Data Intelligence Journal CfP: Metadata as Data Intelligence

Call for papers

Data Intelligence, MIT Press Direct

Special issue/title:

Title: Metadata as Data Intelligence

Call for Submission

Metadata, as a type of data, describes content, provides context, documents transactions, and situates data. As AI activities accelerate, so has the interest in how metadata can be leveraged for machine learning and related activities. The growing interest stems from the fact that metadata is intelligent data and essential to both FAIR (findable, accessible, interoperable and reusable) data and AI ready applications. As part of this trend, researchers across nearly every discipline as well as front-line data stewards have been advancing metadata approaches, applications, and overall metadata-related operations.

This special issue of Data Intelligence invites submission from researchers and practitioners across all disciplines and sectors (academia, industry, government, etc.) to report on metadata practices, innovations, and work under development addressing metadata as data intelligence. Data intelligence is viewed widely, and encompasses metadata standards and processes, addressing areas such as knowledge organization, ontology and semantic web development, machine learning, deep learning, linked-data analysis, knowledge graphs, data visualisation and other related areas. We welcome submissions of the following three types:

• Research articles presenting novel or state-of-the-art research findings on the latest developments, up-to-date issues, or challenges covering metadata generation, metadata analysis, metadata interoperability, metadata integration, FAIR metadata, data discovery, dataset quality information and related topics.
  
• Practice/implementation articles reporting on the implementation of metadata standards, vocabulary services, community of practices, FAIR metadata, and any applications that utilize metadata.
  
• Opinion/vision articles discussing current practices, research trends, or technologies, or providing a perspective on future directions for metadata development and utilization.

Data Intelligence (DI) on Metadata for Data Intelligence. DI  is an open-access, metadata-centric journal intended for data creators, curators, stewards, policymakers, and domain scientists/researchers as well as communities interested in sharing data. DI informs industry leaders, researchers, and scientists engaged in sharing and reusing data, metadata, knowledge bases, and data visualization tools. In addition to traditional articles addressing methodologies and/or resources, the journal also publishes “data articles” in the form of knowledge graphs, ontologies, and linked datasets.

Co-editors for the special issue: Jane Greenberg, Mingfang Wu

Important dates

• Submission Deadline: Oct. 31 2021
• Notification of acceptance: Dec. 31, 2021
• Revised/final manuscripts due: Feb. 10, 2022
• Publication of special issue: March 2022

Submission instructions

Prospective authors should submit papers via the journal’s online submission system at https://mc03.manuscriptcentral.com/di. All papers will follow the usual DI’s peer review process. Authors are suggested to follow the journal’s Submission Guidelines. There is no page limitation to submitted manuscripts, however, a research article should have no less than 8 pages, the other two types of articles can be shorter.  

When authors submit a paper, designate your paper as “special issue”, and specify “Metadata special issue” and  nominate your paper types in the “cover letter” (a box to be filled in the submission form Step 6: Details and Comments), for example, Metadata special issue, paper type: research paper.

Further information

For questions regarding this special issue, please contact the special issue editors: Jane Greenberg (jg3243@drexel.edu) and Mingfang Wu (mingfang.wu@ardc.edu.au).

Jane Greenberg, Ph.D., Alice B. Kroeger Professor, Director of the Metadata Research Center, College of Computing & Informatics, Drexel University, Philadelphia, PA – U.S.A.

Mingfant Wu, Ph.D., Senior Research Data Specialist, Australian Research Data Commons (ARDC), Melbourne office: Monash University, Melbourne, Australia