All groups investigated emerging trends in quantum sensing. For more info, see the Infographics Contest page.
Lulwah and Mostafa
 | In this project, we were interested in predicting emerging technology trend in quantum sensing. For the project, we were provided with datasets of publication related to quantum sensing. The data initially gathered by searching "Term of Keyword" related to quantum sensing. The initial dataset has 70 papers related to different field of quantum sensing. The dataset contains title, abstract, year of publication, authors and keyword index. During the project we have extended the dataset by addition following contents; affiliation of the author and the content of paper if it was available to public. In addition, we extracted the keywords from the dataset that are related to quantum sensing. As like many visualization project, In this project, we had to deal with the challenges of cleaning, filtering and organizing the actual raw data. At the beginning of the project we had to do lot of manual cleaning and filtering of the data. Later we use organize the extracted data into several parts in order to make it useful for visualization. |
Liang
 | Before investing time, funding and valuable resources in a research area, researchers and investors need to be prepared with a good understanding of its development and growth trends, including detecting growth patterns, identifying interesting exceptions or changes, and predicting potential future via analyzing a large number of statistical data. A good visualization can effectively facilitate these tasks and transform data into useful information. In this project, I apply powerful visualization techniques and design principles to implement an interactive visualization for analyzing development trend of quantum sensing technologies. The visualization abstracts interesting information from a large-scale dataset and clearly represent the data. Interaction methods are adopted also, which allow users to zoom and filter, highlight and query more detailed information. Researchers and scientists can take advantage of this visualization to obtain insights as where and when the quantum sensing research started, how a specific research topic is developed, and what is the potential future of a research topic. Based on the visualization results, users can get clues for investment decisions. |
Abhishek and Ben
 | Often data provides much information regarding itself than we can infer. Many times we cannot gain insight about the data by just looking at it. It hides some of the information. So, need arises to visualize the data, where we can gain insight about the data itself. As gaining insight about the data is the main purpose of visualization, we thought of visualizing the data. This is where the words of Ben Shneiderman comes to my mind, “The purpose of visualization is insight, not pictures”. Our goal was to visualize the data i.e., the papers on a world map. |
Mat
 | One method to find trends in any industry is to examine the publications related to that industry. Given a set of publications, one should be able to extrapolate trends based on solely on the publications’ metadata, e.g., title, keywords, abstract. For one to analyze text data to determine trends is daunting, so another method should be used that analyzes this data and presents it in a way that can be easily consumed by a casual user. This casual user should be be able to achieve the goal of identifying trends in the respective industry. In this paper I have created a visualization that examines a small corpus consisting of metadata (BibTeX) about a collection of articles related to Quantum Sensing. Based solely on this data, I am able to provide an interface that allows a user to explore this data and conclude many attributes of the data set and industry, including finding trends. |
Andrew S.
Wayne
 | In this paper, I present a visualization for displaying the history and trajectory of quantum sensing. History is shown as a year-by-year slideshow. The most publicized quantum sensing areas for the selected year are displayed. Clicking on a topic shows the amount of publications on that subject over time. This allows users to see when a subject started to rise in popularity, and at what point in time (if any) it started to decline. The visualization also shows which research groups have the most publications for the selected subject. The final slide in the visualization is a projection for the year 2025 to show where quantum sensing is headed in the future. |
Andrew W.
 | The United States Air Force is interested in detecting new trends in technological research, namely Quantum Sensing. In many cases, the most effective way to boost a project dealing with data analysis is to visualize the data at hand, which entails seven steps: acquisition, parsing, filtering, mining, representation, refining, and interaction. Throughout these steps one can turn a set of raw, unreadable data into a useful visualization that can depict trends, stories, relationships, and sometimes all of the above. I propose a tool that will allow the Air Force to determine which fields of research are popular, detailed with trends per year and field. |
