World's Best Scientists 2026 revealed!
Data and Knowledge Engineering
H-index 15

Data and Knowledge Engineering

Ranking & Metrics

Discipline name Position Best Scientists Publications D-Index
Computer Science 387 69 76 15

Additional Metrics

Number of Best Scientists*: 77
Documents by Best Scientists*: 80
Top 100 Ranked Scientists*: 1
SCIMAGO H-index: 96
SCIMAGO SJR: 0.682
Impact Factor: 2.6

Overview

Top Research Topics at Data and Knowledge Engineering?

The journal tackles a plethora of topics, such as Data warehouse, Data science, Knowledge engineering, Knowledge-based systems and Knowledge management.

  • Data warehouse (50.00%)
  • Data science (50.00%)
  • Knowledge engineering (50.00%)

Papers citation over time

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The top authors publishing in Data and Knowledge Engineering (based on the number of publications) are:

  • R. C. Ting (1 papers) absent at the last edition,
  • Fred J. Maryanski (1 papers) absent at the last edition,
  • Sanjay Kumar Madria (1 papers) published 1 paper at the last edition.

The overall trend for top authors publishing in this journal is outlined below. The chart shows the number of publications at each edition of the journal for top authors.

Only papers with recognized affiliations are considered

Insufficient data to conduct the analysis

Publication chance based on affiliation

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Returning Authors Index

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The experience to innovation index

Our experience to innovation index was created to show a cross-section of the experience level of authors publishing in a journal. The index includes the authors publishing at the last edition of a journal, grouped by total number of publications throughout their academic career (P) and the total number of citations of these publications ever received (C).

The group intervals were selected empirically to best show the diversity of the authors' experiences, their labels were selected as a convenience, not as judgment. The authors were divided into the following groups:

  • Novice - P < 5 or C < 25 (the number of publications less than 5 or the number of citations less than 25),
  • Competent - P < 10 or C < 100 (the number of publications less than 10 or the number of citations less than 100),
  • Experienced - P < 25 or C < 625 (the number of publications less than 25 or the number of citations less than 625),
  • Master - P < 50 or C < 2500 (the number of publications less than 50 or the number of citations less than 2500),
  • Star - P ≥ 50 and C ≥ 2500 (both the number of publications greater than 50 and the number of citations greater than 2500).

Further Career Opportunities in the Field of Data and Knowledge Engineering

Many students and professionals who frequent Data and Knowledge Engineering research may be curious about career opportunities in this rapidly expanding field. There are numerous job possibilities, from data analysts and data scientists to knowledge engineers. For instance, one can explore becoming a teacher in the field of data and knowledge engineering at a private school. These roles require unique skills and offer diverse experiences that can be deeply rewarding and impactful. To become a private school teacher in the field of Data and Knowledge Engineering, it is essential to meet certain requirements in both education and experience. These prerequisites might include a degree in a related field and a specified number of hours of teaching experience. For more detailed information on these requirements, particularly for those based in the Arizona region, we recommend visiting this page on private school teacher requirements in Arizona. It’s of utmost importance to understand that these careers not only hold the potential for personal and professional development but also contribute to the increment of knowledge and evolution of these vital sectors.

Top Publications

  • Interpretable Anomaly Prediction: Predicting anomalous behavior in industry 4.0 settings via regularized logistic regression tools

    Rocco Langone;Alfredo Cuzzocrea;Nikolaos Skantzos

    (2020)
    75 Citations
  • The impact of psycholinguistic patterns in discriminating between fake news spreaders and fact checkers

    (2021)
    59 Citations
  • Applying the CRISP-DM data mining process in the financial services industry: Elicitation of adaptation requirements

    (2022)
    42 Citations
  • Group-based privacy preservation techniques for process mining

    Majid Rafiei;Wil M.P. van der Aalst

    (2021)
    38 Citations
  • Types and taxonomic structures in conceptual modeling: A novel ontological theory and engineering support

    Giancarlo Guizzardi;Giancarlo Guizzardi;Claudenir M. Fonseca;João Paulo A. Almeida;Tiago Prince Sales

    (2021)
    36 Citations
  • Trustworthy journalism through AI

    (2023)
    34 Citations
  • Discovering business process simulation models in the presence of multitasking and availability constraints

    Bedilia Estrada-Torres;Bedilia Estrada-Torres;Manuel Camargo;Marlon Dumas;Luciano García-Bañuelos

    (2021)
    32 Citations
  • On the explanatory power of Boolean decision trees

    (2022)
    30 Citations
  • Pairing Conceptual Modeling with Machine Learning

    (2021)
    30 Citations
  • Discovering rare correlated periodic patterns in multiple sequences

    Philippe Fournier-Viger;Peng Yang;Zhitian Li;Jerry Chun-Wei Lin

    (2020)
    21 Citations

Related Online Degrees & Career Pathways

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Best Scientists Contributing to This Journal

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