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Manuscript Auditing →01Impact factor
Impact factor of Frontiers In Big Data (2026)
The impact factor shown here is the 2-year mean citedness: citations received in a year by the papers Frontiers In Big Data published in the two previous years, divided by the number of those papers. That is the same formula as the Journal Impact Factor, applied to the open citation data of OpenAlex. The journal is listed in JCR 2024, so it also has an official Journal Impact Factor published by Clarivate, which can differ because it counts citations from Web of Science journals only.
Rank in its subject categories
- Q1Multidisciplinary Sciencesrank 19 of 155 journals
- Q1Computer Science, Information Systemsrank 39 of 274 journals
- Q1Computer Science, Interdisciplinary Applicationsrank 31 of 182 journals
Quartiles here rank journals of the same Web of Science category by 2-year citedness; they are not the official JCR quartiles.
Citations and papers per year
Open access (listed in DOAJ); article processing charge listed at about US$1,418.
02Indexing
Indexing of Frontiers In Big Data
| List | Status |
|---|---|
| Science Citation Index Expanded (SCIE) | Not listed |
| Social Sciences Citation Index (SSCI) | Not listed |
| Arts & Humanities Citation Index (AHCI) | Not listed |
| Emerging Sources Citation Index (ESCI) | Not listed |
| Scopus | Not listed |
| Journal Citation Reports 2024 | ✓ Listed |
From the indexing lists used on ScholarsColab, updated 1 March 2026. Indexing can change: confirm on the Web of Science Master Journal List or the Scopus source list before submitting. Official Journal Impact Factors and JCR quartiles are published by Clarivate; the impact factor and quartile on this page are calculated from OpenAlex open data (see how the impact factor works).
03What it publishes
What Frontiers In Big Data publishes: real papers
Words that appear most often in the titles of the papers published here that we track. Choose one to see those papers:
04Published papers
Papers published in Frontiers In Big Data
Papers from the publication records ScholarsColab tracks, with their year and citations. Author names are not shown.
- Application of artificial intelligence in cervical cytology: a systematic review of deep learning models, datasets, and reported metrics20260 citations
- Decoding deception: state-of-the-art approaches to deep fake detection20260 citations
- Explainable attrition risk scoring for managerial retention decisions in human resource analytics20260 citations
- Deep learning-enabled hybrid systems for accurate recognition of text in seal images20260 citations
- EnDuSecFed: an ensemble approach for privacy preserving Federated Learning with dual-security framework for sustainable healthcare20260 citations
- Intelligent leak monitoring of oil pipeline based on distributed temperature and vibration fiber signals20250 citations
- Robust contactless fingerprint authentication using dolphin optimization and SVM hybridization20250 citations
- Robust detection framework for adversarial threats in Autonomous Vehicle Platooning20250 citations
- Finding the needle in the haystack—An interpretable sequential pattern mining method for classification problems20250 citations
- Time series forecasting for bug resolution using machine learning and deep learning models20250 citations
- Enhancing intelligence source performance management through two-stage stochastic programming and machine learning techniques20250 citations
- Privacy protection method for ADS-B air traffic control data based on convolutional neural network and symmetric encryption20250 citations
- PHTFNet-RPM: a probabilistic hybrid network with RPM for tobacco root disease forecasting20250 citations
- ULBERT: a domain-adapted BERT model for bilingual information retrieval from Pakistan's constitution20250 citations
- Domain-independent deception: a new taxonomy and linguistic analysis20250 citations
- Towards the neuromorphic Cyber-Twin: an architecture for cognitive defense in digital twin ecosystems20250 citations
- A review of AI-based radiogenomics in neurodegenerative disease20240 citations
- CrowdRadar: a mobile crowdsensing framework for urban traffic green travel safety risk assessment20230 citations
- Optimizing public health management with predictive analytics: leveraging the power of random forest20230 citations
- AI-powered smart emergency services support for 9-1-1 call handlers using textual features and SVM model for digital health optimization20230 citations
- Natural language processing for recommender systems20230 citations
- Toward explainable AI in radiology: Ensemble-CAM for effective thoracic disease localization in chest X-ray images using weak supervised learning20230 citations
- Fine-tuning or prompting on llms: evaluating knowledge graph construction task20230 citations
- Federated learning framework for IoT intrusion detection using tab transformer and nature-inspired hyperparameter optimization20230 citations
- Recommender systems for sustainability: overview and research issues20230 citations
- Predicting student self-efficacy in Muslim societies using machine learning algorithms20230 citations
- Healthcare analytics—A literature review and proposed research agenda20230 citations
- Sparse and Expandable Network for Google's Pathways20230 citations
- Navigating pathways to automated personality prediction: A comparative study of small and medium language models20230 citations
- Prediction and classification of obesity risk based on a hybrid metaheuristic machine learning approach20230 citations
- Cloud computing convergence: integrating computer applications and information management for enhanced efficiency20220 citations
- A review on individual and multistakeholder fairness in tourism recommender systems20200 citations
05Reviewer comments
Reviewer comments and rejection reasons for Frontiers In Big Data
No reviewer or editor comments have been shared for this journal yet. Did you submit here? Help other researchers by sharing the comments you received, anonymously.
Share reviewer comments for this journal →Across the reviewer comments researchers have shared with us, the points raised most often are figures, tables and equations (21%), literature and references (12%) and novelty and contribution (10%). Before you submit to Frontiers In Big Data, a Manuscript Audit by a PhD reviewer in your area checks your paper against exactly these points.
Audit my paper before I submit →Not sure yet? Check if your paper is ready for this journal: free, no AI, under 5 secondsPreparing to submit here? Make sure reviewers don't stop at the issues they raise most often. A PhD reviewer in your area can audit your manuscript section by section, and we can convert it into the journal's LaTeX template.
06Similar journals
Journals similar to Frontiers In Big Data
Journals that publish the closest work to the papers above, from the indexing lists:
- Neural Computing and ApplicationsScopusJCR 20243 similar papers
- International Journal of Engineering Trends and TechnologyScopus3 similar papers
- Frontiers in Plant ScienceSCIEScopusJCR 20245 similar papers
- Journal of Theoretical and Applied Information TechnologyScopus31 similar papers
- SustainabilitySCIESSCIScopusJCR 20245 similar papers
- Scientific ReportsSCIEScopusJCR 20247 similar papers
07Journal Finder
Find the right journal for your paper
Is Frontiers In Big Data right for your paper? Compare journals
Paste your title, keywords or abstract. We match it against 164,212 published journal papers, by ScholarsColab mentors and other researchers, and show where the closest work appeared, with each journal’s indexing (SCIE, SSCI, AHCI, ESCI, Scopus, JCR 2024).
How it works: no AI or language model is used. Your words are matched against the titles of real published journal papers, by our mentors and by other researchers (shown without names); journals are ranked by how many closely matching papers they published. Indexing comes from the SCIE, SSCI, AHCI, ESCI, Scopus and JCR 2024 lists, matched by journal name; “not found in our indexing lists” does not prove a journal is unindexed. Always check a journal’s scope and current indexing before submitting.
08Questions
Frequently asked questions
What is the impact factor of Frontiers In Big Data?
Based on OpenAlex citation data (October 2026), the 2-year impact factor of Frontiers In Big Data is 7.02: papers it published in the two previous years were cited 7.02 times on average in a year. The journal is listed in JCR 2024, so Clarivate also publishes an official Journal Impact Factor, which can differ.
What is the h-index of Frontiers In Big Data?
The h-index of Frontiers In Big Data is 53 (OpenAlex, October 2026): 53 of its papers have each been cited at least 53 times. Its i10-index is 296.
What is the APC of Frontiers In Big Data?
OpenAlex lists an article processing charge (APC) of about US$1,418 for Frontiers In Big Data, an open access journal (data from October 2026). APCs change and can differ by article type, country or discounts, so confirm the current charge on the journal’s website before submitting.
Is Frontiers In Big Data a Q1 journal?
By 2-year citedness, Frontiers In Big Data ranks 19 of 155 journals in Multidisciplinary Sciences, which places it in Q1 of that Web of Science category. This ranking is calculated by ScholarsColab from OpenAlex data; the official JCR quartile can differ.
Is Frontiers In Big Data indexed in Scopus?
Frontiers In Big Data is not listed in the Scopus list, according to the indexing lists used on ScholarsColab (updated 1 March 2026). Always confirm the current status on the official list before submitting.
Is Frontiers In Big Data an SCIE journal?
Frontiers In Big Data is not listed in SCIE or the other Web of Science indexes, according to the indexing lists used on ScholarsColab (updated 1 March 2026). Always confirm the current status on the official list before submitting.
Is Frontiers In Big Data in Journal Citation Reports (JCR)?
Yes. Frontiers In Big Data is listed in JCR 2024, so it has a Journal Impact Factor. For the current impact factor and quartile, check Journal Citation Reports.
What topics does Frontiers In Big Data publish?
The papers published in Frontiers In Big Data that we track most often mention learning, model, deep, systems, framework, machine. Check the journal’s aims and scope for its full coverage.
How many papers published in Frontiers In Big Data does ScholarsColab track?
We track 32 papers published in Frontiers In Big Data between 2020 and 2026, cited 0 times in total, with a median of 0 citations per paper.
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