First, a particular deficiency of the system that needs to be addressed is the software’s inability to run on Linux or Macs. While popular, it has become clear that there are several areas in which the product needs to be improved.
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The desktop software has undergone a number of revisions and is currently built upon the Windows operating system. It is estimated that there are over one million users. The Epi-Info software is widely used by the epidemiologists and health professionals in the governments, public health non-profits, NGO’s, universities and health schools (for example, ). Specifically, the design allows for cross-platform form-design, data-collection, offline/online modes, scalable storage, automatic local-to-remote data sync, and fast analytics which rival more traditional approaches.ĭeveloped by the Centers for Disease Control and Prevention (CDC), Epi-Info is a software package which enables public health workers to assess disease outbreak, collect data, manage surveillance data sets, and analyze data. Promising results warrant future research. This has been accomplished by using Electron as a wrapper for an AngularJS app, a Python analytics module, and a local, browser-based NoSQL database. We have successfully generated executables for Linux, Mac, and Windows from a single code-base, and we have shown that performance need not be completely sacrificed when building a cross-platform application. In this paper, we present a viable cross-platform architecture for Epi-Info which solves many of these problems. Such understanding should allow for improved design, and thus result in substantial mitigation of reduced performance. Specifically, it is critical to fully understand any underlying negative performance issues which arise from platform-agnostic systems.
Thus, there is a blatant need for continued research. These include reduced development time, reduced cost, and simplified system architecture. Software portability has become increasingly important over the past few years as it offers a number of obvious benefits. As it exists today, Epi-Info Desktop runs only on the Windows platform, and the larger Epi-Info Suite of products consists of separate codebases for several different devices and use-cases. It will also offer a helping hand to the interested individual seeking to make sense of genealogical data or digitized newspapers, and even the local historical society who are trying to see the value in digitizing their holdings.The companion website to Exploring Big Historical Data can be found at http: //On this site you will find code, a discussion forum, essays, and datafiles that accompany this book.The Epi-Info software suite, built and maintained by the Centers for Disease Control and Prevention (CDC), is widely used by epidemiologists and public health researchers to collect and analyze public health data, especially in the event of outbreaks such as Ebola and Zika. It represents the current state-of-the-art thinking in the field and exemplifies the way that digital work can enhance public engagement in the humanities.Exploring Big Historical Data should be the go-to resource for undergraduate and graduate students confronted by a vast corpus of data, and researchers encountering these methods for the first time.
Authored 'live' online with ongoing feedback from the wider digital history community, Exploring Big Historical Data breaks new ground and sets the direction for the conversation into the future.
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It helps humanities scholars to grasp Big Data in order to do their work, whether that means understanding the underlying algorithms at work in search engines, or designing and using their own tools to process large amounts of information.Demonstrating what digital tools have to offer and also what 'digital' does to how we understand the past, the authors introduce the many different tools and developing approaches in Big Data for historical and humanistic scholarship, show how to use them, what to be wary of, and discuss the kinds of questions and new perspectives this new macroscopic perspective opens up. This pioneering book describes and demonstrates the ways these data can be explored to construct cultural heritage knowledge, for research and in teaching and learning. Exploring Big Historical Data by Shawn Graham Ian Milligan Scott Weingart The Digital Humanities have arrived at a moment when digital Big Data is becoming more readily available, opening exciting new avenues of inquiry but also new challenges.
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