Semantic-Driven Visualized Model for Ecological Datasets

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Semantic-Driven Visualized Model for Ecological Datasets

Large volume of datasets in ecological science requires an understanding of metadata standards and assessment techniques in ecological research findings among diverse research groups. It requires a sharing medium of technical assistance and comprehensive definition of interpretations about the modeling concepts. It can lead to adhoc solutions subjected to growth and change in course of new ecological improvements and methodologies. It urges the need of self-learning initiative to understand the terms with their semantic relationships. These requirements can be mapped to the creation of ontology schema of ecological datasets and visual-information driven models as an initiative. This strategy is clearly explained as follows:

• Collaboration of sharing and usage of datasets for analytical assessments by researchers and information managers make request/response to other research teams by queries and derive in a comprehensive description in their documentations for future references can be mapped in the form of observational metadata standards.

• These observational metadata standards can be stored as observational ontology schema.

• This schema can have technological intelligence of automated entity-relationship model creation for semantic identification and dependencies among the data standards.

• In extension to this semantic entity-relationship model (ERD), application of additional visualized models such as Unified Modeling Language (UML) can be used with the transformation of entities to different components constructs.

This concept can solve the information entropy problem of platform incompatibility of technological advancements and creates the impact of...

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...se recordings of observations in ontology schema along with the data model reduce the work effort of research groups to self-examine the behaviour of the datasets with more semantic relationships. Designing the data model can be automated and use as a visual-documentation standard throughout new findings.

FUTURE WORK The implementation of the data model through database schema information retrieval algorithms needed to be explored. In some situations, tracing package in the observed records is required to be the extension of this work.

Fig 4.Representation of ERD model in Observational Ontology Schema

ACKNOWLEDGEMENT

We thank the Department of Computer Science and Engineering of Velammal College of Engineering and Technology, Madurai to encourage and provide infrastructure for the preparation of this journal work.

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