Current Trends on Data Management
A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Computer Science & Engineering".
Deadline for manuscript submissions: 15 October 2024 | Viewed by 1293
Special Issue Editors
Interests: software engineering; automated testing; cloud computing
Special Issues, Collections and Topics in MDPI journals
Interests: wearable technologies for health and wellbeing applications; mobile and pervasive computing for assistive living; Internet of Things and assistive technologies; machine learning algorithms for physiological; inertial and location sensors; personal assistants and coaching for health self-management; activity detection and prediction methods
Special Issues, Collections and Topics in MDPI journals
Interests: Internet measurements; web transparency; online advertising; data analysis; machine learning
Special Issue Information
Dear Colleagues,
We live in a highly data-driven digital-first era. The creation of high volumes of data leads to the formation of large repositories, which necessitate the development of novel techniques to analyze, process and structure these data. The term "data management" pertains to the processes and procedures employed in handling data and involves creating, implementing, and overseeing plans, policies, programs, and practices that ensure the proper delivery, control, protection, and enhancement of the value of data and information assets over their entire lifespan.
New trends in cloudification, microservices, open data, or software as a service (SaaS) approaches, among others, have a significant impact on data management. In parallel, new approaches to Artificial Intelligence (AI), Machine Learning (ML), and Natural Language Processing (NLP) require the management of increasingly large amounts of datasets (e.g., Large Language Models, LLMs) and synthetic data (i.e., artificially generated data).
The main objective of this Special Issue is to bring together novel and impactful research on data management and the adoption of these techniques for practical applications. Specific topics of interest include, but are not limited to, the following:
- Data governance;
- Data storage and operations;
- Data integration and interoperability;
- Data confidentiality;
- Data security and protection;
- Data architecture and infrastructure;
- Synthetic data ;
- Open data.
Dr. Boni García
Prof. Dr. Mario Munoz-Organero
Dr. Patricia Callejo
Prof. Miguel Ángel Hombrados
Guest Editors
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Electronics is an international peer-reviewed open access semimonthly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
Keywords
- data management
- data governance
- data interoperability
- data confidentiality
- data security
- data infrastructure
- synthetic data
- open data
