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International Conference on Service-Oriented Computing

ICSOC 2021: Service-Oriented Computing – ICSOC 2021 Workshops pp 321–335Cite as

AI-Enabled Processes: The Age of Artificial Intelligence and Big Data

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Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 13236))

Abstract

Business processes, i.e., a set of coordinated tasks and activities carried out manually/automatically to achieve a business objective or goal, are central to the operation of public and private enterprises. Modern processes are often highly complex, data-driven, and knowledge-intensive. In such processes, it is not sufficient to focus on data storage/analysis; and the knowledge workers will need to collect, understand, and relate the big data (from open, private, social, and IoT data islands) to process analysis. Today, the advancement in Artificial Intelligence (AI) and Data Science can transform business processes in fundamental ways; by assisting knowledge workers in communicating analysis findings, supporting evidence, and making decisions. This tutorial gives an overview of services in organizations, businesses, and society. We introduce notions of Data Lake as a Service and Knowledge Lake as a Service and discuss their role in analyzing data-centric and knowledge-intensive processes in the age of Artificial Intelligence and Big Data. We introduce the novel notion of AI-enabled Processes and discuss methods for building intelligent Data Lakes and Knowledge Lakes as the foundation for Process Automation and Cognitive Augmentation in Business Process Management. The tutorial also points out challenges and research opportunities.

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Notes

  1. 1.

    Three-tier architecture is a well-established software application architecture that organizes applications into three logical and physical computing tiers: the presentation tier, or user interface; the application tier, where data is processed; and the data tier, where the data associated with the application is stored and managed.

  2. 2.

    https://www.elastic.co/elasticsearch/.

  3. 3.

    https://developers.google.com/knowledge-graph/.

  4. 4.

    https://www.wikidata.org/.

  5. 5.

    https://sites.google.com/view/di2019.

  6. 6.

    https://rrc.cvc.uab.es/?ch=17.

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Acknowledgements

We acknowledge the AI-enabled Processes (AIP) Research Centre (https://aip-research-center.github.io/) for funding part of this research.

Author information

Authors and Affiliations

  1. Macquarie University, Sydney, Australia

    Amin Beheshti, Quan Z. Sheng, Hamid-Reza Motahari Nezhad & Jian Yang

  2. University of New South Wales, Sydney, Australia

    Boualem Benatallah

  3. Servicenow, Santa Clara, CA, USA

    Fabio Casati

  4. University of Wollongong, Wollongong, Australia

    Aditya Ghose

Authors
  1. Amin Beheshti
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  2. Boualem Benatallah
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  3. Quan Z. Sheng
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  4. Fabio Casati
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  5. Hamid-Reza Motahari Nezhad
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  6. Jian Yang
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  7. Aditya Ghose
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Corresponding author

Correspondence to Amin Beheshti .

Editor information

Editors and Affiliations

  1. Zayed University, Dubai, United Arab Emirates

    Hakim Hacid

  2. Zayed University, Abu Dhabi, United Arab Emirates

    Monther Aldwairi

  3. Deakin University, Waurn Ponds, VIC, Australia

    Mohamed Reda Bouadjenek

  4. National Research Council C.N.R., Pisa, Italy

    Marinella Petrocchi

  5. University of Lyon, Villeurbanne, France

    Noura Faci

  6. Zayed University, Dubai, United Arab Emirates

    Fatma Outay

  7. Macquarie University, Sydney, NSW, Australia

    Amin Beheshti

  8. Technical University of Berlin, Berlin, Germany

    Lauritz Thamsen

  9. Royal Melbourne Institute of Technology, Melbourne, VIC, Australia

    Hai Dong

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Beheshti, A. et al. (2022). AI-Enabled Processes: The Age of Artificial Intelligence and Big Data. In: Hacid, H., et al. Service-Oriented Computing – ICSOC 2021 Workshops. ICSOC 2021. Lecture Notes in Computer Science, vol 13236. Springer, Cham. https://doi.org/10.1007/978-3-031-14135-5_29

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  • DOI: https://doi.org/10.1007/978-3-031-14135-5_29

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  • Online ISBN: 978-3-031-14135-5

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