Why Researchers Choose Journal of Data and Information Quality for High-Impact Publications
The Journal of Data and Information Quality (JDIQ) serves as a vital resource for scholars focused on the challenges and innovations in data management. Established by the Association for Computing Machinery (ACM), this journal emphasizes rigorous methodologies to ensure data integrity and usability across various applications. Researchers value JDIQ for its commitment to publishing work that bridges theoretical foundations with practical implementations in information systems.
Since its inception in 2009, JDIQ has built a reputation for fostering advancements in data quality assessment, cleansing techniques, and metadata standards. Its interdisciplinary approach attracts contributions from computer science, information science, and related domains, making it a hub for collaborative research. The journal's emphasis on reproducible results and empirical validation sets it apart, encouraging submissions that demonstrate real-world impact.
Publishing in the Journal of Data and Information Quality enhances a researcher's profile, given its inclusion in prestigious indexing services. The peer-review process, handled by experts in the field, ensures that accepted papers meet high standards of originality and relevance. For those navigating complex data environments, JDIQ provides insights into emerging trends like big data analytics and AI-driven quality control.
Audience includes academics, industry professionals, and policymakers interested in reliable information systems. The journal's scope extends to topics such as data provenance, quality metrics, and integration strategies, offering a platform for groundbreaking studies. As data volumes grow, the need for quality-focused research intensifies, positioning JDIQ at the forefront of this evolution.
To explore career opportunities in academia that align with data and information quality expertise, visit our higher education jobs section. This resource can help researchers find roles that leverage their publications in JDIQ.
Overview & History
The Journal of Data and Information Quality was launched in 2009 by the ACM to address the growing need for specialized research on data reliability. It emerged from the recognition that poor data quality undermines decision-making in computing and information management. Over the years, JDIQ has evolved to cover modern challenges like machine learning applications in data cleaning and blockchain for provenance tracking.
Key milestones include special issues on data quality in open science and collaborations with international conferences. The journal maintains a quarterly publication schedule, ensuring timely dissemination of findings. Its history reflects the ACM's dedication to computing excellence, with editorial policies adapting to technological shifts.
Scope and Disciplines Covered
JDIQ's scope encompasses all aspects of data and information quality, from foundational theories to applied solutions. It welcomes papers on quality dimensions such as accuracy, completeness, and timeliness, applied to diverse contexts like databases and knowledge graphs.
| Discipline | Description |
|---|---|
| Library Services | Focus on metadata standards and archival data management. |
| Data Management | Techniques for data integration, cleansing, and governance. |
| Information Management | Strategies for ensuring usability in information systems. |
| Computer Science | Algorithms and models for quality assessment. |
| Database Systems | Query optimization and quality in relational and NoSQL databases. |
These disciplines highlight JDIQ's broad appeal, encouraging cross-disciplinary submissions.
Key Journal Metrics
| Metric | Value | Source |
|---|---|---|
| Impact Factor | 1.833 | Clarivate JCR 2022 |
| 5-Year Impact Factor | 1.921 | Clarivate JCR 2022 |
| CiteScore | 3.2 | Scopus 2023 |
| SJR | 0.45 | Scopus 2023 |
| h-Index | 28 | Scopus |
These metrics underscore JDIQ's influence in the field, with steady growth in citations.
Indexing and Abstracting
JDIQ is indexed in major databases including Scopus, Web of Science (Emerging Sources Citation Index), DBLP, and Google Scholar. This ensures wide visibility for published works. For full details, visit the official journal homepage. Abstracting services like Inspec and EI Compendex further amplify its reach.
Publication Model and Fees
As a hybrid journal, JDIQ offers both subscription access and open access options. The standard model is subscription-based, with no mandatory fees for authors. For open access, an Article Processing Charge (APC) of $1,900 applies, covering gold OA publication. ACM supports waivers for authors from low-income countries. Policies align with Sherpa/RoMEO for self-archiving.
Submission Process and Guidelines
Submissions are handled via the ACM Manuscript Central system. Authors must follow ACM's template, ensuring anonymous review. Guidelines emphasize clear methodology, datasets, and quality evaluations. Initial checks occur within weeks, followed by peer review averaging 4-6 months. For tips, check our academic calendar for relevant timelines.
Editorial Board Highlights
The editorial board features experts like Editor-in-Chief Felix Naumann from Hasso Plattner Institute, alongside associate editors from universities worldwide. Their diverse backgrounds in data engineering and quality metrics guide the journal's direction. Board members contribute to special issues and workshops.
Why Publish in Journal of Data and Information Quality?
Publishing in JDIQ offers exposure to a targeted audience, enhancing career prospects. Its ACM affiliation boosts credibility, and rigorous review improves manuscript quality. Researchers benefit from fast indexing and potential for conference extensions. For those evaluating publication venues, consider how JDIQ aligns with rate my professor insights on faculty achievements.
Comparison with Similar Journals
| Journal | Impact Factor | Focus | Publisher |
|---|---|---|---|
| Journal of Data and Information Quality | 1.833 | Data quality methodologies | ACM |
| Information Systems | 3.2 | Broad IS topics | Elsevier |
| Data & Knowledge Engineering | 1.5 | Knowledge representation | Elsevier |
| Journal on Data Semantics | 1.1 | Semantic data | Springer |
JDIQ excels in specialized data quality, offering a niche advantage over broader journals.
Researcher Tips for Successful Submission
To succeed with Journal of Data and Information Quality submissions, prioritize novel contributions with empirical evidence. Use standard quality frameworks and provide reproducible code. Engage with recent issues for trends. Network via ACM events, and review guidelines thoroughly. For academic planning, explore our higher ed jobs to see how publications influence hiring.