DMIA 2010 - 1st International Workshop on Data Management and Information Analytics (DMIA 2010)
Topics/Call fo Papers
1st International Workshop on
Data Management and Information Analytics - DMIA 2010
23 July, 2010 - Athens, Greece
In conjunction with the 5th International Conference on Software and Data Technologies - ICSOFT 2010
Co-Chairs
Markus Helfert
School of Computing, Dublin City University
Ireland
e-mail
Brian Donnellan
National University of Ireland, Maynooth
Ireland
e-mail
Scope and Goals
For several years research and practice has addressed various topics related to Data Management such as data modeling, data warehousing, data movement, database administration and data mining. However recent advances in technology provided us the possibility to gather enormous amounts of data. This resulted in many new challenges for data management. Most frequent examples of the technology advances are mobile, wireless and sensor technology providing many opportunities for innovative applications. The large amount of data, gathered anywhere from anything, requires different solutions than traditional data management approaches.
With this workshop we intend to present and discuss novel approaches in data management and information analytics. Overall aim of this workshop is to examine how advances in technology have changed traditional data management approaches and how these advances enable enterprises to increase the value of information. In the context of advances in technology, the goal of this workshop is to discuss and share best practices, experiences, models, architectures, methods and tools for data management and information analytics.
Challenges for data management arise not only from managing large data volumes, but also from an increased complexity in the data manufacturing system. Data often is provided from many heterogeneous sources. Data transfer and transformation routines are complex and often involve a variety and large number of database systems and applications. Furthermore, enterprises often not only utilize structured data, but also include more frequently semi-structured or unstructured data sources. Support for data integration, quality management, modeling and managing complex data manufacturing systems are crucial, in order to provide benefit for enterprises. In contrast to more traditional environments, data in these complex systems are often not certain, not always accessible or of different quality. This calls for different approaches in data management.
Another important topic regarding data management is data mining and analytics, which can expose interesting information about the data being collected. Further research challenges arise from the large amount of relationship data. Novel approaches in analyzing relationships between data, can provide additional insight and thus benefits enterprises. In these data-rich environments, privacy and data security provides further challenges for data management. Overall economic evaluations are required to assess the benefit of novel approaches of data management to enterprises.
The idea of the workshop is to provide a forum and platform for both researchers and practitioners to exchange knowledge, ideas and to learn from each other. Practitioners and researchers present findings and experience.
The workshop seeks contributions on concepts, models, architectures, methods and tools associated with data management and information analytics. In this regard, we encourage the submission of design science research in the form of constructs, models, methods and instantiations. We invite contributions from industry, academia and collaborative research as well as encourage postgraduate researchers to submit their work. Submissions may be any of the following: research papers, short papers, research in progress, case studies, teaching cases or experience reports.
Topics of interest include, but are not limited to:
Managing large Data Manufacturing systems
Organizational Concepts and best practice
Architectural Concepts
Data and Information Quality
Data Modeling
Methods for Data Management
Modeling and Analyzing Relationship Data
Modeling large Data Manufacturing systems
Data Warehousing and Data Cleansing
Data Visualization
Data privacy and integrity
Management of uncertain data
Accessibility of data
Mobile data management
Management of Sensor Data
Data integration
Integration and analyzing semi-structured and unstructured data
Text Analytics
Business Cases and Cost/Benefit Analysis of Data Management Approaches
Important Dates
Regular Paper Submission: April 06, 2010
Authors Notification: May 04, 2010
Final Paper Submission and Registration: May 19, 2010
Workshop Program Committee
Laure Berti-Équille, Université de Rennes 1, France
José Cordeiro, Polytechnic Institute of Setúbal / INSTICC, Portugal
Xiuzhen Feng, Beijing University of Technology, China
Cathal Gurrin, Dublin City University, Ireland
Frantisek Hunka, University of Ostrava, Czech Republic
Andy Koronios, University of South Australia, Australia
David L. Olson, University of Nebraska?Lincoln, United States
Marcin Sikorski, Gdansk University of Technology, Poland
Paper Submission
Prospective authors are invited to submit papers in any of the topics listed above.
Instructions for preparing the manuscript (in Word and Latex formats) are available at the conference Paper Templates web page. Please also check the web page with the Submission Guidelines.
Papers should be submitted electronically via the web-based submission system at: http://www.insticc.org/Primoris
Publications
All accepted papers will be published in the workshop proceedings book, under an ISBN reference, and on CD-ROM support.
Registration Information
At least one author of an accepted paper must register for the workshop. If the registration fees are not received by May 19, 2010, the paper will not be published in the workshop proceedings book.
Secretariat Contacts
ICSOFT Workshops - DMIA 2010
e-mail: icsoft.workshops.secretariat-AT-insticc.org
Data Management and Information Analytics - DMIA 2010
23 July, 2010 - Athens, Greece
In conjunction with the 5th International Conference on Software and Data Technologies - ICSOFT 2010
Co-Chairs
Markus Helfert
School of Computing, Dublin City University
Ireland
Brian Donnellan
National University of Ireland, Maynooth
Ireland
Scope and Goals
For several years research and practice has addressed various topics related to Data Management such as data modeling, data warehousing, data movement, database administration and data mining. However recent advances in technology provided us the possibility to gather enormous amounts of data. This resulted in many new challenges for data management. Most frequent examples of the technology advances are mobile, wireless and sensor technology providing many opportunities for innovative applications. The large amount of data, gathered anywhere from anything, requires different solutions than traditional data management approaches.
With this workshop we intend to present and discuss novel approaches in data management and information analytics. Overall aim of this workshop is to examine how advances in technology have changed traditional data management approaches and how these advances enable enterprises to increase the value of information. In the context of advances in technology, the goal of this workshop is to discuss and share best practices, experiences, models, architectures, methods and tools for data management and information analytics.
Challenges for data management arise not only from managing large data volumes, but also from an increased complexity in the data manufacturing system. Data often is provided from many heterogeneous sources. Data transfer and transformation routines are complex and often involve a variety and large number of database systems and applications. Furthermore, enterprises often not only utilize structured data, but also include more frequently semi-structured or unstructured data sources. Support for data integration, quality management, modeling and managing complex data manufacturing systems are crucial, in order to provide benefit for enterprises. In contrast to more traditional environments, data in these complex systems are often not certain, not always accessible or of different quality. This calls for different approaches in data management.
Another important topic regarding data management is data mining and analytics, which can expose interesting information about the data being collected. Further research challenges arise from the large amount of relationship data. Novel approaches in analyzing relationships between data, can provide additional insight and thus benefits enterprises. In these data-rich environments, privacy and data security provides further challenges for data management. Overall economic evaluations are required to assess the benefit of novel approaches of data management to enterprises.
The idea of the workshop is to provide a forum and platform for both researchers and practitioners to exchange knowledge, ideas and to learn from each other. Practitioners and researchers present findings and experience.
The workshop seeks contributions on concepts, models, architectures, methods and tools associated with data management and information analytics. In this regard, we encourage the submission of design science research in the form of constructs, models, methods and instantiations. We invite contributions from industry, academia and collaborative research as well as encourage postgraduate researchers to submit their work. Submissions may be any of the following: research papers, short papers, research in progress, case studies, teaching cases or experience reports.
Topics of interest include, but are not limited to:
Managing large Data Manufacturing systems
Organizational Concepts and best practice
Architectural Concepts
Data and Information Quality
Data Modeling
Methods for Data Management
Modeling and Analyzing Relationship Data
Modeling large Data Manufacturing systems
Data Warehousing and Data Cleansing
Data Visualization
Data privacy and integrity
Management of uncertain data
Accessibility of data
Mobile data management
Management of Sensor Data
Data integration
Integration and analyzing semi-structured and unstructured data
Text Analytics
Business Cases and Cost/Benefit Analysis of Data Management Approaches
Important Dates
Regular Paper Submission: April 06, 2010
Authors Notification: May 04, 2010
Final Paper Submission and Registration: May 19, 2010
Workshop Program Committee
Laure Berti-Équille, Université de Rennes 1, France
José Cordeiro, Polytechnic Institute of Setúbal / INSTICC, Portugal
Xiuzhen Feng, Beijing University of Technology, China
Cathal Gurrin, Dublin City University, Ireland
Frantisek Hunka, University of Ostrava, Czech Republic
Andy Koronios, University of South Australia, Australia
David L. Olson, University of Nebraska?Lincoln, United States
Marcin Sikorski, Gdansk University of Technology, Poland
Paper Submission
Prospective authors are invited to submit papers in any of the topics listed above.
Instructions for preparing the manuscript (in Word and Latex formats) are available at the conference Paper Templates web page. Please also check the web page with the Submission Guidelines.
Papers should be submitted electronically via the web-based submission system at: http://www.insticc.org/Primoris
Publications
All accepted papers will be published in the workshop proceedings book, under an ISBN reference, and on CD-ROM support.
Registration Information
At least one author of an accepted paper must register for the workshop. If the registration fees are not received by May 19, 2010, the paper will not be published in the workshop proceedings book.
Secretariat Contacts
ICSOFT Workshops - DMIA 2010
e-mail: icsoft.workshops.secretariat-AT-insticc.org
Other CFPs
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- Third Workshop on Model-based Testing in Practice (MoTiP'10)
- Third Workshop on Model-Driven Tool & Process Integration (MDTPI 2010)
- THIRD International Workshop on Model-Driven Product Line Engineering (MDPLE)
- First Workshop on Hands-on Platforms and tools for model-based engineering of Embedded Systems (HoPES'10)
Last modified: 2010-06-04 19:32:22