CALL FOR PAPERS
9th International Conference on Data Science, Technology and Applications DATA

website: http://www.dataconference.org

July 7 - 9, 2020 [Online Streaming]


In Cooperation with: ACM SIGMIS
Proceedings will be submitted for indexation by: DBLP, Thomson Reuters, EI, SCOPUS, Semantic Scholar, Google Scholar and Microsoft Academic.


IMPORTANT DATES:

Regular Paper Submission: February 14, 2020
Authors Notification (regular papers): April 15, 2020
Final Regular Paper Submission and Registration: April 29, 2020


Position Paper Submission: March 31, 2020
Authors Notification (position papers): May 7, 2020
Final Regular Paper Submission and Registration: May 20, 2020

Scope:
The purpose of the 9th International Conference on Data Science, Technology and Applications (DATA) is to bring together researchers, engineers and practitioners interested on databases, big data, data mining, data management, data security and other aspects of information systems and technology involving advanced applications of data.

Papers describing advanced methodologies, prototypes, systems, tools and techniques and general survey papers indicating future directions are also encouraged. Papers describing original work are invited in any of the areas listed. Accepted papers, presented at the conference by one of the authors, will be published in the conference proceedings. Acceptance will be based on quality, relevance and originality. Both full research papers and work-in-progress are welcome. There will be both oral and poster sessions.

Special sessions, dedicated to case-studies and commercial presentations, as well as demos or tutorials dedicated to technical/scientific topics are also envisaged: companies interested in presenting their products/methodologies or researchers interested in holding a tutorial, workshop or special session are invited to contact the conference secretariat or visit the conference website.

Conference Topics:
Area 1: Business Analytics
- Business Intelligence
- Statistics Exploratory Data Analysis
- Text Analytics
- Web Analytics
- Change Detection
- Data Analytics
- Data Warehouse Management
- Decision Support Systems
- Dimensional Modelling
- Information Integration
- Information Retrieval
- Semi-Structured and Unstructured Data
- Data Governance

Area 2: Data Science
- Data Fusion
- Pattern Recognition
- Predictive Modelling
- Support Vector Machines
- Data Science
- Data Mining
- Deep Learning
- Evolutionary Computing and Optimization
- Feature Selection
- Fuzzy Computing
- Hybrid Methods
- Neural Network Applications
- Process Mining
- Granular Computing

Area 3: Data Management and Quality
- Architectural Concepts
- Mobile Data Management
- Modeling and Managing Large Data Systems
- Open Data
- Organizational Concepts and Best Practices
- Smart Cities and Urban Data Analytics
- Transparency in Research Data
- City Data Management
- Data and Information Quality
- Data Management for Analytics
- Data Modeling and Visualization
- Data Structures and Data Management Algorithms
- Data Virtualization
- Industry 4.0
- Management of Sensor Data
- Linked Data
- Semantic Web Technologies for Data Management

Area 4: Big Data
- Big Data Applications
- New Computational Models for Big Data
- New Data Standards
- Social Data Analytics
- Social Web Search and Mining
- Big Data as a Service
- Big Data Infrastructure
- Big Data Search and Mining
- Big Data Security, Privacy and Trust
- Cloud/Grid/Stream Computing for Big Data
- Data and Information Quality for Big Data
- Deep Learning and Big Data
- Information Visualization
- Edge Computing
- In-Network Data Processing
- Energy-Efficient Computing
- In-Memory Databases

Area 5: Databases and Data Security
- Data Integrity
- WWW and Databases
- Data Privacy and Security
- Database Architecture and Performance
- Large Scale Databases
- Mobile Databases
- NoSQL Databases
- Object-Oriented Database Systems
- Open Source Databases
- Query Processing and Optimization


DATA KEYNOTE LECTURE
Wil van der Aalst, RWTH Aachen University, Germany
Ioana Manolescu, Inria, France


DATA CONFERENCE CHAIR:
Jorge Bernardino, Polytechnic of Coimbra - ISEC, Portugal

DATA PROGRAM CO-CHAIRS:
Slimane Hammoudi, ESEO, ERIS, France
Christoph Quix, Hochschule Niederrhein, University of Applied Sciences and Fraunhofer FIT, Germany

PROGRAM COMMITTEE
http://www.dataconference.org/ProgramCommittee.aspx

DATA Secretariat
Address: Avenida de S. Francisco Xavier, Lote 7 Cv. C
Tel: +351 265 520 185
Fax: +351 265 520 186
Web: http://www.dataconference.org
e-mail: data.secretariat@insticc.org