Fingerprint Fingerprint is based on mining the text of the persons scientific documents to create an index of weighted terms, which defines the key subjects of each individual researcher.

  • 26 Similar Profiles
Industry Engineering & Materials Science
Students Engineering & Materials Science
Big data Engineering & Materials Science
program Social Sciences
internship Social Sciences
student Social Sciences
multinational corporation Social Sciences
Visualization Engineering & Materials Science

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Projects 2016 2020

Research Output 1984 2017

  • 64 Citations
  • 4 h-Index from Scopus
  • 7 Conference contribution
  • 5 Article
  • 2 Chapter

A framework for describing big data projects

Saltz, J., Shamshurin, I. & Connors, C. Jan 1 2017 Lecture Notes in Business Information Processing. Springer Verlag, Vol. 263, p. 183-195 13 p. (Lecture Notes in Business Information Processing; vol. 263)

Research output: Chapter in Book/Report/Conference proceedingChapter

Big data
Methodology
Team work
Likely
Attribute

An initial view of a process model for data-driven product concept development

Li, Y., Roy, U. & Saltz, J. S. Mar 1 2017 In : C e Ca. 42, 3, p. 982-987 6 p.

Research output: Contribution to journalArticle

Anthralin
Acyclic Acids
Dust
Learning systems
Squamous Cell Carcinoma
1 Citations

Big data team process methodologies: A literature review and the identification of key factors for a project's success

Saltz, J. S. & Shamshurin, I. Feb 2 2017 Proceedings - 2016 IEEE International Conference on Big Data, Big Data 2016. Institute of Electrical and Electronics Engineers Inc., p. 2872-2879 8 p. 7840936

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Big data

Not all software engineers can become good data engineers

Saltz, J. S., Yilmazel, S. & Yilmazel, O. Feb 2 2017 Proceedings - 2016 IEEE International Conference on Big Data, Big Data 2016. Institute of Electrical and Electronics Engineers Inc., p. 2896-2901 6 p. 7840939

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Engineers
Big data
Industry

Blended learning at the boundary: Designing a new internship

Heckman, R., Østerlund, C. S. & Saltz, J. Jun 1 2015 In : Journal of Asynchronous Learning Network. 19, 3

Research output: Contribution to journalArticle

Blended Learning
internship
Students
Industry
learning

Press / Media