Topics of interest | Submission guidelines | Important dates | Organizers | Supporters

Data Science for Business Information Systems

The exponential increase in the amount of data that is generated every day and an ever-growing interest in exploiting this data in an intelligent way leads to a situation in which companies need to use Big Data solutions in a smart way. It is no longer sufficient to focus solely on data storage and data analysis.

A more interdisciplinary approach allowing to extract a valuable knowledge from data is required for companies to make profits, be more competitive and survive in the even more dynamic and fast changing environment. Therefore, the concept of Data Science has emerged and gained attention of both scientists and business analysts.

Data Science is the profession of today and the future, as it seeks to provide meaningful information from processing, analysing and interpreting vast amounts of complex and heterogeneous data. It combines different fields of work, such as Mathematics, Statistics, Economics, and Information Systems and uses various scientific and practical methods, tools and systems. The key objective is to extract valuable information and infer knowledge from data that then may be used for multiple purposes, starting from decision making, through product development, up to trend analysis and forecasting. The extracted knowledge allows also a better understanding of actual phenomena and can be applied to improve business processes. Therefore, enterprises in different domains want to take benefit from Data Science that entails technological, industrial and economical advances of our entire society. Following this trend, also the focus of the BIS conference migrates towards Data Science.

The BIS 2019 conference will foster the multidisciplinary discussion about Data Science from both the scientific and practical sides, and its impact on current enterprises. Our goal is to inspire researchers to share theoretical and practical knowledge of the different aspects related to Data Science, and to help them transform their ideas into the innovations of tomorrow.

Topics of interest

Big Data and Data Science

  • data science for business systems and applications
  • business intelligence
  • linked (open) data
  • knowledge representation and reasoning
  • knowledge graphs
  • big data analytics
  • real-time big data analysis and streaming analytics / stream reasoning
  • standards, data models, and business models for big & smart data
  • corporate semantic web and semantic web applications
  • sentiment analysis, emotion mining
  • data integration from Web information sources
  • modelling and describing evolving data sources
  • information gathering for supporting knowledge-intensive enterprises

Artificial Intelligence

  • smart machines
  • artificial intelligence methods and tools
  • cognitive computing in business systems and applications
  • machine learning

ICT Project Management

  • tools and techniques
  • stakeholder and user management
  • effort, time, and cost estimation
  • resource management
  • risk management
  • quality management
  • global and virtual teams

Smart Infrastructures

  • cloud computing
  • fog and edge computing
  • security and privacy
  • (micro) services architectures
  • sensor systems
  • software-defined infrastructures
  • agent systems and collective intelligence
  • internet of things and cyber-physical systems
  • industry 4.0

Social Media and Web-based Business Information Systems

  • social CRM
  • social user experience
  • social media in business
  • social media and privacy
  • social media analytics
  • social network analytics
  • social computing
  • social sentimental analysis
  • communities and crowdsourcing
  • social semantic web and pragmatic web
  • web / social / distributed search
  • personalized search and recommendation
  • user interfaces and human computer interaction

Applications, Evaluations, and Experiences

  • smart cities
  • e-government
  • business related e-science
  • mobile applications
  • industry specific applications
  • future directions and interdisciplinary relations

Submission guidelines

  • BIS 2019 proceedings will be published as a volume in Lecture Notes in Business Information Processing (LNBIP) series by Springer Verlag
  • Information for LNBIP authors may be found at page
  • Submission system is available at EasyChair
  • Submission guidelines can be found at page

Important dates

  • Submission deadline for conference papers:  January 7, 2019
  • Notification of acceptance/rejection: March 8, 2019
  • Submission of final papers: March 22, 2019
  • The conference: June 26-28, 2019


  • University of Seville, Spain
  • Poznań University of Economics and Business, Department of Information Systems, Poland