The CODATA Data Science Journal is a peer-reviewed, open access, electronic journal, publishing papers on the management, dissemination, use and reuse of research data and databases across all research domains, including science, technology, the humanities and the arts. The scope of the journal includes descriptions of data systems, their implementations and their publication, applications, infrastructures, software, legal, reproducibility and transparency issues, the availability and usability of complex datasets, and with a particular focus on the principles, policies and practices for open data.
All data is in scope, whether born digital or converted from other sources.
Manuscript Submission Deadline: April 30, 2023
Recent changes in data science are transforming cybersecurity in a computing context. Applied science is the process of applying scientific methods, machine learning techniques, processes, and systems to data. While Cybersecurity Data Science (CSDS) enables more actionable and intelligent computing in the domain of cybersecurity as compared to traditional methods. It encompasses the rapidly growing practice of applying data science to prevent, detect, and remediate cybersecurity threats.
Cybersecurity data science is a fast-developing field that uses data science techniques to address cybersecurity issues. Data-driven, statistical, and analytical methodologies are increasingly used to close security holes. It examines the healthcare, transportation, surveillance, social media, and law enforcement sectors, in order to evaluate the specific issues they pose and how they can be addressed.
Cybersecurity data science is the focus of this special issue, with analytics supporting the most recent trends to optimize security solutions. The data is acquired from reliable cybersecurity sources. Using machine learning, the problem also aims to develop a multi-layered cybersecurity modeling framework. Data-driven intelligent decision-making can help defend systems against cyberattacks as we address cybersecurity data science and pertinent methodologies.
Special Collection Editors:
Zhenfeng Liu, Shanghai Maritime University
Xiaogang Ma, University of Idaho
Anwar Vahed, Data Intensive Research Initiative of South Africa
Posted on 06 Feb 2023
Posted on 09 Nov 2022
The Data Science Journal (https://datascience.codata.org/) is seeking papers for a special collection devoted to “Data Management Planning across Disciplines and Infrastructures”. Papers should focus on work related to Data Management Plans and their implementation, not data management per se.
Deadline for submissions: November 15th 2022 (UPDATE: deadline is now December 15th 2022
Details:
Data Management Plans (DMPs) are evolving. Several communities address challenges in developing DMP templates, e.g., to provide proper guidance across disciplines, used collaboratively along the data life cycle, or in the development of machine-actionable tools to facilitate efficient data management and sharing as well as fostering the reuse of (pieces) of already existing DMPs in new research context. Thereby, DMP templates do not only have to provide tailored guidance, but they should also ensure interoperability across research disciplines to foster multidisciplinary research. Although DMPs support the management of research data, DMP tools are often not integrated into researchers’ project workflows yet, but serve as an additional component next to project management software, electronic lab notebooks, metadata tools, etc..
The international Data Science Journal seeks papers describing practical experiences, concepts, and future directions on the design and deployment of effective data management. Journal’s topics cover hypothesis and investigation planning, data management planning, organization and operation, reproducibility planning, provenance recording, and data maintenance and publication are considered in their entirety.
For the collection, we welcome papers from researchers, data professionals, data managers and curators, data providers, founders, IT specialists, software developers, and others, who are using, developing, or experimenting with the effective use of data management planning. Submissions from lab researchers and practitioners are particularly encouraged, as contributions from open-source movements. Papers might, e.g., focus core activities of experimentation, data processing and analysis, long-term preservation or data sharing, or consider the integration of data management planning into existing or future infrastructures. This could reflect innovative research into new directions for DMPs. Moreover, papers detailing practical examples on supporting researchers are welcomed.
Submissions can be made in one or several of the following categories:
For further information and submission details see guidance of the Data Science Journal: https://datascience.codata.org/about/submissions.
Published articles will be charged with a fee of £650, covering all publication costs (editorial processes; web hosting; indexing; marketing; archiving; DOI registration; etc.) and ensuring full (golden) open access, under a Creative Commons Attribution License.
Collection editors (in alphabetical order):
Ivonne Anders, Kevin Ashley, Daniela Hausen, Christin Henzen, Sarah Jones, Tomasz Miksa, Sebastian Netscher, Maria Praetzellis, Chris Wiley
Posted on 10 Aug 2022