Data-driven engineering design research: Opportunities using open data

Engineering Design research relies on quantitative and qualitative data to describe design-related phenomena and prescribe improvements for design practice. Given data availability, privacy requirements and other constraints, most empirical data used in Engineering Design research can be described as “closed”. Keeping such data closed is in many cases necessary and justifiable. However, this closedness also hinders replicability, and thus, may limit our possibilities to test the validity and reliability of research results in the field. This paper discusses implications and applications of using the already available and continuously growing body of open data sources to create opportunities for research in Engineering Design. Insights are illustrated by an examination of two examples: a study of open source software repositories and an analysis of open business registries in the cleantech industry. We conclude with a discussion about the limitations, challenges and risks of using open data in Engineering Design research and practice.

[1]  Conrad S. Tucker,et al.  Automated Discovery of Lead Users and Latent Product Features by Mining Large Scale Social Media Networks , 2015 .

[2]  Tony Hey,et al.  The Fourth Paradigm: Data-Intensive Scientific Discovery , 2009 .

[3]  Yongtae Park,et al.  Development of a service evolution map for service design through application of text mining to service documents , 2017 .

[4]  Petra Badke-Schaub,et al.  ONLINE WAYS OF SHAREDNESS: A SYNTACTIC ANALYSIS OF DESIGN COLLABORATION IN OPENIDEO , 2015 .

[5]  César A. Hidalgo,et al.  The Product Space Conditions the Development of Nations , 2007, Science.

[6]  Christopher L. Tucci,et al.  Interfirm Modularity and Its Implications for Product Development , 2005 .

[7]  Jianxi Luo,et al.  Technology-Based Design and Sustainable Economic Growth , 2012 .

[8]  Randy Holden,et al.  Data-driven innovation : big data for growth and well-being , 2015 .

[9]  Tom Fawcett,et al.  Data science for business , 2013 .

[10]  W. Seering,et al.  Beyond Cost: Product Complexity and the Global Product Development Location Advantage , 2009 .

[11]  Rajiv Vaid Basaiawmoit,et al.  DESIGN THINKING AND THE HYPE CYCLE IN MANAGEMENT EDUCATION AND IN ENGINEERING EDUCATION , 2016 .

[12]  Pedro Parraguez Ruiz,et al.  Network Insights for Partner Selection in Inter-Organisational New Product Development Projects , 2016 .

[13]  Anja Maier,et al.  Mapping industrial networks as an approach to identify inter-organisational collaborative potential in new product development , 2012 .

[14]  Nate Silver,et al.  The signal and the noise : why so many predictions fail but some don't , 2012 .

[15]  Jitesh H. Panchal,et al.  Analysis of the interdependent co-evolution of product structures and community structures using dependency modelling techniques , 2012 .

[16]  Thomas Stone,et al.  Consumer preference estimation from Twitter classification: Validation and uncertainty analysis , 2013 .

[17]  B. Song,et al.  OVERLAY PATENT NETWORK FOR ANALYZING DESIGN SPACE EVOLUTION: THE CASE OF HYBRID ELECTRICAL VEHICLES , 2016 .

[18]  Sascha Friesike,et al.  Opening Science: The Evolving Guide on How the Internet is Changing Research, Collaboration and Scholarly Publishing , 2016 .

[19]  Alan MacCormack,et al.  Exploring the Structure of Complex Software Designs: An Empirical Study of Open Source and Proprietary Code , 2006, Manag. Sci..

[20]  Conrad S. Tucker,et al.  An automated approach to quantifying functional interactions by mining large-scale product specification data , 2016 .

[21]  Brian A. Nosek,et al.  Promoting an open research culture , 2015, Science.

[22]  Conrad S. Tucker,et al.  Predicting emerging product design trend by mining publicly available customer review data , 2011 .

[23]  Steven D. Eppinger,et al.  Comparing product development processes and managing risk , 2009 .

[24]  Ali Mostashari,et al.  Visualisation of the organisation knowledge structure evolution , 2013, J. Knowl. Manag..

[25]  Wei Chen,et al.  Modeling customer preferences using multidimensional network analysis in engineering design , 2016, Design Science.

[26]  Emilie Poirson,et al.  SENTIMENT RATING ALGORITHM OF PRODUCT ONLINE REVIEWS , 2014 .

[27]  Luca Simeone,et al.  Data challenges and opportunities in designing for service , 2018 .

[28]  Anja Maier,et al.  Towards describing co-design by the integration of Engineering Design and Technology and Innovation Management literature , 2012 .

[29]  Kah-Hin Chai,et al.  Understanding design research: A bibliometric analysis of Design Studies (1996–2010) , 2012 .

[30]  Steven L. Goldman.  Reinventing Discovery: The New Era of Networked Science , 2014 .

[31]  Joost Duflou,et al.  SYSTEMATIC ONLINE LEAD USER IDENTIFICATION - CASE STUDY FOR ELECTRICAL INSTALLATIONS , 2015 .

[32]  Zhihua Wang,et al.  Using web crawler technology to support design-related web information collection in idea generation , 2013 .

[33]  Albert Albers,et al.  COMBINING PROCESS MODEL AND SEMANTIC WIKI , 2010 .

[34]  Tanja Aitamurto,et al.  Three layers of openness in design: Examining the open paradigm in design research , 2013 .

[35]  Yue Maggie Zhou,et al.  Designing for Complexity: Using Divisions and Hierarchy to Manage Complex Tasks , 2012, Organ. Sci..

[36]  Antonello Cammarano,et al.  Measuring Open Innovation in the Bio‐Pharmaceutical Industry , 2015 .

[37]  H. Pampel,et al.  Open Research Data: From Vision to Practice , 2014 .

[38]  Monica Chiarini Tremblay,et al.  Advancing the Impact of Design Science: Moving from Theory to Practice , 2014, Lecture Notes in Computer Science.

[39]  K. Fichter.  Innovation Communities: The Role of Networks of Promotors in Open Innovation , 2009 .

[40]  Maria C. Yang,et al.  Evaluating Wikis as a Communicative Medium for Collaboration Within Colocated and Distributed Engineering Design Teams , 2011 .

[41]  P. John Clarkson,et al.  A Holistic Categorization Framework for Literature on Engineering Change Management , 2013, Syst. Eng..

[42]  Lucienne Blessing,et al.  DRM, a Design Research Methodology , 2009 .