Domain Ontology As Conceptual Model for Big Data Management: Application in Biomedical Informatics

Jayapandian, Catherine P.; Chen, Chien‐Hung; Dabir, Aman; Lhatoo, Samden D.; Zhang, Guoqiang; Sahoo, Satya S.

doi:10.1007/978-3-319-12206-9_12

Cited by 15 publications

(8 citation statements)

References 19 publications

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“…In previous work, we have demonstrated the advantages of transferring fragments of signal data corresponding to the six standard montages over the network as compared to an unpartitioned EDF file (Jayapandian et al, 2014 ). In addition, the CSF object stores signal data in integer format as physical values (described in Section Signal Data Processing and Flexible Data Partitioning Technique), which significantly reduces the data processing task of the Web browser.…”

Section: Methodsmentioning

confidence: 99%

“…The processing of EDF files to generate channel-specific CSF objects was found to improve the response time of the Cloudwave visualization interface. In addition, the total time taken to transfer the signal data fragments with associated metadata as well as clinical event annotation and rendering of the signal data on the Web browser interface was found to be consistently less for signal data fragments (stored in CSF objects) in comparison to EDF files (Jayapandian et al, 2014 ). The signal visualization interface also used the annotation properties of EpSO classes to display clinical events as human readable text on the signal data.…”

Section: Methodsmentioning

confidence: 99%

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A scalable neuroinformatics data flow for electrophysiological signals using MapReduce

Jayapandian

Wei

Ramesh

et al. 2015

Front. Neuroinform.

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Data-driven neuroscience research is providing new insights in progression of neurological disorders and supporting the development of improved treatment approaches. However, the volume, velocity, and variety of neuroscience data generated from sophisticated recording instruments and acquisition methods have exacerbated the limited scalability of existing neuroinformatics tools. This makes it difficult for neuroscience researchers to effectively leverage the growing multi-modal neuroscience data to advance research in serious neurological disorders, such as epilepsy. We describe the development of the Cloudwave data flow that uses new data partitioning techniques to store and analyze electrophysiological signal in distributed computing infrastructure. The Cloudwave data flow uses MapReduce parallel programming algorithm to implement an integrated signal data processing pipeline that scales with large volume of data generated at high velocity. Using an epilepsy domain ontology together with an epilepsy focused extensible data representation format called Cloudwave Signal Format (CSF), the data flow addresses the challenge of data heterogeneity and is interoperable with existing neuroinformatics data representation formats, such as HDF5. The scalability of the Cloudwave data flow is evaluated using a 30-node cluster installed with the open source Hadoop software stack. The results demonstrate that the Cloudwave data flow can process increasing volume of signal data by leveraging Hadoop Data Nodes to reduce the total data processing time. The Cloudwave data flow is a template for developing highly scalable neuroscience data processing pipelines using MapReduce algorithms to support a variety of user applications.

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

A scalable neuroinformatics data flow for electrophysiological signals using MapReduce

Jayapandian

Wei

Ramesh

et al. 2015

Front. Neuroinform.

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“…Varios autores (Epstein, Ping, Fogarty & Munson, 2015;Jayapandian et al, 2014) plantean la necesidad de utilizar modelos en la informática en todas sus disciplinas científicas.…”

Section: La Modelación Como Parte De La Actividad Informática Y El Prunclassified

La Modelación Como Competencia en La Formación Del Profesional Informático

Hernández¹

2016

Docencia univ.

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La modelación como competencia en la formación del profesional informático RESUMEN. La modelación es una de las actividades más importantes en la actividad ingenieril. En el artículo se toma posiciones de los autores sobre el modelo y sus clasificaciones. Por otro lado, se asumen los elementos esenciales del currículo informático en el mundo y la importancia de la modelación en ellos. En el último acápite se analiza el cómo estructurar la modelación como elemento esencial en su modo de actuación. También se explica acerca de la estructura de la competencia modelar tomando como sustento el análisis de definiciones actuales de competencia a partir de los conocimientos, habilidades, valores y los procesos de autorregulación del aprendizaje. Se asume en el artículo que para el desarrollo de esta competencia la enseñanza de la ingeniería del software debe anteceder a la programación. ABSTRACT. Modeling is one of the most important activities in engineering activity. In the article the authors positions on the model and its classifications is taken. Furthermore, the essential elements of computer curriculum in the world and the importance of modeling them are assumed. In the last paragraph it discusses how to structure modeling as an essential element in their mode of action. In this section the structure of competence unfolds modeling analysis taking support current definitions of competence from the knowledge, skills, values and self-regulated learning processes. It is assumed in the article for the development of this competence the teaching of software engineering must precede to programming teach. El desarrollo acelerado de las TIC en la época actual ha llevado a considerar su introducción en la sociedad como un proceso estratégico. Sin embargo, este proceso debe llevarse a cabo por profesionales altamente capacitados para ejercer las funciones que demanda. Para la formación de este profesional es necesario investigar un conjunto de problemas inherentes al proceso de enseñanza-aprendizaje de la Informática.En el desarrollo histórico de la informática se han destacado varias disciplinas científicas que pueden ser estructuradas como parte del currículo del profesional de esta ciencia mientras que otras no. Sin embargo, existen determinados contenidos que son esenciales para su formación y que no se encuentran enmarcados en una única disciplina. Uno de estos contenidos es precisamente la modelación de procesos de informatización.La modelación es una de las actividades más importantes en la formación del ingeniero informático debido a la necesidad de una representación anticipada de los procesos de informatización por realizar. Para ello, el análisis debe estar en el orden de las estructuras psicológicas de la personalidad que se debe considerar como modelación en la formación del profesional informático.Un primer momento de análisis pudiera llevar a definir la modelación como una habilidad; sin embargo, el alcance de la modelación implica además conocimientos, valores, procesos de autorregulación que llevan a pensar...

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“…They represent not only the concepts (nodes) but the relationships (edges) between the concepts. Ontologies have become a critical knowledge source in informatics and data intensive applications, such as information retrieval [ 1 ], data integration [ 2 ], data management [ 3 ], and decision support [ 4 ].…”

Section: Introductionmentioning

confidence: 99%

FEDRR: fast, exhaustive detection of redundant hierarchical relations for quality improvement of large biomedical ontologies

2016

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BackgroundRedundant hierarchical relations refer to such patterns as two paths from one concept to another, one with length one (direct) and the other with length greater than one (indirect). Each redundant relation represents a possibly unintended defect that needs to be corrected in the ontology quality assurance process. Detecting and eliminating redundant relations would help improve the results of all methods relying on the relevant ontological systems as knowledge source, such as the computation of semantic distance between concepts and for ontology matching and alignment.ResultsThis paper introduces a novel and scalable approach, called FEDRR – Fast, Exhaustive Detection of Redundant Relations – for quality assurance work during ontological evolution. FEDRR combines the algorithm ideas of Dynamic Programming with Topological Sort, for exhaustive mining of all redundant hierarchical relations in ontological hierarchies, in O(c·|V|+|E|) time, where |V| is the number of concepts, |E| is the number of the relations, and c is a constant in practice. Using FEDRR, we performed exhaustive search of all redundant is-a relations in two of the largest ontological systems in biomedicine: SNOMED CT and Gene Ontology (GO). 372 and 1609 redundant is-a relations were found in the 2015-09-01 version of SNOMED CT and 2015-05-01 version of GO, respectively. We have also performed FEDRR on over 190 source vocabularies in the UMLS - a large integrated repository of biomedical ontologies, and identified six sources containing redundant is-a relations. Randomly generated ontologies have also been used to further validate the efficiency of FEDRR.ConclusionsFEDRR provides a generally applicable, effective tool for systematic detecting redundant relations in large ontological systems for quality improvement.

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Domain Ontology As Conceptual Model for Big Data Management: Application in Biomedical Informatics

Cited by 15 publications

References 19 publications

A scalable neuroinformatics data flow for electrophysiological signals using MapReduce

A scalable neuroinformatics data flow for electrophysiological signals using MapReduce

La Modelación Como Competencia en La Formación Del Profesional Informático

FEDRR: fast, exhaustive detection of redundant hierarchical relations for quality improvement of large biomedical ontologies

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