International Journal of Data Science - Call for Papers - Deadline September 1, 2023 for Next Issue
The Data Science Association International Journal of Data Science (IJDS) is calling for papers. The deadline for the next available IJDS issue is September 1, 2023. Guidelines for data science practitioners are different and more lax than academics: Length between four (4) and eighteen (18) single spaced pages in Word format.
If you would like to submit a paper contact IJDS Editor Michael Walker (email@example.com) or contact us here.
A few essentials for publishing in the IJDS:
- Submitted articles should not have been previously published or be currently under consideration for publication elsewhere.
- Conference papers may only be submitted if the paper has been completely re-written (taken to mean more than 50%) and the author has cleared any necessary permissions with the copyright owner if it has been previously copyrighted.
- All our articles are refereed through a double-blind process.
- All authors must declare they have read and agreed to the content of the submitted article. A full statement of our Ethical Guidelines for Authors (PDF) is available.
The IJDS publishes both academic research and practitioner papers (descriptive or predictive, and/or prescriptive), innovative ideas, case studies, surveys/reports and book reviews. Special Issues devoted to important topics will be published.
With the Age of Big Data upon us, we risk drowning in a flood of digital data. Big data spans five dimensions (volume, variety, velocity, volatility and veracity), generally steered towards one critical destination - value. Big data has now become a critical part of the business world and daily life. Containing big information and big knowledge, big data does indeed have big value. IJDS confronts the challenges of extracting a fountain of knowledge from "mountains" of big data.
Topics covered include:
- Big data cloud, mining and management
- Big data storage, processing, sharing and visualisation
- Big data systems, tools, theory and applications
- Business analytics, intelligence and mathematics
- Computer science, hacking skills
- Informatics and information systems and technology
- Machine learning, web-based decision making
- Management science, social sciences and statistics
- Mathematical optimisation and mathematics of decision sciences
- Multiple source data processing and integration
- Network and social-graph analysis
- Optimisation, performance measurement
- Security and privacy
- System analysis and theory
- Volume, velocity and variety of big data on cloud
IJDS employs an interdisciplinary approach and bridges the gap between different disciplines, including computer science, OR/MS, statistics, data mining, DSS, graphic design and human-computer interaction. The process of knowledge creation therefore can include multiple components and perspectives. By adopting such a diverse set of tools/techniques while employing the synergies involved, companies and organisations can make faster (real-time), frequent and fact-based decisions.
IJDS therefore aims to provide a professional forum for examining the processes and results associated with obtaining data, as well as munging, scrubbing, exploring, modelling, interpreting, communicating and visualising data. Data science takes data in cyberspace as a research object. The goal is an integrated and interconnected process designed to form a common ground from which a knowledge-based system can be built, shared and supported by professionals from different disciplines.
- Data scientists
- Strategic planners
- Leaders / decision makers
- Policy makers
- Applied statisticians
- Data analysts
- Database administrators
- Educators and graduate students
- Management scientists
- Operation researchers