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ORCIDJeffrey S. Saltz
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- affiliation: Syracuse University, School of Information Studies, NY, USA
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2020 – today
- 2024
[c58]Jeffrey V. Nickerson, Aron Lindberg, Stefan Seidel, Jeffrey S. Saltz:
Introduction to the Minitrack on AI, Organizing, and Management. HICSS 2024: 5784-5785- [c57]Sucheta Lahiri, Jeffrey S. Saltz:
AI Project and Deployment Risk: Articulation and Legitimization. HICSS 2024: 5836-5845 - [c56]Jeffrey S. Saltz, Viktoria Stray, Edward Anderson, Alex Sutherland:
Introduction to the Minitrack on Agile and Lean: Organizations, Products and Development. HICSS 2024: 7236-7238 - 2023
- [j12]Yin Zhang
, Dan Wu, Loni Hagen, Il-Yeol Song, Javed Mostafa, Sam Gyun Oh, Theresa D. Anderson, Chirag Shah, Bradley Wade Bishop, Frank Hopfgartner, Kai Eckert, Lisa Federer, Jeffrey S. Saltz:
Data science curriculum in the iField. J. Assoc. Inf. Sci. Technol. 74(6): 641-662 (2023) - [c55]Akit Kumar, M. S. Lakshmi Devi, Jeffrey S. Saltz:
Bridging the Gap in AI-Driven Workflows: The Case for Domain-Specific Generative Bots. IEEE Big Data 2023: 2421-2430 - [c54]Sucheta Lahiri, Jeffrey S. Saltz:
Data Science Failure: A Literature Review. IEEE Big Data 2023: 2431-2440 - [c53]Jeffrey Nickerson, Jeffrey S. Saltz, Stefan Seidel, Aron Lindberg:
Introduction to the Minitrack on AI, Organizing, and Management. HICSS 2023: 5241 - [c52]Jeffrey S. Saltz, Edward Anderson, Alex Sutherland:
Introduction to the Minitrack on Agile and Lean: Organizations, Products and Development. HICSS 2023: 6484-6485 - [c51]Sucheta Lahiri, Jeffrey S. Saltz:
Evaluating Data Science Project Agility by Exploring Process Frameworks Used by Data Science Teams. HICSS 2023: 6538-6547 - 2022
- [j11]Jeffrey S. Saltz, Iva Krasteva:
Current approaches for executing big data science projects - a systematic literature review. PeerJ Comput. Sci. 8: e862 (2022) - [c50]Jeffrey S. Saltz:
Nine Questions to Evaluate a Data Science Team's Process: Exploring a Big Data Science Team Process Evaluation Framework Via a Delphi Study. IEEE Big Data 2022: 2667-2672 - [c49]Jasmina Tacheva, Sucheta Lahiri, Jeffrey S. Saltz:
Analyzing a Data Science Online Practitioner Community: Trends and Implications for Data Science Project Management. IEEE Big Data 2022: 2673-2681 - [c48]Sucheta Lahiri, Jeffrey S. Saltz:
The Risk Management Process for Data Science: Gaps in Current Practices. HICSS 2022: 1-10 - [c47]Jeffrey S. Saltz, Alex Sutherland, Edward Anderson:
Introduction to the Minitrack on Agile and Lean: Organizations, Products and Development. HICSS 2022: 1-2 - [c46]Jeffrey S. Saltz, Alex Sutherland, Nicholas Hotz:
Achieving Lean Data Science Agility Via Data Driven Scrum. HICSS 2022: 1-10 - [c45]Stefan Seidel, Jeffrey V. Nickerson, Jeffrey S. Saltz, Aron Lindberg:
Introduction to the Minitrack on AI, Organizing, and Management. HICSS 2022: 1-2 - 2021
- [j10]Kevin Crowston, Jeffrey S. Saltz, Niraj Sitaula, Yatish Hegde:
Evaluating MIDST, A System to Support Stigmergic Team Coordination. Proc. ACM Hum. Comput. Interact. 5(CSCW1): 36:1-36:24 (2021) - [c44]Jeffrey S. Saltz:
CRISP-DM for Data Science: Strengths, Weaknesses and Potential Next Steps. IEEE BigData 2021: 2337-2344 - [c43]Jeffrey S. Saltz, Alex Sutherland, Thibaut Jombart:
Identifying and Addressing 6 Key Questions when Using Data Driven Scrum. IEEE BigData 2021: 2345-2352 - [c42]Jeffrey S. Saltz, Edward Anderson, Alex Sutherland:
Introduction to the Minitrack on Agile and Lean: Organizations, Products and Development. HICSS 2021: 1-2 - [c41]Jeff Saltz, Nicholas Hotz:
Factors that Influence the Selection of a Data Science Process Management Methodology: An Exploratory Study. HICSS 2021: 1-11 - [c40]Stefan Seidel, Aron Lindberg, Jeffrey S. Saltz, Jeffrey V. Nickerson:
Introduction to the Minitrack on AI, Organizing, and Management. HICSS 2021: 1-2 - 2020
- [j9]Jeff Saltz, Robert Heckman:
Exploring Which Agile Principles Students Internalize When Using a Kanban Process Methodology. J. Inf. Syst. Educ. 31(1): 51-60 (2020) - [c39]Jeffrey S. Saltz, Nicholas Hotz:
Identifying the most Common Frameworks Data Science Teams Use to Structure and Coordinate their Projects. IEEE BigData 2020: 2038-2042 - [c38]Jeffrey S. Saltz, Sucheta Lahiri:
The Need for an Enterprise Risk Management Framework for Big Data Science Projects. DATA 2020: 268-274 - [c37]Jeffrey S. Saltz, Alex Sutherland:
SKI: A New Agile Framework that Supports DevOps, Continuous Delivery, and Lean Hypothesis Testing. HICSS 2020: 1-10 - [c36]Jeffrey S. Saltz, Anna Sidorova, Michael Goul:
Introduction to the Minitrack on Artificial Intelligence and Big Data Analytics Management, Governance, and Compliance. HICSS 2020: 1-2 - [c35]Alex Sutherland, Jeffrey S. Saltz, Edward Anderson:
Introduction to the Minitrack on Agile and Lean: Organizations, Products and Development. HICSS 2020: 1-2 - [e2]Xintao Wu, Chris Jermaine, Li Xiong, Xiaohua Hu, Olivera Kotevska, Siyuan Lu, Weija Xu, Srinivas Aluru, Chengxiang Zhai, Eyhab Al-Masri, Zhiyuan Chen, Jeff Saltz:
2020 IEEE International Conference on Big Data (IEEE BigData 2020), Atlanta, GA, USA, December 10-13, 2020. IEEE 2020, ISBN 978-1-7281-6251-5 [contents]
2010 – 2019
- 2019
- [j8]Jeffrey S. Saltz, Neil I. Dewar:
Data science ethical considerations: a systematic literature review and proposed project framework. Ethics Inf. Technol. 21(3): 197-208 (2019) - [j7]Jeffrey S. Saltz, Michael Skirpan, Casey Fiesler, Micha Gorelick, Tom Yeh, Robert Heckman, Neil I. Dewar, Nathan Beard:
Integrating Ethics within Machine Learning Courses. ACM Trans. Comput. Educ. 19(4): 32:1-32:26 (2019) - [j6]Kevin Crowston, Jeffrey S. Saltz, Amira Rezgui, Yatish Hegde, Sangseok You:
Socio-technical Affordances for Stigmergic Coordination Implemented in MIDST, a Tool for Data-Science Teams. Proc. ACM Hum. Comput. Interact. 3(CSCW): 117:1-117:25 (2019) - [c34]Jeffrey S. Saltz:
Visualizing Kanban Work: Towards an Individual Contributor View. AMCIS 2019 - [c33]Jeffrey S. Saltz, Ivan Shamshurin:
Exploring the Use of a Kanban Coach for Student Teams. AMCIS 2019 - [c32]Jeffrey S. Saltz, Alex Sutherland:
SKI: An Agile Framework for Data Science. IEEE BigData 2019: 3468-3476 - [c31]Jeffrey S. Saltz, Ivan Shamshurin:
Achieving Agile Big Data Science: The Evolution of a Team's Agile Process Methodology. IEEE BigData 2019: 3477-3485 - [c30]Kevin Crowston, Jeffrey S. Saltz, Amira Rezgui, Yatish Hegde, Sangseok You:
MIDST: A System to Support Stigmergic Coordination in Data-Science Teams. CSCW Companion 2019: 5-8 - [c29]Jeff Saltz:
Ethics in Data Science Projects: current Practices and Perceptions. ECIS 2019 - [c28]Michael Goul, Zhongju Zhang, Jeffrey S. Saltz:
Introduction to the Minitrack on Big Data, Data Science and Analytics Management, Governance and Compliance. HICSS 2019: 1-2 - [c27]Jeffrey S. Saltz, Robert Heckman, Kevin Crowston, Sangseok You, Yatish Hegde:
Helping Data Science Students Develop Task Modularity. HICSS 2019: 1-10 - [c26]Jeff Saltz, Daniel E. Turk, Edward Anderson:
Introduction to the Minitrack on Agile and Lean: Organizations, Products and Development. HICSS 2019: 1-2 - [c25]Sangseok You, Kevin Crowston, Jeffrey S. Saltz, Yatish Hegde:
Coordination in OSS 2.0: ANT Approach. HICSS 2019: 1-10 - 2018
- [j5]Jeffrey S. Saltz, Frank Armour, Ramesh Sharda:
Data Science Roles and the Types of Data Science Programs. Commun. Assoc. Inf. Syst. 43: 33 (2018) - [j4]Jeffrey S. Saltz, Robert Heckman:
A Scalable Methodology to Guide Student Teams Executing Computing Projects. ACM Trans. Comput. Educ. 18(2): 9:1-9:19 (2018) - [c24]Jeffrey S. Saltz, Michael Goul, Frank Armour, Ramesh Sharda:
Key Management and Governance Challenges when Executing Data Science / Analytics Projects. AMCIS 2018 - [c23]Jeff Saltz, Nicholas Hotz, David J. Wild, Kyle Stirling:
Exploring Project Management Methodologies Used Within Data Science Teams. AMCIS 2018 - [c22]Ivan Shamshurin, Jeffrey S. Saltz:
Will Deep Learning Change How Teams Execute Big Data Projects? IEEE BigData 2018: 2813-2817 - [c21]Heng Zhang, Utpal Roy, Jeffrey S. Saltz:
Improving Data Science Projects by Enriching Analytical Models with Domain Knowledge. IEEE BigData 2018: 2828-2837 - [c20]Jeff Saltz:
Identifying the Key Drivers for Teams to Use a Data Science Process Methodology. ECIS 2018: 58 - [c19]Jeffrey S. Saltz:
A Framework to Explore Ethical Issues When Using Big Data Analytics on the Future Networked Internet of Things. FNSS 2018: 49-60 - [c18]John Tripp, Jeff Saltz, Dan Turk:
Introduction to the Minitrack on Agile and Lean: Organizations, Products and Development. HICSS 2018: 1-2 - [c17]John Tripp, Jeff Saltz, Dan Turk:
Thoughts on Current and Future Research on Agile and Lean: Ensuring Relevance and Rigor. HICSS 2018: 1-8 - [c16]Jeffrey S. Saltz, Neil I. Dewar, Robert Heckman:
Key Concepts for a Data Science Ethics Curriculum. SIGCSE 2018: 952-957 - [e1]Naoki Abe, Huan Liu, Calton Pu, Xiaohua Hu, Nesreen K. Ahmed, Mu Qiao, Yang Song, Donald Kossmann, Bing Liu, Kisung Lee, Jiliang Tang, Jingrui He, Jeffrey S. Saltz:
IEEE International Conference on Big Data (IEEE BigData 2018), Seattle, WA, USA, December 10-13, 2018. IEEE 2018, ISBN 978-1-5386-5035-6 [contents] - 2017
- [j3]Jeffrey S. Saltz, Ivan Shamshurin, Colin Connors:
Predicting data science sociotechnical execution challenges by categorizing data science projects. J. Assoc. Inf. Sci. Technol. 68(12): 2720-2728 (2017) - [c15]Jeffrey S. Saltz, Ivan Shamshurin:
Does pair programming work in a data science context? An initial case study. IEEE BigData 2017: 2348-2354 - [c14]Jeffrey S. Saltz, Nancy W. Grady:
The ambiguity of data science team roles and the need for a data science workforce framework. IEEE BigData 2017: 2355-2361 - [c13]Jeffrey S. Saltz:
Acceptance Factors for using a Big Data Capability and Maturity Model. ECIS 2017 - [c12]Jeffrey S. Saltz, Robert Heckman, Ivan Shamshurin:
Exploring How Different Project Management Methodologies Impact Data Science Students. ECIS 2017 - [c11]Jeffrey S. Saltz, Ivan Shamshurin, Kevin Crowston:
Comparing Data Science Project Management Methodologies via a Controlled Experiment. HICSS 2017: 1-10 - 2016
- [c10]Jeffrey S. Saltz, Ivan Shamshurin:
Big data team process methodologies: A literature review and the identification of key factors for a project's success. IEEE BigData 2016: 2872-2879 - [c9]Jeffrey S. Saltz, Sibel Yilmazel, Özgür Yilmazel:
Not all software engineers can become good data engineers. IEEE BigData 2016: 2896-2901 - [c8]Jeffrey S. Saltz, Ivan Shamshurin, Colin Connors:
A Framework for Describing Big Data Projects. BIS (Workshops) 2016: 183-195 - 2015
- [c7]Jeffrey S. Saltz:
The need for new processes, methodologies and tools to support big data teams and improve big data project effectiveness. IEEE BigData 2015: 2066-2071 - [c6]Jeffrey S. Saltz, Ivan Shamshurin:
Exploring the process of doing data science via an ethnographic study of a media advertising company. IEEE BigData 2015: 2098-2105 - 2013
- [j2]Jeff Saltz, Mark A. Serva, Robert Heckman:
The GET Immersion Experience: A New Model for Leveraging the Synergies between Industry and Academia. J. Inf. Syst. Educ. 24(2): 121-132 (2013) - 2012
- [c5]Jeffrey S. Saltz, Jae C. Oh:
An open co-op model for global enterprise technology education: integrating the internship and course work. SIGCSE 2012: 117-122
2000 – 2009
- 2007
- [j1]Jeffrey S. Saltz, Starr Roxanne Hiltz, Murray Turoff, Katia Passerini:
Increasing Participation in Distance Learning Courses. IEEE Internet Comput. 11(3): 36-44 (2007) - 2004
- [c4]Jeffrey S. Saltz, Starr Roxanne Hiltz, Murray Turoff, Katia Passerini:
Measuring Student Participation in a Web-based Environment: A Framework for Developing New Tools. AMCIS 2004: 379 - [c3]Jeffrey S. Saltz, Starr Roxanne Hiltz, Murray Turoff:
Student social graphs: visualizing a student's online social network. CSCW 2004: 596-599
1990 – 1999
- 1997
- [c2]Hikmet Senay, Jeffrey S. Saltz:
Dynamic visualization of hierarchical data. Human Vision and Electronic Imaging 1997: 451-459
1980 – 1989
- 1988
- [c1]William H. Clifford Jr., John I. McConnell, Jeffrey S. Saltz:
The Development of PHEX, a 3D Graphics Extension to X11. Eurographics 1988
Coauthor Index
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last updated on 2024-11-20 20:58 CET by the dblp team
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