An Open Data Repository for Engineering Design: Using Text Mining with Open Government Data

Engineering Design (ED) is a complex process in which the reuse of knowledge is crucial: applying the knowledge consolidated in previous design activities to future design activities means performing them in a better way. The relevance of data in ED is even more crucial in a business context in which Data Science (DS) is literally revolutionizing the way companies operate and therefore also the way data are analyzed. Despite having been recognized as crucial for ED processes, data still remain closed in the domain and accessible only to their owners due to several constraints related to the private and proprietary nature of the acquired data. An answer to these challenges could be found in Open Data, but at the state of the art an operational Engineering Design framework to embrace them is still far to be achieved by both academia and industry. Given these issues, the aim of this paper is to give evidence that Text Mining can help to make a complex open database more effective to be used for the ED process, taking U.S. Open Government Data (OGD) repository as a case study. Open access to methods and data used within this research is provided. The results of this study allow us to understand for which purposes it is possible to apply the datasets and to comprehend the expertise and the data science methods needed for processing different data for-mats. Moreover, this work opens relevant implications and challenges for researchers, practitioners and policy makers operating in ED and DS domains that could become opportunities for future research and industrial applications. (c) 2022 Elsevier B.V. All rights reserved.