Journal of Data and Information Quality

Aims & Scope

JDIQ is a multi-disciplinary journal that attracts papers ranging from theoretical research to algorithmic solutions to empirical research to experiential evaluations.

Its mission is to publish high impact articles contributing to the field of data and information quality (IQ).

IQ covers a wide range of dimensions including accuracy and completeness, provenance, lineage and trust, understandability and accessibility.

Research contributions can range from modeling and measurement of quality, to improvement of quality with data cleansing methods, to organizational management of quality, to evaluations of quality in real scenarios.

Given the diversity of disciplines and author interests, we also welcome experience papers, typically submitted by a practitioner or industrial researcher who has a compelling application, interesting dataset or valuable teaching tool, to share with our readers.

Finally, we are accepting two-page vision papers that describe a major research challenge to the JDIQ community.

View Aims & Scope

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Metrics & Ranking

Impact Factor

Year	Value
2025	2.9

Journal Rank

Year	Value
2024	10293

Journal Citation Indicator

Year	Value
2024	354

SJR (SCImago Journal Rank)

Year	Value
2024	0.565

Quartile

Year	Value
2024	Q2

h-index

Year	Value
2024	32

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Abstracting & Indexing

Journal is indexed in leading academic databases, ensuring global visibility and accessibility of our peer-reviewed research.

• Scopus
• Google Scholar
• Web of Science

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Subjects & Keywords

Journal’s research areas, covering key disciplines and specialized sub-topics in Computer Science and Decision Sciences, designed to support cutting-edge academic discovery.

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Most Cited Articles

The Most Cited Articles section features the journal's most impactful research, based on citation counts. These articles have been referenced frequently by other researchers, indicating their significant contribution to their respective fields.

• The Web of False Information

  Citation: 232

  Authors: Savvas, Michael, Jeremy, Nicolas

• Biases in Large Language Models: Origins, Inventory, and Discussion

  Citation: 194

  Authors: Roberto, Simone, Björn

• One Size Does Not Fit All---A Contingency Approach to Data Governance

  Citation: 161

  Authors: Kristin, Boris, Hubert

• Overview and Framework for Data and Information Quality Research

  Citation: 139

  Authors: Stuart E., Richard Y., Yang W., Hongwei

• Anserini

  Citation: 116

  Authors: Peilin, Hui, Jimmy

• Automated Quality Assessment of Metadata across Open Data Portals

  Citation: 116

  Authors: Sebastian, Jürgen, Axel

• Data Transparency with Blockchain and AI Ethics

  Citation: 89

  Authors: Elisa, Ahish, Zehra

• The Effects and Interactions of Data Quality and Problem Complexity on Classification

  Citation: 89

  Authors: Roger, Paul

• On Graph-Based Name Disambiguation

  Citation: 83

  Authors: Xiaoming, Jianyong, Xu, Lizhu, Bing

• Representing Data Quality in Sensor Data Streaming Environments

  Citation: 71

  Authors: A., W.

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