Biomedical Engineering Reference
In-Depth Information
Implementation
Even with all of the public-domain databases accessible through the Internet, there will be research
tasks that necessitate using a local database. The reasons vary from a need to collect, analyze, and
publish sequence information inside a small laboratory to establishing a massive data warehouse as
part of a pharmacogenomic R&D effort. In either case, the general issues and challenges are the
same, albeit in different degrees of severity. As shown in
Table 2-7
, the major database
implementation issues range from the storage capacity requirements and cost to scalability and
security.
Table 2-7. Bioinformatics Database Implementation Issues.
Issue
Description
Accessibility
Ease of use, support for multiple mental models and database
abstractions
Archiving
Support for the archival process, including software and hardware, and
offsite storage facilities
Capacity
Local and remote data storage capacity, including space for expansion
of the database
Connectivity
Connectivity through local and wide area networks, intranets, and the
Internet
Control
Internal vs. third-party control of data, which may be an issue with
storage service providers and other Internet-based commercial storage
options
Cost
Initial, operating, and indirect (need to upgrade current network
hardware and software, purchase additional peripherals) costs
Data Dictionary
Design, implementation, and maintenance of the data dictionary
Data Formats
Data formats supported by the database
Data Input
Hardware, software, and processes involved in feeding data into the
database, from keyboard and voice recognition to direct instrument
feed and the Internet
Data Model
Flat files, relational, hierarchical, network, object-oriented, or semi-
structured
DBMS Software
Robustness, scalability, performance, cost, vendor reputation (if
commercial), support available (if open source)
Dependencies
Dependence on primary databases for populating the database,
especially regarding update frequency provision for validating data to
minimize propagation of errors
Disaster Recovery
Procedural, hardware, and software provisions for disaster recovery,
including error recovery mechanisms
Export/Import Capabilities Provisions for importing and exporting data to and from different file
formats
Hardware Requirements
Hard disks, controllers, backup hardware, production and staging
servers for large database projects
