Database challenges and solutions in neuroscientific applications.
In the scientific community, the quality and progress of various endeavors depend in part on the ability of researchers to share and exchange large quantities of heterogeneous data with one another efficiently. This requires controlled sharing and exchange of information among autonomous, distributed, and heterogeneous databases. In this paper, we focus on a neuroscience application, Neuroanatomical Rat Brain Viewer (NeuART Viewer) to demonstrate alternative database concepts that allow neuroscientists to manage and exchange data. Requirements for the NeuART application, in combination with an underlying network-aware database, are described at a conceptual level. Emphasis is placed on functionality from the user's perspective and on requirements that the database must fulfill. The most important functionality required by neuroscientists is the ability to construct brain models using information from different repositories. To accomplish such a task, users need to browse remote and local sources and summaries of data and capture relevant information to be used in building and extending the brain models. Other functionalities are also required, including posing queries related to brain models, augmenting and customizing brain models, and sharing brain models in a collaborative environment. An extensible object-oriented data model is presented to capture the many data types expected in this application. After presenting conceptual level design issues, we describe several known database solutions that support these requirements and discuss requirements that demand further research. Data integration for heterogeneous databases is discussed in terms of reducing or eliminating semantic heterogeneity when translations are made from one system to another. Performance enhancement mechanisms such as materialized views and spatial indexing for three-dimensional objects are explained and evaluated in the context of browsing, incorporating, and sharing. Policies for providing the system with fault tolerance and avoiding possible intellectual property abuses are presented. Finally, two existing systems are evaluated and compared using the identified requirements.
Dashti
A E
AE
Department of Biological Science, USC Brain Project, University of Southern California, Los Angeles 90089-2520, USA.
Ghandeharizadeh
S
S
Stone
J
J
Swanson
L W
LW
Thompson
R H
RH
D000818:Animals; D001921:Brain / Q000033:anatomy & histology / Q000502:physiology*; D001931:Brain Mapping; D003195:Computer Communication Networks; D019992:Databases as Topic; D006801:Humans; D008959:Models, Neurological; D009488:Neurosciences; D051381:Rats; D012984:Software; D014055:Tomography, Emission-Computed