Relational databases have their focus on rows in which they store the instances or the records and return rows or instances of an entity against a data retrieval query.
This chapter describes how data are stored, submission procedures, and mechanisms for data retrieval and query.
To meet such challenges, we augmented an open-source DBMS with novel data structures and algorithms for efficient data retrieval and query processing.
RAMMCAP is part of the CAMERA data portal [ 128, 129], which currently comes closest to an integrative processing pipeline for metagenomes with various tools for data retrieval, upload, querying and analysis.
The Analysis layer is implemented in R programming environment and is responsible for the execution of the mapping algorithm, and the Data Storage layer refers to the back-end databases used for data retrieval and query jobs by the R code.
In addition to aiding data retrieval via semantic queries, the OntoSearch hierarchies provide a suitable controlled vocabulary for annotating the new neuronal reconstructions continuously deposited in NeuroMorpho.Org while reducing the need for constant expert curation.
Data retrieval through meaningful queries [ 6] is paramount to the successful fulfilment of the ever more sophisticated data requirements of the systematics community.
The potential solutions to these challenges are automated data retrieval through electronic queries of existing systems for example electronic medical record (EMR) and cancer registry.
Future solutions to these barriers include automated data retrieval through electronic queries of existing systems (i.e. EMR and the Enterprise Tumor Registry).
