Dataset for "The emergent structures within digital engineering work: what can we learn from dynamic DSMs of near-identical systems design projects?"
Design structure matrices (DSMs) support engineers in the management of dependencies across product and organisational architectures. This dataset contains the underlying data used to generate dynamic DSMs for the cross-project comparison of three near-identical systems design projects. The data is stored in an SQLite database and a Jupyter notebook is provided to demonstrate how to access the data.
Cite this dataset as:
              
  Gopsill, J.,
  Snider, C.,
  Hicks, B.,
2019.
Dataset for "The emergent structures within digital engineering work: what can we learn from dynamic DSMs of near-identical systems design projects?".
Bath: University of Bath Research Data Archive.
Available from: https://doi.org/10.15125/BATH-00621.
            
Export
Data
anon_cad_metadata.db
application/octet-stream (565kB)
Creative Commons: Attribution 4.0
SQLite3 database
Code
Data Description.ipynb
text/plain (3kB)
Software: MIT License
Jupyter notebook
Creators
James Gopsill
                  
                  
University of Bath
                
Christopher Snider
                  
                  
University of Bristol
                
Ben Hicks
                  
                  
University of Bristol
                
Contributors
University of Bath
                  
Rights Holder
                
Coverage
Temporal coverage:
From 2012 to 2019
Documentation
Technical details and requirements:
The data was collected using the FolderActivityLogger node.js package created by the authors, which can be accessed from the npm Registry.
Methodology link:
Gopsill, J., 2017. FolderActivityLogger. Version 0.1.1. npm Registry. Available from: https://www.npmjs.com/package/fal.
Documentation Files
README.md
text/plain (1kB)
Creative Commons: Attribution 4.0
Funders
Engineering and Physical Sciences Research Council
                  
https://doi.org/10.13039/501100000266
                
The Language of Collaborative Manufacturing
                  
EP/K014196/2
                
Engineering and Physical Sciences Research Council
                  
https://doi.org/10.13039/501100000266
                
RCUK Catapult Researchers in Residence (High Value Manufacturing NCC) - Valuing Digital Knowledge Assets within the High-Value Manufacturing Catapult
                  
EP/R513556/1
                
Engineering and Physical Sciences Research Council
                  
https://doi.org/10.13039/501100000266
                
Platform: Designing the Future: Resilient Trans-Disciplinary Design Engineers
                  
EP/R013179/1
                
Publication details
            
              Publication date: 9 December 2019
            
              
by: University of Bath
            
            
Version: 1
DOI: https://doi.org/10.15125/BATH-00621
URL for this record: https://researchdata.bath.ac.uk/621
Related papers and books
Gopsill, J. A., Snider, C., and Hicks, B. J., 2019. The emergent structures in digital engineering work: what can we learn from dynamic DSMs of near-identical systems design projects? Design Science, 5. Available from: https://doi.org/10.1017/dsj.2019.20.
Contact information
Please contact the Research Data Service in the first instance for all matters concerning this item.
Contact person: James Gopsill
Faculty of Engineering & Design
              
Mechanical Engineering
