Research

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Explore some of the research that has helped advance the field of data science as a team sport.

Title & Conference Year
Data science ethical considerations: a systematic literature review and proposed project framework Ethics and Information Technology 21 (3), 197-208 2019
Integrating ethics within machine learning courses ACM Transactions on Computing Education (TOCE) 19 (4), 1-26 2019
Towards an integrated process model for new product development with data-driven features (NPD3) Research in Engineering Design 30 (2), 271-289 2019
A predictive model to identify Kanban teams at risk Model Assisted Statistics and Applications 14 (4), 321-335 2019
Exploring pair programming beyond computer science: a case study in its use in data science/data engineering International Journal of Higher Education and Sustainability 2 (4), 265-278 2019
Ethics In Data Science Projects: Current Practices and Perceptions Proceedings of the 27th European Conference on Information Systems (ECIS) 2019
Visualizing Kanban Work: Towards an Individual Contributor View Proceedings of the 25th Americas Conference on Information Systems (AMCIS) 2019
Using a coach to improve team performance when the team uses a Kanban process methodology International Journal of Information Systems and Project Management 7 (2), 61-77 2019
Socio-technical Affordances for Stigmergic Coordination Implemented in MIDST, a Tool for Data-Science Teams Proc. ACM Hum.-Comput. Interactions 2019
Helping Data Science Students Develop Task Modularity. Proceedings of the 52nd Hawaii International Conference on System Sciences, 1-10 2019
Will Deep Learning Change How Teams Execute Big Data Projects? 2018 IEEE International Conference on Big Data (Big Data), 2813-2817 2018
Improving Data Science Projects by Enriching Analytical Models with Domain Knowledge 2018 IEEE International Conference on Big Data (Big Data), 2828-2837 2018
A Framework to Explore Ethical Issues When Using Big Data Analytics on the Future Networked Internet of Things International Conference on Future Network Systems and Security, 49-60 2018
Key concepts for a data science ethics curriculum Proceedings of the 49th ACM technical symposium on computer science … 2018
Thoughts on current and future research on agile and lean: ensuring relevance and rigor Proceedings of the 51st Hawaii International Conference on System Sciences 2018
Data Science Roles and the Types of Data Science Programs Communications of the Association for Information Systems 43 (1), 33 2018
Identifying the Key Drivers for Teams to Use a Data Science Process Methodology Proceedings of the 26th European Conference on Information Systems (ECIS), 58 2018
Exploring Project Management Methodologies Used Within Data Science Teams Proceedings of the 24th Americas Conference on Information Systems (AMCIS) 2018
Does pair programming work in a data science context? An initial case study 2017 IEEE International Conference on Big Data (Big Data), 2348-2354 2017
The ambiguity of data science team roles and the need for a data science workforce framework 2017 IEEE International Conference on Big Data (Big Data), 2355-2361 2017
Predicting data science sociotechnical execution challenges by categorizing data science projects Journal of the Association for Information Science and Technology 68 (12 … 2017
Modular design of data-driven analytics models in smart-product development ASME 2017 International Mechanical Engineering Congress and Exposition 2017
Exploring How Different Project Management Methodologies Impact Data Science Students Proceedings of the 25th European Conference on Information Systems (ECIS), 2939 2017
Acceptance Factors for Using a Big Data Capability and Maturity Model In Proceedings of the 25th European Conference on Information Systems (ECIS … 2017
Comparing data science project management methodologies via a controlled experiment Proceedings of the 50th Hawaii International Conference on System Sciences 2017
Big data team process methodologies: A literature review and the identification of key factors for a project’s success 2016 IEEE International Conference on Big Data (Big Data), 2872-2879 2016
Not all software engineers can become good data engineers 2016 IEEE International Conference on Big Data (Big Data), 2896-2901 2016
A framework for describing big data projects International Conference on Business Information Systems, 183-195 2016
Exploring the process of doing data science via an ethnographic study of a media advertising company 2015 IEEE International Conference on Big Data (Big Data), 2098-2105 2015
The need for new processes, methodologies and tools to support big data teams and improve big data project effectiveness 2015 IEEE International Conference on Big Data (Big Data), 2066-2071 2015