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Various data sources like relational/XML databases and comma separated value files can be combined via a Mapping Schema.
Fundamentally, the unified BioTCM ontology provides a common generalized terminological and assertional base for mapping from multiple sources to a unified mapping schema.
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Mapping schemas across species or different experimental protocols allow users to comparatively analyze the omics data.
The basic learning activities are: exploration, recognition, differentiation and generalization of stimuli, labeling (groups of) stimuli, building knowledge about the behaviors (dangers, contingencies, rules, affordances) of the unknown stimuli, creating mental maps (schema's) of the environment, acting within the situation and solving problems.
Although definitions of mental models have varied greatly depending on the context of their use (Johnson-Laird 1983), most tend to encompass internal representations of knowledge that are structured as cognitive maps, schemas, or frameworks (Johnson-Laird 1983).
Although several studies have explored in detail student mental models of particular biological phenomena within ecology and evolution (e.g., Anderson and Demitrius 1993; d'Apollonia et al. 2002; Anderson et al. 2001), no research to our knowledge has explored biology students' cognitive maps, schemas, or mental models of biology as a whole.
As relational databases are the primary choices for this purpose considering their data management power, it is necessary to research the problem of mapping XML schemas to relational schemas.
The idea to transform these lists as part of a controlled SPASE vocabulary into the SKOS format was realized by mapping such schema elements which are related to an enumeration list to an appropriate SKOS concept schema.
This transformation usually consists of three steps: linguistic analysis, component mapping and schema construction.
The WinFS runtime maps the schema to a relational modality, by defining the tables it will store the types in and the primary keys and foreign keys that would be required to represent the relationships.
It suggests that all courses should have some material introducing students to cloud computing, that practical teaching should focus on Platform as a Service and that there is scope for a graduate course in cloud software engineering covering map-reduce, schema-free databases, service-oriented computing, security and compliance and design for resilience.
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