Piloting Data Science Learning Platforms through the Development of Cloud-based interactive Digital Computational Notebooks

the delivery, distance learning, document collaboration increasingly introduces a novel method to allow students and faculty in the Humanities, Arts, and Social Sciences (HASS) to collaborate and interact through data analytical technologies using "interactive Digital Computational Notebooks" (iDCNs). We demonstrate this approach using a digitized Legacy of Slavery (LoS) archival dataset collection from the Maryland State Archives (MSA) and illustrate the socio-technical challenges in establishing this learning environment. We provide a step-by-step process involved in accessing, developing, and integrating different infrastructure elements. The program and vast Maryland’s American population. 420,000 data into this paper’s to enable the digital representation of these culturally rich and sensitive collections to be and studied contemporary scholars’ This project to achieve this goal by making these databases available and accessible so that individual glean insights, and possibly recover “erased” memories of people. To as a first step, unique dataset by downloading the put through rigorous exploration, cleaning, and visualization archivists, computer technology the importance of a multidisciplinary approach to a unique set of digitized archival data with a specific focus on contextual aspects due to the data’s historical value and sensitivity. The collaborative process used open-source and readily accessible tools to create meaningful visualizations as an arrange-ment that flows together conducive for educators to teach. The visualizations use the spatial and temporal characteristics of the datasets to produce graphs and charts for a graphical view of the datasets. The visualizations constructed are responsive to present the data by instant connections to the datasets dynamically. The integration of these digital artifacts obtained from each dataset was carried out through Jupyter Notebooks (JNs). These iDCNs are unlike the traditional digital notebooks that provide a space for students to take notes and collect clippings of text. Instead, the iDCNs developed in this project are a novel set of educational tools that allow text and software code to co-exist and be rendered in a single document coherently for instructors and students to follow the text with visual representations back-to-back. The iDCNs are also equipped with live examples of basic natural language processing on certain text-rich features of these dataset collections. The open-source nature of this project’s setup and cloud-based distribution of these digital artifacts pave the way for students from under served communities to take advantage of a unique way of learning and to perform hands-on work on marketable software tools, preparing them for a successful career. The contributions of this paper to the fields of HASS and other non-STEM (Science, Technology, Engineering, and Mathematics) backgrounds lie in the idea of providing an “always-on” cloud-based pedagogical environment for aspiring students and researchers worldwide to analyze, learn and unearth stories through data science driven approach on a cultural dataset, in our case, the LoS dataset collection.