IEEE Data Descriptions Launches as First IEEE Journal Focused on Datasets

IEEE Data Descriptions (IEEE-DATA), a periodical published on behalf of all IEEE Societies and Technical Councils, was launched in early May. IEEE-DATA  is a specialized journal that publishes peer-reviewed, concise articles detailing datasets across various domains, promoting open and reproducible scientific research. The founding Editor-in-Chief, Stephen Makonin, first presented the idea during the June 9 (2022) IEEE DataPort Steering Committee meeting, of which he is a member.

The journal’s primary aim is to enhance dataset visibility and utility through comprehensive descriptions, which include data collection methods, data quality assessments, and detailed metadata. To ensure the datasets are broadly usable, they must be findable, accessible, interoperable, and reusable, with a strong preference for storage on IEEE DataPort or other permanent repositories.

There are three types of articles that can be submitted for review: descriptors, collections, and metadata. Descriptor articles (the main type of article published) describe the published (or soon-to-be-published) dataset. In essence, this is a detailed manual on the dataset — what it is and how to use it. Similarly, collections articles follow the lead and expectations of Descriptor articles and will focus on groups of datasets collected during or created from a competition, hackathon, or event. 

Meta articles depart from but follow the lead and expectations of Descriptor articles. Meta articles are articles that allow for discussion about data. Authors can express their findings about data in several areas, including, but not limited to: standardized formats for data in a given area (e.g., collecting power data from sub-stations), surveys of several datasets of a given type (e.g., GIS, time-series, etc.), data that are a library of models for a given AI or machine learning algorithm or system, data or dataset that is metadata of existing published datasets, comparing many similar datasets in an area to create meta-statistics data; or, any other data topics that may not have traditional scientific experimental results.

IEEE Data Descriptions is a gold, fully open-access publication and is one of the first to have an open review process. Until IEEE-DATA receives an impact factor (usually three years), the standard APC will be heavily discounted. Accepted articles have a recommended length of 4—8 pages and any extra information can be submitted as supplementary information, which will be published alongside the article on IEEE Xplore. 

Visit https://www.ieee-data.org/ for more information and instructions on how to submit your manuscript today.