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...
... middle of paper ...
...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.
Generally, the development and adoption of Clinical Decision Support (CDS) systems is based on the necessity and essence of technical standards in enhancing healthcare. However, the various health IT tools must comply with some data interchange standards in order to enhance access to clinical records, lessen clinical errors and risks to patient safety, and promote innovation in “individual-based” care (Hammond, Jaffe & Kush, 2009, p.44). The need for compliance with standards is fueled by their role in enabling aggregation of informa...
The next project deliverable is a robust, modernized database and data warehouse design. The company collects large amounts of website data and uses this data to analyze it for the company’s customers. This document will provide an overview of the new data warehouse along with the type of database design that has been selected for the data warehouse. Included in the appendix of this document is a graphical depiction of the logical design of the
The mean of witch the authors went about on collecting data is sort of like field research. For an example, they would go into areas with the most problems in the chosen community. Instead of offering to help and solve the p...
Information and Software Technology Years 7–10: Syllabus. (2003, June). Retrieved April 10, 2014, from http://www.boardofstudies.nsw.edu.au/syllabus_sc/pdf_doc/info_soft_tech_710_syl.pdf
Foundational Interoperability is data exchange from one system by another, Structural Interoperability is the exchange of information between systems and it is interpreted in the data field level, and Semantic Interoperability allows multiple system to exchange information (3). Currently I believe our organization is at the structural level, but our end goal of this project is to ensure we achieve Semantic
Key words and phrases (highlighted) were used to determine the appropriate entities and their attributes, and to help determine the kinds of queries that might be useful for key stakeholders.
A gold-standard method allows for the comparison of resulting data with an independent source. Given the lack of such method for evaluating data linkage quality, several indirect methods are available for this purpose. These methods, however, can be flawed. The available methods provide sensitivity and specificity estimates that range between 74% - 98% and 99% - 100%, respectively (Bohensky, Jolley et al. 2010). Decision makers and stakeholders should be aware of the possibility of data linkage errors and the difficulty of assessing linkage success.
[7] Elmasri & Navathe. Fundamentals of database systems, 4th edition. Addison-Wesley, Redwood City, CA. 2004.
A data warehouse comprised of disparate data sources enables the “single version of truth” through shared data repositories and standards and also provides access to the data that will expand frequency and depth of data analysis. Due to these reasons, data warehouse is the foundation for business intelligence.
Board, Technology Strategy, Metadata production tools MAINSTREAM COLLABORATIVE R & D FUNDING Metadata production tools 2011 http://www.innovateuk.org/_assets/pdf/competition-documents/metadataproductiontoolscompetition.pdf accessed 02-01-2011
The Unified Modeling Language is a standard language for specifying, visualizing, constructing, and documenting the artifacts of software systems, as well as for business modeling and other non-software systems. The key is to organize the design process in a way that clients, analysts, programmers and other involved in system development can understand and agree on. The UML provides the organization. The UML was released in 1997 as a method to diagram software design, by some of the best minds in object oriented analysis and design. It is by far the most exciting thin to happen to the software industry in recent years. Every other engineering discipline has a standard method of documentation. Electronic engineers have schematic diagrams; architects and mechanical engineers have blueprints and mechanical diagrams. The software industry now has UML.
HARRIS, H., MURPHY, S., & VAISMAN, M. (2013).Analyzing the analyzers an introspective survey of data scientists and their work.Sebastopol, Calif, O'Reilly Media.http://proquest.safaribooksonline.com/9781449368388.
People have been relying for their daily needs and well-being on nature. The natural ecosystem provides varieties of goods and services to us, for instance, fresh water, fisheries, timber, water purification etc. The benefits that people directly get from the natural systems are called ecosystem services (ES).
Data collection is a process by which you receive useful information. It is an important aspect of any type of research, as inaccurate data can alter the results of a study and lead to false hypothesis and interpretations. The approach the researcher utilizes to collect data depends on the nature of the study, the study design, and the availability of time, money and personnel. In addition, it is important for the researcher to determine whether the study is intended to produce qualitative or quantitative information.
Did your phone just ring? Or was that your computer notifying you of a new email? Since the Digital Revolution and the addition of digital electronics like the personal computer, software-based technology has always been an essential aspect of our lives. Something that would have taken up an entire classroom can now fit within the grasp of your hands thanks to the efforts of various computer scientists and engineers, making our lives much easier.