Title: Developing the Chinese Academic Map Publishing Platform
The discipline of the humanities has long been inseparable from the exploration of space and time. With the rapid advancement of digitization, databases, and data science, humanities research is making greater use of quantitative spatiotemporal analysis and visualization. In response to this trend, our team developed the Chinese academic map publishing platform (AMAP) with the aim of supporting the digital humanities from a Chinese perspective. In compiling materials mined from China’s historical records, AMAP attempts to reconstruct the geographical distribution of entities including people, activities, and events, using places to connect these historical objects through time. This project marks the beginning of the development of a comprehensive database and visualization system to support humanities scholarship in China, and aims to facilitate the accumulation of spatiotemporal datasets, support multi-faceted queries, and provide integrated visualization tools. The software itself is built on Harvard’s WorldMap codebase, with enhancements which include improved support for Asian projections, support for Chinese encodings, the ability to handle long text attributes, feature level search, and mobile application support. The goal of AMAP is to make Chinese historical data more accessible, while cultivating collaborative opensource software development. more »« less
Craig, Kalani; Danish, Joshua; Humburg, Megan; Szostalo, Maksymilian; McCranie, Ann; Hmelo-Silver, Cindy(
, The Interdisciplinarity of the Learning Sciences, 14th International Conference of the Learning Sciences (ICLS) 2020)
Gresalfi, M. and
(Ed.)
History educators in large-lecture humanities undergraduate classrooms struggle to support reading comprehension, defined as the ability to simultaneously read a complex text critically, understand the text’s details and context, and vet the text’s claims. Critical reading of historical texts in particular helps bridge the gap between seeing history as memorization-oriented and seeing it as an inquiry-oriented discipline that reconstructs narrative and context. Net.Create is an open-source, network-analysis software tool paired with activities that support intuitive creation and revision of a network data set and accompanying visualization, and through these representational practices, reading comprehension in humanities classrooms. Findings show that as students draw on details in a historical text to collaboratively construct a larger network, they begin to emphasize context reconstruction over memorization.
Zhou, Jun; Smith, Karen; Wilsbacher, Greg; Sagona, Paul; Reddy, David; Torkian, Ben(
, PEARC '20: Practice and Experience in Advanced Research Computing)
Building science gateways for humanities content poses new challenges to the science gateway community. Compared with science gateways devoted to scientific content, humanities-related projects usually require 1) processing data in various formats, such as text, image, video, etc., 2) constant public access from a broad audience, and therefore 3) reliable security, ideally with low maintenance. Many traditional science gateways are monolithic in design, which makes them easier to write, but they can be computationally inefficient when integrated with numerous scientific packages for data capture and pipeline processing. Since these packages tend to be single-threaded or nonmodular, they can create traffic bottlenecks when processing large numbers of requests. Moreover, these science gateways are usually challenging to resume development on due to long gaps between funding periods and the aging of the integrated scientific packages. In this paper, we study the problem of building science gateways for humanities projects by developing a service-based architecture, and present two such science gateways: the Moving Image Research Collections (MIRC) – a science gateway focusing on image analysis for digital surrogates of historical motion picture film, and SnowVision - a science gateway for studying pottery fragments in southeastern North America. For each science gateway, we present an overview of the background of the projects, and some unique challenges in their design and implementation. These two science gateways are deployed on XSEDE’s Jetstream academic clouding computing resource and are accessed through web interfaces. Apache Airavata middleware is used to manage the interactions between the web interface and the deep-learning-based (DL) backend service running on the Bridges graphics processing unit (GPU) cluster.
Abstract With the efflorescence of palaeoscientific approaches to the past, historians have been confronted with a wealth of new evidence on both human and natural phenomena, from human disease and migration through to landscape change and climate. These new data require a rewriting of our narratives of the past, questioning what constitutes an authoritative historical source and who is entitled to recount history to contemporary societies. Humanities-based historical inquiry must embrace this new evidence, but to do so historians need to engage with it in a critical manner, just as they engage critically with textual and material sources. This article highlights the most vital methodological issues, ranging from the spatiotemporal scales and heterogeneity of the new evidence to the new roles attributed to quantitative methods and the place of scientific data in narrative construction. It considers areas of study where the palaeosciences have “intruded” into fields and subjects previously reserved for historians, especially socioeconomic, climate, and environmental history. The authors argue that active engagement with new approaches is urgently needed if historians want to contribute to our evolving understanding of the challenges of the Anthropocene.
Understanding the space-time dynamics of human activities is essential in studying human security issues such as climate change impacts, pandemic spreading, or urban sustainability. Geotagged social media posts provide an open and space-time continuous data source with user locations which is convenient for studying human movement. However, the reliability of Chinese geotagged social media data for representing human mobility remains unclear. This study compares human movement data derived from the posts of Sina Weibo, one of the largest social media software in China, and that of Baidu Qianxi, a high-resolution human movement dataset from ‘Baidu Map’, a popular location-based service in China with 1.3 billion users. Correlation analysis was conducted from multiple dimensions of time periods (weekly and monthly), geographic scales (cities and provinces), and flow directions (inflow and outflow), and a case study on COVID-19 transmission was further explored with such data. The result shows that Sina Weibo data can reveal similar patterns as that of Baidu Qianxi, and that the correlation is higher at the provincial level than at the city level and higher at the monthly scale than at the weekly scale. The study also revealed spatial variations in the degree of similarity between the two sources. Findings from this study reveal the values and properties and spatiotemporal heterogeneity of human mobility data extracted from Weibo tweets, providing a reference for the proper use of social media posts as the data sources for human mobility studies.
Cleveland, Sean B; Geis, Jennifel Jacobs(
, Practice and Experience in Advanced Research Computing)
. Granting agencies invest millions of dollars on the generation and analysis of data, making these products extremely valuable. However, without sufficient annotation of the methods used to collect and analyze the data, the ability to reproduce and reuse those products suffers. This lack of assurance of the quality and credibility of the data at the different stages in the research process essentially wastes much of the investment of time and funding and fails to drive research forward to the level of potential possible if everything was effectively annotated and disseminated to the wider research community. In order to address this issue for the Hawai'i Established Program to Stimulate Competitive Research (EPSCoR) project, a water science gateway was developed at the University of Hawai‘i (UH), called the ‘Ike Wai Gateway. In Hawaiian, ‘Ike means knowledge and Wai means water. The gateway supports research in hydrology and water management by providing tools to address questions of water sustainability in Hawai‘i. The gateway provides a framework for data acquisition, analysis, model integration, and display of data products. The gateway is intended to complement and integrate with the capabilities of the Consortium of Universities for the Advancement of Hydrologic Science's (CUAHSI) Hydroshare by providing sound data and metadata management capabilities for multi-domain field observations, analytical lab actions, and modeling outputs. Functionality provided by the gateway is supported by a subset of the CUAHSI’s Observations Data Model (ODM) delivered as centralized web based user interfaces and APIs supporting multi-domain data management, computation, analysis, and visualization tools to support reproducible science, modeling, data discovery, and decision support for the Hawai'i EPSCoR ‘Ike Wai research team and wider Hawai‘i hydrology community. By leveraging the Tapis platform, UH has constructed a gateway that ties data and advanced computing resources together to support diverse research domains including microbiology, geochemistry, geophysics, economics, and humanities, coupled with computational and modeling workflows delivered in a user friendly web interface with workflows for effectively annotating the project data and products. Disseminating results for the ‘Ike Wai project through the ‘Ike Wai data gateway and Hydroshare makes the research products accessible and reusable.
Xu, Yongming, Lewis, Benjamin, and Guan, Weihe Wendy. Developing the Chinese Academic Map Publishing Platform. Retrieved from https://par.nsf.gov/biblio/10136053. ISPRS International Journal of Geo-Information 8.12 Web. doi:10.3390/ijgi8120567.
@article{osti_10136053,
place = {Country unknown/Code not available},
title = {Developing the Chinese Academic Map Publishing Platform},
url = {https://par.nsf.gov/biblio/10136053},
DOI = {10.3390/ijgi8120567},
abstractNote = {The discipline of the humanities has long been inseparable from the exploration of space and time. With the rapid advancement of digitization, databases, and data science, humanities research is making greater use of quantitative spatiotemporal analysis and visualization. In response to this trend, our team developed the Chinese academic map publishing platform (AMAP) with the aim of supporting the digital humanities from a Chinese perspective. In compiling materials mined from China’s historical records, AMAP attempts to reconstruct the geographical distribution of entities including people, activities, and events, using places to connect these historical objects through time. This project marks the beginning of the development of a comprehensive database and visualization system to support humanities scholarship in China, and aims to facilitate the accumulation of spatiotemporal datasets, support multi-faceted queries, and provide integrated visualization tools. The software itself is built on Harvard’s WorldMap codebase, with enhancements which include improved support for Asian projections, support for Chinese encodings, the ability to handle long text attributes, feature level search, and mobile application support. The goal of AMAP is to make Chinese historical data more accessible, while cultivating collaborative opensource software development.},
journal = {ISPRS International Journal of Geo-Information},
volume = {8},
number = {12},
author = {Xu, Yongming and Lewis, Benjamin and Guan, Weihe Wendy},
}
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