ACM Journal of Data and Information Quality

Scope & Guideline

Transforming Insights into Information Excellence

Introduction

Welcome to your portal for understanding ACM Journal of Data and Information Quality, featuring guidelines for its aims and scope. Our guidelines cover trending and emerging topics, identifying the forefront of research. Additionally, we track declining topics, offering insights into areas experiencing reduced scholarly attention. Key highlights include highly cited topics and recently published papers, curated within these guidelines to assist you in navigating influential academic dialogues.
LanguageEnglish
ISSN1936-1955
PublisherASSOC COMPUTING MACHINERY
Support Open AccessNo
CountryUnited States
TypeJournal
Convergefrom 2009 to 2024
AbbreviationACM J DATA INF QUAL / ACM J. Data Inf. Qual.
Frequency4 issues/year
Time To First Decision-
Time To Acceptance-
Acceptance Rate-
Home Page-
Address1601 Broadway, 10th Floor, NEW YORK, NY 10019-7434

Aims and Scopes

The ACM Journal of Data and Information Quality focuses on advancing the understanding and methodologies related to data quality, information management, and the ethical implications of data usage. The journal serves as a platform for researchers and practitioners to share innovative approaches and solutions that address the multifaceted challenges of ensuring high-quality data in various domains.
  1. Data Quality Assessment and Improvement:
    Research on methodologies and frameworks for assessing and enhancing data quality, including techniques for data cleaning, validation, and completeness.
  2. Human-in-the-Loop Approaches:
    Exploration of interactive systems where human expertise is integrated into data curation processes, improving the quality of data through user involvement.
  3. Machine Learning and AI for Data Quality:
    Investigating the use of machine learning algorithms and artificial intelligence to automate and improve data quality tasks, such as anomaly detection and data cleansing.
  4. Ethics and Governance in Data Management:
    Studies focusing on the ethical considerations and governance frameworks necessary for responsible data usage, including fairness, transparency, and accountability.
  5. Multimodal Data Integration:
    Research on combining different types of data (text, images, time series) to enhance data quality and facilitate comprehensive analysis in various applications.
The ACM Journal of Data and Information Quality is currently witnessing several emerging themes that indicate a shift in focus toward cutting-edge methodologies and interdisciplinary approaches. These trends are shaping the future of data quality research and practice.
  1. AI-Driven Data Quality Solutions:
    A notable increase in research papers exploring the integration of artificial intelligence and machine learning in data quality tasks, signaling a trend towards automation and intelligent systems.
  2. Focus on Ethical Data Practices:
    Emerging themes around ethics and governance in data usage reflect a heightened awareness of the implications of data management, particularly concerning fairness and accountability.
  3. Human-Centric Data Curation:
    Research emphasizing human involvement in data processes is gaining traction, showcasing the importance of collaborative approaches in enhancing data quality.
  4. Contextual and Multimodal Data Quality:
    There is a growing interest in assessing data quality across various contexts and modalities, highlighting the need for comprehensive frameworks that address the complexities of modern data ecosystems.
  5. Application of Data Quality in Emerging Technologies:
    Increased publications relating to data quality in fields like IoT, blockchain, and social media analytics suggest a trend toward exploring data quality challenges in new technological landscapes.

Declining or Waning

While the journal has consistently emphasized several core areas, certain themes appear to be diminishing in prominence. This shift may reflect changing priorities in the field of data quality and the evolving landscape of data science.
  1. Traditional Data Cleaning Techniques:
    There seems to be a decline in papers focusing solely on traditional data cleaning techniques without integrating newer technologies or methodologies, indicating a shift towards more innovative solutions.
  2. Static Data Quality Frameworks:
    Research centered on static models for data quality assessment is becoming less frequent, as there is a growing preference for dynamic and adaptive frameworks that can respond to real-time data changes.
  3. Basic Data Management Practices:
    Papers discussing foundational data management practices are waning, likely due to a focus on more complex and integrated approaches that incorporate advanced technologies like AI and machine learning.

Similar Journals

International Journal of Web Information Systems

Pioneering research for the evolving web landscape.
Publisher: EMERALD GROUP PUBLISHING LTDISSN: 1744-0084Frequency: 4 issues/year

The International Journal of Web Information Systems is a distinguished publication dedicated to advancing the field of web information systems, offering a platform for high-quality research and innovative practices. Published by EMERALD GROUP PUBLISHING LTD in the United Kingdom, this journal has established itself as a vital resource for researchers, practitioners, and academics from various disciplines, particularly in Computer Networks and Communications and Information Systems, as evidenced by its ranking in the 2023 quartile assessments (Q3) and Scopus rankings. With an H-index reflecting its impact within the academic community and a publication window spanning from 2005 to 2024, the journal is committed to fostering scholarly exchange and collaboration. While it currently does not have open access options, it provides valuable insights and breakthroughs that are essential for professionals and students navigating the ever-evolving digital landscape.

Big Data Mining and Analytics

Shaping Tomorrow's Technologies with Big Data Insights
Publisher: TSINGHUA UNIV PRESSISSN: Frequency: 4 issues/year

Big Data Mining and Analytics, published by TSINGHUA UNIVERSITY PRESS, stands at the forefront of interdisciplinary research in the fields of Artificial Intelligence, Computer Networks and Communications, Computer Science Applications, and Information Systems. With an impressive Q1 ranking in multiple categories as of 2023, this journal serves as a critical platform for researchers and professionals eager to explore innovative techniques and methodologies related to big data analytics. Since its transition to Open Access in 2018, Big Data Mining and Analytics has aimed to increase the visibility and accessibility of its cutting-edge research, making permanent strides in the global academic landscape. Housed in Beijing, China, and actively embracing the converged years from 2018 to 2024, the journal aims to cultivate a rich discourse on emerging trends and applications, ensuring its relevance in a rapidly evolving technological environment. Join a vibrant community of scholars dedicated to advancing the frontiers of knowledge in big data.

INTERNATIONAL JOURNAL OF COOPERATIVE INFORMATION SYSTEMS

Navigating the Future of Cooperative Information Systems
Publisher: WORLD SCIENTIFIC PUBL CO PTE LTDISSN: 0218-8430Frequency: 4 issues/year

INTERNATIONAL JOURNAL OF COOPERATIVE INFORMATION SYSTEMS

Published by WORLD SCIENTIFIC PUBL CO PTE LTD, the INTERNATIONAL JOURNAL OF COOPERATIVE INFORMATION SYSTEMS plays a pivotal role within the fields of Computer Science and Information Systems. With a focus on the development and application of cooperative information systems, this journal aims to foster innovation and collaborative research among scholars and professionals. Established in 1996, the journal has consistently published high-quality research that contributes to a better understanding of cooperative methodologies, enhancing system efficiencies across various applications. While its impact factor remains undisclosed, the journal is positioned in the Q4 category of the Scopus rankings, indicating a growing presence in the academic community. Although it does not offer open access, its rich repository of articles remains accessible to subscribers and relevant institutions. Located in Singapore, this journal will continue to serve as a critical resource for researchers, practitioners, and students keen on exploring the evolving dynamics of information systems in today's interconnected world.

Frontiers in Big Data

Exploring New Horizons in Big Data Research
Publisher: FRONTIERS MEDIA SAISSN: Frequency: 1 issue/year

Frontiers in Big Data, published by Frontiers Media SA in Switzerland, is a leading open access journal that has established itself as a vital resource for scholars and practitioners in the expanding realms of artificial intelligence, computer science, and information systems since its inception in 2018. With an impressive impact factor reflected in its Q2 rankings across multiple categories, including Artificial Intelligence, Computer Science (Miscellaneous), and Information Systems, this journal serves as a pivotal platform for disseminating groundbreaking research and promoting interdisciplinary collaboration. The journal's commitment to open access ensures that high-quality research is readily accessible to a global audience, fostering the exchange of innovative ideas and advancements in big data technologies. By creating an inclusive space for diverse perspectives, Frontiers in Big Data aims to bridge the gap between theoretical research and practical application, making it an essential read for anyone invested in the future of data science.

International Journal of Data Warehousing and Mining

Unlocking the Future of Data Management
Publisher: IGI GLOBALISSN: 1548-3924Frequency: 1 issue/year

International Journal of Data Warehousing and Mining, published by IGI Global, is a vital resource in the field of data management and analytics, catering to researchers, professionals, and students alike. With ISSN 1548-3924 and E-ISSN 1548-3932, this journal has been at the forefront of disseminating pioneering research since its inception in 2005 and will continue to do so through 2024. Despite its current categorization in the Q4 quartile for Hardware and Architecture as well as Software, and its Scopus rankings, the journal aims to foster innovation within the domains of data warehousing, data mining, and their applications across various sectors. The absence of an open access option does not diminish its significance; rather, it ensures that the journal maintains rigorous peer-review standards, providing high-quality research outputs that contribute to ongoing discussions and advancements within the field. Researchers and practitioners looking to stay updated on the latest trends and methodologies will find the International Journal of Data Warehousing and Mining an indispensable tool in their academic and professional endeavors.

Acta Informatica Pragensia

Transforming Ideas: Open Access to the Future of Information Technology.
Publisher: UNIV ECONOMICS, PRAGUEISSN: Frequency: 2 issues/year

Acta Informatica Pragensia is a prominent open access journal published by UNIV ECONOMICS, PRAGUE, which has been dedicated to advancing the fields of Computer Science Applications, Information Systems, Library and Information Sciences, and Management Information Systems since its inception in 2012. Situated in the beautiful Czech Republic, this journal aims to foster academic dialogue and disseminate high-quality research across these interdisciplinary domains. With an H-index indicating its growing impact, Acta Informatica Pragensia offers authors the opportunity to publish their findings in a Q4 ranked journal within significant categories according to the 2023 metrics, including a notable Q3 in Library and Information Sciences. Its placement in the Scopus ranks also showcases its relevance in the field, including a solid position in the 58th percentile for Library and Information Sciences. The journal's open access model ensures that research is widely available, empowering students, researchers, and professionals to engage with the latest innovations and trends. Submissions from diverse backgrounds are welcomed, making it an essential resource for those seeking to contribute to the evolution of information technology and systems.

International Journal of Data Science and Analytics

Unleashing the Power of Analytics for Tomorrow
Publisher: SPRINGERNATUREISSN: 2364-415XFrequency: 4 issues/year

International Journal of Data Science and Analytics, published by SpringerNature, is a leading peer-reviewed journal dedicated to advancing the fields of data science and analytics. Since its inception in 2016, the journal has become an essential platform for researchers, professionals, and students, promoting the exchange of innovative ideas and cutting-edge research. With an impressive categorization in Q2 across multiple domains including Applied Mathematics, Computational Theory and Mathematics, and Information Systems, it demonstrates a notable impact within the academic community, as reflected by its high rankings in various Scopus categories. The journal emphasizes rigorous methodologies and practical applications of data science, making it a valuable resource for those seeking to enhance their understanding and application of data-driven solutions. Although it currently does not operate as an open-access journal, it is committed to disseminating high-quality research that shapes the future of analytics and computation. The journal's headquarters in Switzerland further enriches its international scope, fostering a global dialogue among scholars and practitioners alike.

DATA & KNOWLEDGE ENGINEERING

Transforming Data into Knowledge for a Smarter World
Publisher: ELSEVIERISSN: 0169-023XFrequency: 6 issues/year

Data & Knowledge Engineering is a prestigious, peer-reviewed journal dedicated to the fields of data management, information systems, and knowledge engineering. Published by Elsevier in the Netherlands, this journal serves as a critical resource for researchers, professionals, and students alike, offering a platform for high-quality, original research and innovative approaches in the realm of data-driven technologies and methodologies. With a considerable impact factor and classified in the Q2 quartile for Information Systems and Management, it ranks 47th out of 148 journals in its category, placing it in the esteemed 68th percentile according to Scopus metrics. Data & Knowledge Engineering covers a wide array of topics including database systems, data mining, and knowledge representation, ensuring that it remains at the forefront of advancing understanding and application in these dynamic fields. Engage with compelling articles and significant findings published since its inception in 1985, as the journal continues to shape the future of data-centric research up to 2024 and beyond.

Data Technologies and Applications

Advancing Knowledge in Data Technologies
Publisher: EMERALD GROUP PUBLISHING LTDISSN: 2514-9288Frequency: 4 issues/year

Data Technologies and Applications is a leading academic journal published by Emerald Group Publishing Ltd, captivating the interest of researchers, professionals, and students alike within the dynamic fields of Information Systems and Library and Information Sciences. With its ISSN 2514-9288 and E-ISSN 2514-9318, this journal holds a commendable Q2 ranking in Library and Information Sciences and a Q3 ranking in Information Systems as of 2023, reflecting its impact and contribution to ongoing discourse in these disciplines. Operating with an open access model, it provides a platform for accessing high-quality research that encompasses innovative methodologies and applications of data technologies. The journal's scope includes interdisciplinary studies that leverage data to enhance decision-making, improve information retrieval, and foster technological convergence. Housed in the United Kingdom, the journal facilitated its first publication in 2018, with a commitment to fostering valuable academic conversations through to 2024 and beyond. Engage with insightful research that shapes the future of data technologies and applications, making this journal an essential resource for anyone invested in the advancement of knowledge in these pivotal fields.

GEOINFORMATICA

Pioneering Methodologies for a Spatially Aware World
Publisher: SPRINGERISSN: 1384-6175Frequency: 4 issues/year

GEOINFORMATICA is a leading journal in the field of geoinformatics, widely recognized for its contributions to both Geography, Planning and Development as well as Information Systems. Published by Springer, this journal holds a distinguished Q1 ranking in Geography and a Q2 ranking in Information Systems as of 2023, reflecting its high-impact research contributions and authoritative voice in these disciplines. Since its inception in 1997, GEOINFORMATICA has provided a platform for innovative research, methodologies, and applications related to geographic information science, spatial data analysis, and remote sensing technologies. The journal's rigorous peer-review process and strategic positioning within the academic landscape allow it to attract a diverse array of publications, assisting researchers, professionals, and students in understanding complex spatial phenomena. While the journal does not offer Open Access, it remains a vital resource located in the Netherlands, and its indexed status has secured impressive Scopus rankings—#131 in Geography, Planning and Development, and #134 in Information Systems, showcasing its robust scholarly influence. Explore the latest developments and cutting-edge research through GEOINFORMATICA, where scholarly excellence converges with real-world relevance.