ADAGE: a framework for supporting user-driven ad-hoc data analysis processes

Data analysis is an important part of the scientific process carried out by domain experts in data-intensive science. Despite the availability of several software tools and systems, their use in combination with each other for conducting complex types of analyses is a very difficult task for non-IT...

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Vydáno v:Computing Ročník 94; číslo 6; s. 489 - 519
Hlavní autoři: Rabhi, Fethi A., Yao, Lawrence, Guabtni, Adnene
Médium: Journal Article
Jazyk:angličtina
Vydáno: Vienna Springer Vienna 01.06.2012
Springer Nature B.V
Témata:
Artificial Intelligence
Availability
Batch processing
Computation
Computer Appl. in Administrative Data Processing
Computer Communication Networks
Computer programs
Computer Science
Conduction
Cooperation
Data analysis
Data processing
Information Systems Applications (incl.Internet)
Interoperability
Libraries
Markets
News
Problem solving
Science
Scientists
Semantics
Service oriented architecture
Software
Software Engineering
Studies
Subject specialists
Tasks
Time series
SOA applications
User-driven composition
Event processing systems
Time series analysis
Financial market data
Thomson Reuters
Data-intensive science
Business process modeling
High-frequency data
ADAGE
68M01
ISSN:0010-485X, 1436-5057
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Popis
Shrnutí:Data analysis is an important part of the scientific process carried out by domain experts in data-intensive science. Despite the availability of several software tools and systems, their use in combination with each other for conducting complex types of analyses is a very difficult task for non-IT experts. The main contribution of this paper is to introduce an open architectural framework based on service-oriented computing (SOC) principles called the Ad-hoc DAta Grid Environment (ADAGE) framework that can be used to guide the development of domain-specific problem-solving environments or systems to support data analysis activities. Through an application of the ADAGE framework and a prototype implementation that supports the analysis of financial news and market data, this paper demonstrates that systems developed based on the framework allow users to effectively express common analysis processes. This paper also outlines some limitations as well as avenues for future research.
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ISSN:0010-485X
1436-5057
DOI:10.1007/s00607-012-0193-0