Call for Chapters


Business intelligence (BI) aims to support decisions, not only in the business area stricto sensu, but also in the domains of health, environment, energy, transportation, science, etc. It provides a transverse vision of an organization's data and allows accessing quickly and simply to strategic information. For this sake, data must be extracted, grouped, organized, aggregated and correlated with methods and techniques such as data integration (ETL), data warehousing, online analytical processing (OLAP), reporting, data mining and machine learning. BI is nowadays casually used both in large companies and organizations, and small and middle-sized entreprises, thanks to the advent of cloud computing and cheap BI-as-a-service. The development of BI in the 1990's has also sparkled vivid research that currently addresses new challenges in big data.

Objective of the Book

Mashing up internal and external data is acknowledged as the best way to provide the most complete view for decision making. Yet, tackling data heterogeneity has always been an issue. With big data coming into play, benefits from processing external data look even better, but issues are also more complex. Data volume challenges even warehouses that were tailored for large amounts of data. Velocity challenges the very idea of materializing historicized data. Variety and veracity issues remain, but at a much greater extent. Finally, actually extracting intelligible information from big data (data value) requires novel methods. Finally, new technologies such as cloud computing, Hadoop/Spark and NoSQL databases also question classical BI.

This book plans to gather top-level research contributions addressing problems related to the five "Vs" of big data, technological issues, as well as big data analytics applications. Contributions will be reviewed by an international scientific committee.

Target Audience

The target audience of this book will be composed of

  • researchers
  • practitioners from the industry
  • graduate students in the fields of computer science, data science and business intelligence.

Recommended topics

Recommended topics include, but are not limited to, the following:

  • Data volume issues: physical data management, scalability issues, performance optimization, NoSQL storage
  • Data variety issues: information retrieval, complex data preparation/ETL, data lakes, metadata extraction and management, semantics, linked data...
  • Data velocity issues: cloud/parallel processing for analytics...
  • Data veracity issues: data quality, data security (privacy, integrity...)
  • Data value issues: data visualization, data storytelling, personalization, recommendation, collaborative analyses...
  • Applications: Internet of Things & BI, Textual Documents Analytics, Social Media Analytics, Real-time analytics, Self-service BI, Smart cities & BI, Big Data Analytics in Healthcare, Social BI, Open Data, Digital Humanities...

Submission Procedure

Researchers and practitioners are invited to submit on or before April 30, 2017 a chapter proposal of 1,000 to 2,000 words clearly explaining the mission and concerns of his or her proposed chapter. Authors will be notified by May 1st, 2017 about the status of their proposals and sent chapter guidelines. Full chapters of about 10,000 words are expected to be submitted by June 30, 2017, and all interested authors must consult the guidelines for manuscript submissions prior to submission. All submitted chapters will be reviewed on a double-blind review basis. Contributors may also be requested to serve as reviewers for this project.

Note: There are no submission or acceptance fees for manuscripts submitted to this book publication, Utilizing Big Data Paradigms for Business Intelligence. All manuscripts are accepted based on a double-blind peer review editorial process.

All proposals should be submitted through the E-Editorial Discovery™ online submission manager.


This book is scheduled to be published by IGI Global (formerly Idea Group Inc.), publisher of the "Information Science Reference" (formerly Idea Group Reference), "Medical Information Science Reference," "Business Science Reference," and "Engineering Science Reference" imprints. For additional information regarding the publisher, please visit This publication is anticipated to be released in 2018.

Important Dates

  • April 30, 2017: Proposal Submission 3rd Deadline
  • May 1, 2017: Notification of Proposal Acceptance
  • June 30, 2017: Full Chapter Submission
  • October 30, 2017 November 15, 2017: Review Results Returned
  • November 30, 2017 December 15, 2017: Revised Chapter Submission
  • December 15, 2017 January 8, 2018: Final Acceptance Notification
  • December 30, 2017 January 15, 2018: Final Chapter Submission
  • February 6, 2018: Second Call for Chapters
  • March 9, 2018: 2nd call Full Chapter Submission
  • March 15, 2018: Book in queue to be copy edited
  • April 19, 2018: Proofreading complete
  • July 31, 2018: Book published!

Scientific committee

  • Alberto Abello, Universitat Politècnica de Catalunya, Barcelona, Spain
  • Antonio Badia, University of Louisville, USA
  • Fatma Boualli, Université Lille 2, France
  • Stéphane Bressan, National University of Singapore, Singapore
  • Arnaud Castelltort, Université de Montpellier, France
  • Karen Davis, Miami University, Oxford, USA
  • John W. Emerson, Yale University, USA
  • Pedro Furtado, Universidade de Coimbra, Portugal
  • Amine Ghrab, Université Libre de Bruxelles, Belgium
  • Anastasios Gounaris, Aristotle University of Thessaloniki, Greece
  • Le Gruenwald, University of Oklahoma, USA
  • Zhen He, La Trobe University, Australia
  • Chang-Shing Lee, National University of Tainan, Taiwan
  • Daniel Lemire, Université du Québec, Montréal, Canada
  • Patrick Marcel, Université de Tours, France
  • Morten Middelfart, Lumina Analytics, USA
  • Richi Nayak, Queensland University of Technology, Australia
  • Franck Ravat, Université de Toulouse, France
  • Alkis Simitsis, HP Labs, USA
  • Won-Kyung Sung, KISTI, South Korea
  • Thomas Tamisier, Luxembourg Institute of Science and Technology, Luxembourg
  • Christian Thomsen, Aalborg University, Denmark
  • Panos Vassiliadis, University of Ioannina, Greece
  • Robert Wrembel, Poznan University of Technology, Poland
  • Roberto Zicari, Frankfurt University, Germany
  • Iryna Zolotaryova, Kharkiv National University of Economics, Ukraine

For any Inquiry, please contact us.

Format Guildelines

  • Chapter length: about 10,000 words / about 12,000 words for final version
  • Chapter format guidelines at IGI Global
  • Chapter submission site
  • Submissions will undergo a double-blind reviewing process. Please dot not include in your manuscript any author name, affiliation, self-reference, project name or other information that could help indentify you.


Submission and Review Statistics
Chapter Proposals Accepted Proposals Chapter Submissions Average Number of Reviews per Chapter Accepted Chapters (after revision)
19 18 15 2.87 8

Origin of Chapter Proposals

Table of Contents


Torben Bach Pedersen, Aalborg University, Denmark
David Taniar, Monash University, Australia


Jérôme Darmont, Université de Lyon, France
Sabine Loudcher, Université de Lyon, France


Chapter 1: Applications of Artificial Intelligence in the Realm of Business Intelligence

Prakhar Mehrotra, Uber Technologies, USA

Chapter 2: A Big Data Platform for Enhancing Life Imaging Activities

Leila Abidi, Université Sorbonne Paris Cité, France
Hanene Azzag, Université Sorbonne Paris Cité, France
Salima Benbernou, Université Sorbonne Paris Cité, France
Mehdi Bentounsi, Université Sorbonne Paris Cité, France
Christophe Cérin, Université Sorbonne Paris Cité, France
Tarn Duong, Université Sorbonne Paris Cité, France
Philippe Garteiser, Inserm U1149 and Université Sorbonne Paris Cité, France
Mustapha Lebbah, Université Paris 13, France
Mourad Ouziri, Université Sorbonne Paris Cité, France
Soror Sahri, Université Sorbonne Paris Cité, France
Michel Smadja, SISNCOM, France

Chapter 3: A Survey of Parallel Indexing Techniques for Large-Scale Moving Object Databases

Eleazar Leal, University of Minnesota Duluth, USA
Le Gruenwald, University of Oklahoma, USA
Jianting Zhang, City College of New York, USA

Chapter 4: Privacy and Security in Data-Driven Urban Mobility

Rajendra Akerkar, Western Norway Research Institute, Norway

Chapter 5: C-Idea - A Fast Algorithm for Computing Emerging Closed Datacubes

Mickaël Martin-Nevot, Aix-Marseille Université, France
Sébastien Nedjar, LIF, Aix-Marseille Université, France
Lotfi Lakhal, LIF, Aix-Marseille Université, France
Rosine Cicchetti, LIF, Aix-Marseille Université, France

Chapter 6: Large Multivariate Time Series Forecasting - Survey on Methods and Scalability

Youssef Hmamouche, LIS, Aix-Marseille Université, France
Piotr Marian Przymus, LIF, Aix-Marseille Université, France
Hana Alouaoui, LIF, Aix-Marseille Université, France
Alain Casali, LIF, Aix-Marseille Université, France
Lotfi Lakhal, LIF, Aix-Marseille Université, France

Chapter 7: Exploring Multiple, Dynamic Social Networks in Computer-Mediated Communications: An Experimentally Validated Ecosystem

Isaac Osesina, Aware Inc., USA
Eduard Tudoreanu, University of Arkansas at Little Rock, USA
John P. McIntire, USAF AFRL, USA
Paul R. Havig, USAF AFRL, USA
Eric E. Geiselman, AFRL 711HPW/RHCV, USA

Chapter 8: Analysis of Operation Performance of Blast Furnace with Machine Learning Methods

Kuo-Wei Hsu, National Chengchi University, Taiwan
Yung-Chang Ko, China Steel Corporation, Taiwan

Compilation of References

About the Contributors


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