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Schema-agnosticism is the property of a database of mapping a query issued with the user terminology and structure, automatically mapping it to the dataset vocabulary. The increase in the size and in the semantic heterogeneity of database schemas bring new requirements for users querying and searching structured data .
Devices and programs [6] can become more data-agnostic by using a generic storage format to create, read, update and delete files. Formats like XML and JSON can store information in a data agnostic manner. For example, XML is data agnostic in that it can save any type of information. However, if you use Data Transform Definitions (DTD) or XML ...
This allows each schema to be concerned with only its own language definition, and the NRL file routes the schema validator to the correct schema file based on the namespace of that element. This XML format is schema-language agnostic and works for just about any schema language.
As a schema for semantic data that needs to be exchanged or stored; As a language that supports a particular method or process; As a language to express additional semantics of existing information; As a mechanism to create tools that work with a broad class of models at run time
Database abstraction layers reduce the amount of work by providing a consistent API to the developer and hide the database specifics behind this interface as much as possible. There exist many abstraction layers with different interfaces in numerous programming languages. If an application has such a layer built in, it is called database ...
The database schema is the structure of a database described in a formal language supported typically by a relational database management system (RDBMS). The term " schema " refers to the organization of data as a blueprint of how the database is constructed (divided into database tables in the case of relational databases ).
Distributional–relational models were first formalized, [3] [4] as a mechanism to cope with the vocabulary/semantic gap between users and the schema behind the data. In this scenario, distributional semantic relatedness measures, combined with semantic pivoting heuristics can support the approximation between user queries (expressed in their own vocabulary), and data (expressed in the ...
Containers are grouped in "databases", which are analogous to namespaces above containers. Containers are schema-agnostic, which means that no schema is enforced when adding items. By default, every field in each item is automatically indexed, generally providing good performance without tuning to specific query patterns.