Paper Info
Title
Data model for scientific models and hypotheses
Abstract
New instruments and techniques used in capturing scientific data are exponentially increasing the volume of data consumed by insilico research, which has been usually referred to as data deluge. Once captured, scientific data goes through a cleaning workflow before getting ready for analysis that will eventually confirm the scientist's hypothesis. The whole process is, nevertheless, complex and takes the focus of the scientist's attention away from his/her research and towards solving the complexity associated with managing computing products. Moreover, as the research evolves, references to previous results and workflows are needed as source of provenance data. Based on these observations, we claim that in-silico experiments must be supported by a hypotheses data model that describes the elements involved in a scientific exploration and supports hypotheses assessment. Adopting a data perspective to represent hypotheses allow high-level references to experiments and provides support for hypotheses evolution. The data model drives the proposal of a data management system that would support scientists in describing, running simulations and interpreting their results.
Year
DOI
Venue
2008
10.1007/978-3-642-17505-3_13
The Evolution of Conceptual Modeling
Keywords
Field
DocType
provenance data,data management system,data deluge,insilico research,hypotheses data model,data perspective,data model,hypotheses assessment,scientific data,scientific model,hypotheses evolution
Data science,Computer science,Scientific modelling,Workflow,Data model,Data management
Conference
Volume
ISSN
ISBN
6520
0302-9743
3-642-17504-X
Citations 
PageRank 
References 
0
0.34
18
Authors
2
Name
Order
Citations
PageRank
Fábio Porto13015.04
Stefano Spaccapietra22603565.28