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Python and Data Science
Python has become the most popular data science programming language in recent years
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Data Science Methodologies – A Benchmarking Study
There are several Data Science methodologies that entities and organizations have daily contact with however real-time decision support is seen as a...
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Towards Data Science Design Patterns
We propose data flow diagrams to model data science design patterns and demonstrate, using a number of explanatory patterns, how they can be used to...
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Computer science and non-computer science faculty members’ perception on teaching data science via an experiential learning platform
Artificial intelligence (AI) has been widely adopted in higher education. However, the current research on AI in higher education is limited lacking...
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Data Science 9th International Conference of Pioneering Computer Scientists, Engineers and Educators, ICPCSEE 2023, Harbin, China, September 22–24, 2023, Proceedings, Part I
This two-volume set (CCIS 1879 and 1880) constitutes the refereed proceedings of the 9th International Conference of Pioneering Computer Scientists,...
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Introduction to Data Science and Data Analytics
This initial chapter, “Introduction to Data Science and Data Analytics”, presents the main concepts related to the subject of the book. As happened...
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Data Science 9th International Conference of Pioneering Computer Scientists, Engineers and Educators, ICPCSEE 2023, Harbin, China, September 22–24, 2023, Proceedings, Part II
This two-volume set (CCIS 1879 and 1880) constitutes the refereed proceedings of the 9th International Conference of Pioneering Computer Scientists,...
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Assisted design of data science pipelines
When designing data science (DS) pipelines, end-users can get overwhelmed by the large and growing set of available data preprocessing and modeling...
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Data Science for Social Science and Digital Humanities Research
In this chapterDigital Humanities and in Chap. 20 , we focus on the third component of the MERge modelMERge...
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Data science pedagogical tools and practices: A systematic literature review
The development of data science curricula has gained attention in academia and industry. Yet, less is known about the pedagogical practices and tools...
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Theoretical and practical data science and analytics: challenges and solutions
Big data have become a core technology for providing innovative solutions in numerical applications and services in many fields. Embedded in these...
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Ethical and Legal Aspects of Data Science
This chapter discusses ethical and legal aspects of data science. There has been a phenomenal growth in the use of digital data with vast amounts of...
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Data Science and Its Tasks
As the name Data Science (DS) suggests, it is a scientific field concerned with data. However, this definition would encompass the whole of...
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Research Data Management in Simulation Science: Infrastructure, Tools, and Applications
Research Data Management (RDM) has gained significant traction in recent years, being essential to allowing research data to be, e.g., findable,...
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Data Science Teacher Preparation: The “Method for Teaching Data Science” Course
In this chapter, we focusTeacher preparation on the second component of the MERge modelMERge model, namely education. We present a detailed...
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Introduction to Data Science A Python Approach to Concepts, Techniques and Applications
This accessible and classroom-tested textbook/reference presents an introduction to the fundamentals of the interdisciplinary field of data science....
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Geo Engine: Workflow-driven Geospatial Portals for Data Science
Geo data portals play a key role in the distribution and exploitation of domain-specific geo data. While such portals are highly specialized, they...
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DAPS diagrams for defining Data Science projects
BackgroundModels for structuring big-data and data-analytics projects typically start with a definition of the project’s goals and the business value...
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Being Agile in a Data Science Project
Applying agile practices in data science requires adaptations. This paper describes challenges and lessons learned in two applied machine learning...
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Das Data-Science-Team
Von den drei Teams, die ein modernes Data Team ausmachen, beginnen wir mit den Data Scientists, weil sie die Ergebnisse liefern, die ihre...