Semantics-based visualized model for ecological datasets A large volume of datasets in ecological sciences requires an understanding of metadata standards and evaluation techniques in the results of ecological research between different research groups. It requires a means of sharing technical assistance and a complete definition of interpretations on modeling concepts. It can lead to ad hoc solutions that are subject to growth and change in the course of new improvements and ecological methodologies. The need for self-learning initiatives emerges to understand the terms with their semantic relationships. These requirements can be mapped into the creation of ontological schemas of ecological datasets and models driven by visual information as an initiative. This strategy is clearly explained as follows: • Collaboration for sharing and using datasets for analytical evaluations by researchers and information managers makes requests/responses to other research groups via queries and derives a complete description in the their documentation for future reference which can be mapped into the form of observational metadata standards. • These observational metadata standards can be stored as an observational ontology schema. • This schema can have technological intelligence for automated creation of entity-relationship models for semantic identification and dependencies between data standards. • In extension to this semantic entity-relationship (ERD) model, the application of further visualized models such as Unified Modeling Language (UML) can be used with the transformation of entities into different component constructs. This concept can solve the information entropy problem of platform incompatibility of technological advances and creates the impact of...... half of the document ......if the observations records in the ontological scheme together with the model of data reduce the work effort of research teams to self-examine the behavior of datasets with multiple semantic relationships. Data model design can be automated and used as a visual documentation standard for new discoveries. FUTURE WORK It was necessary to explore the implementation of the data model through database schema information retrieval algorithms. In some situations, it is necessary for the tracking package in the observed records to be the extension of this work. and provide the infrastructure for the preparation of this journal work.