Data science is a relatively new field that aims at extracting insights from data, to build decision support systems for companies and organizations. Although data science has been successful in many fields, including health, business, social network analysis, and many other sectors, the awareness of data science as a standalone field within the Digital Humanities (DH) community is still relatively low. This does not mean that data science techniques, such as text and visual analytics, are not used in DH, but that there is not full awareness of the entire life cycle of a data science project, with a focus on its final goal, which is extracting insights from data to build better decision support systems. Using all the power of data science in DHs requires that organizations working in DH be proactive in reaching out to potential partners and collaborators who can help them make use of data science. This paper describes how to adapt a data science project life cycle to DH, as well as the challenges and perspectives to raising awareness about data science among organizations, researchers, and practitioners of DH.
Challenges and Perspectives of Data Science for Digital Humanities
A Lo Duca
2023
Abstract
Data science is a relatively new field that aims at extracting insights from data, to build decision support systems for companies and organizations. Although data science has been successful in many fields, including health, business, social network analysis, and many other sectors, the awareness of data science as a standalone field within the Digital Humanities (DH) community is still relatively low. This does not mean that data science techniques, such as text and visual analytics, are not used in DH, but that there is not full awareness of the entire life cycle of a data science project, with a focus on its final goal, which is extracting insights from data to build better decision support systems. Using all the power of data science in DHs requires that organizations working in DH be proactive in reaching out to potential partners and collaborators who can help them make use of data science. This paper describes how to adapt a data science project life cycle to DH, as well as the challenges and perspectives to raising awareness about data science among organizations, researchers, and practitioners of DH.File | Dimensione | Formato | |
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