goal in neuroscience, and biomedicine in general, poses many technical and sociological challenges. Among these are the need to organize neuroscientific data, information, and knowledge to facilitate new scientific endeavors, provide credibility and visibility of research findings, and increase the efficiency of data reuse. Linked Data is a set of principles based on Web technology that can aid this process as it organizes data as an interconnected network of information. This review examines the history, practical impact, potential, and challenges of applying Linked Data principles to neuroscience.

Scientific Communication and Education

Sharing brain mapping statistical results with the neuroimaging data model

Only a tiny fraction of the data and metadata produced by an fMRI study is finally conveyed to the community. This lack of transparency not only hinders the reproducibility of neuroimaging results but also impairs future meta-analyses. In this work we introduce NIDM-Results, a format specification providing a machine-readable description of neuroimaging statistical results along with key image data summarising the experiment. NIDM-Results provides a unified representation of mass univariate analyses including a level of detail consistent with available best practices. This standardized representation allows authors to relay methods and results in a platform-independent regularized format that is not tied to a particular neuroimaging software package. Tools are available to export NIDM-Result graphs and associated files from the widely used SPM and FSL software packages, and the NeuroVault repository can import NIDM-Results archives. The specification is publically available at: http://nidm.nidash.org/specs/nidm-results.html.

Neuroscience

The Brain Imaging Data Structure: a standard for organizing and describing outputs of neuroimaging experiments

The development of magnetic resonance imaging (MRI) techniques has defined modern neuroimaging. Since its inception, tens of thousands of studies using techniques such as functional MRI and diffusion weighted imaging have allowed for the non-invasive study of the brain. Despite the fact that MRI is routinely used to obtain data for neuroscience research, there has been no widely adopted standard for organizing and describing the data collected in an imaging experiment. This renders sharing and reusing data (within or between labs) difficult if not impossible and unnecessarily complicates the application of automatic pipelines and quality assurance protocols. To solve this problem, we have developed the Brain Imaging Data Structure (BIDS), a standard for organizing and describing MRI datasets. The BIDS standard uses file formats compatible with existing software, unifies the majority of practices already common in the field, and captures the metadata necessary for most common data processing operations.

Neuroscience