#LAKEHOUSE ARCHITECTURE SOFTWARE#
Implementation of this API on top of diverse knowledge sources potentially enables their uniform integration behind client software which will facilitate research access and integration of biomedical knowledge. This specification also enforces the annotation of knowledge concepts and statements to the NCATS endorsed the Biolink Model data model and semantic encoding standards (). Knowledge Beacons provide a standardized basic API for the discovery of concepts, their relationships and associated supporting evidence from distributed online repositories of biomedical knowledge. As an activity within the feasibility phase of a project called “Translator” () funded by the National Center for Advancing Translational Sciences (NCATS) to develop a biomedical science knowledge management platform, we designed a Representational more » State Transfer (REST) web services Application Programming Interface (API) specification, which we call a Knowledge Beacon. In order to accelerate research towards effective medical treatments and optimizing health, it is critical that efficient and automated tools for identifying key research concepts and their experimentally discovered interrelationships are developed. The continually expanding distributed global compendium of biomedical knowledge is diffuse, heterogeneous and huge, posing a serious challenge for biomedical researchers in knowledge harvesting: accessing, compiling, integrating and interpreting data, information and knowledge. We demonstrate the utility of Biolink Model in various initiatives, including the Biomedical Data Translator Consortium and the Monarch Initiative, and show how it has supported easier integration and interoperability of biomedical KGs, bringing together knowledge from multiple sources and helping to realize the goals of translational science. Here, we highlight the need for a standardized data model for KGs, describe Biolink Model, and compare it with other models. The model provides class and edge attributes and associations that guide how entities should relate to one another.
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The core of the model is a set of hierarchical, interconnected classes (or categories) and relationships between them (or predicates) representing biomedical entities such as gene, disease, chemical, anatomic structure, and phenotype. It incorporates object-oriented classification and graph-oriented features.
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Biolink Model is an open-source data model that can be used to formalize the relationships between data structures in translational science. Data set heterogeneity and complexity the proliferation of ad hoc data formats poor compliance with guidelines on findability, accessibility, interoperability, and reusability and, in particular, the lack of a universally accepted, open-access model for standardization across biomedical KGs has left the task of reconciling data sources to more » downstream consumers. However, knowledge discovery across these “knowledge graphs” (KGs) has remained difficult. Graph-based data models elucidate the interconnectedness among core biomedical concepts, enable data structures to be easily updated, and support intuitive queries, visualizations, and inference algorithms.
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Within clinical, biomedical, and translational science, an increasing number of projects are adopting graphs for knowledge representation.
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The core software, associated tools, and documentation can be downloaded from the following URL.
#LAKEHOUSE ARCHITECTURE CODE#
It is built on open source components and caGrid source code is publicly and freely available under a liberal open source license. Results: The caGrid 1.0 was released to the caBIG community in December 2006. It provides a set of core services, toolkits for the development and deployment of new community provided services, and application programming interfaces for building client applications. Measurements: The caGrid is built as a Grid software infrastructure and more » leverages Grid computing technologies and the Web Services Resource Framework standards. It is designed to support a wide range of use cases in basic, translational, and clinical research, including (1) discovery, (2) integrated and large-scale data analysis, and (3) coordinated study.