{"id":4479,"date":"2023-12-18T07:01:17","date_gmt":"2023-12-18T07:01:17","guid":{"rendered":"https:\/\/www.editage.com\/insights\/how-science-visualization-can-help-your-research-create-impact\/"},"modified":"2024-07-31T06:53:20","modified_gmt":"2024-07-31T06:53:20","slug":"how-science-visualization-can-help-your-research-create-impact","status":"publish","type":"post","link":"https:\/\/www.editage.com\/insights\/how-science-visualization-can-help-your-research-create-impact","title":{"rendered":"How science visualization can help your research create impact"},"content":{"rendered":"

Introduction to Scientific Visualization<\/span><\/strong><\/span><\/span><\/span><\/span><\/span><\/p>\n

NASA has a fleet of <\/span>dozens of satellites<\/a> observing Earth from space. These satellites monitor and relay data on a wide range of subjects ranging from climate change to weather forecasting, disaster management, resource exploration, and more. Let\u2019s look at the work of an instrument carried on two of these satellites\u2014the Moderate Resolution Imaging Spectroradiometer (MODIS). MODIS acquires <\/span>a massive amount of data: data across <\/span>36 spectral bands<\/a>,<\/span> spanning the electromagnetic spectrum, are captured by measuring the<\/span> intensity of reflected light (within each band) across the earth. The data in this case is, ultimately, <\/span>big data.<\/span><\/span><\/p>\n

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Dealing with large and complex datasets involves a good deal of data scrubbing and data analysis. Algorithms and custom software need to be employed to make sense of the data, to identify patterns or trends and to glean insights. But, even after that, a visual representation can provide a lot more perspectives than an array of numbers, wouldn\u2019t you agree?<\/span><\/span><\/span><\/p>\n

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Consider this: you want to study the impact of climate change on the oceans. You wish to begin by <\/span>analyzing the phytoplankton cover across the earth\u2019s waters, over a couple of years. NASA\u2019s MODIS can help you with this. But imagine dealing with billions of rows of numbers correlating to light intensities in the blue-green range, for different coordinates (corresponding to various points in the oceans of the earth), at different timestamps, and for several years. Now contrast that with an animated map, showing fluctuations in the phytoplankton cover over time.<\/span><\/span><\/span><\/p>\n

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Ocean Color from July 2002 to March 2017 \u2013 NASA Aqua satellite<\/strong><\/a><\/p>\n

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Even better, imagine being able to overlay a secondary dataset, say <\/span>sea surface temperature, displayed in a different color scheme<\/span>, <\/span><\/span>directly onto this video. Obviously, data in rows and columns and charts does tell you a lot. But, a visual? A visual can tell you what direction you need to look in to analyze your data. It can reveal trends and connections that would otherwise go unnoticed. And this is the power of scientific visualization.<\/span><\/span><\/span><\/p>\n

Applications of Science Visualizations<\/span><\/strong><\/span><\/span><\/span><\/span><\/span><\/h1>\n

Of course, although analyzing big data is agreeably a very powerful application of scientific visualization, its value extends far beyond that. This multifaceted approach possesses the unique ability to simplify complex scientific concepts for diverse audiences, fostering deeper understanding and engagement. Its impact extends across a variety of crucial areas, including the following:<\/span><\/span><\/span><\/p>\n

Advancing Research<\/span><\/strong><\/span><\/span><\/span><\/span><\/span><\/h2>\n

Visualizations in science need not always be generated by complex algorithms or a string of code. Simple hand-drawn bar graphs, scatter plots, heat maps, etc., also serve as tools for data analysis and interpretation. In fact, <\/span>this<\/a> illustration of the yeast mitotic spindle\u2014which was conceived following a remarkable two-year collaboration between scientists and artists\u2014is also a visualization. So is <\/span>this<\/a> infographic, made painstakingly by \u201ctoiling in the data mines\u201d of a study on bee\u2013plant interactions of over 120 years. The same goes for <\/span>this<\/a> microscopy photo of trichomes on the <\/span>skin of an immature cucumber.<\/span><\/span><\/span><\/p>\n

Visualizations can be of any kind or format, but what they do is bring before your eyes a picture that you would have missed otherwise, thus serving as a tool for generating new ideas and hypotheses. It allows comprehension, interpretation, exploration, and may even guide novel, fortuitous, study directions.<\/span><\/span><\/span><\/span><\/p>\n

Visualizations help you appreciate interesting data or information from studies outside your field of expertise. Such instances could lead to very fruitful interdisciplinary collaborations too. And, as far as big data is concerned\u2014for studies from genomics, particle physics, astronomy, neuroscience, and more\u2014visualizations are invaluable. Let\u2019s consider some of the instances of how scientific visualizations are being used by researchers in different fields.<\/span><\/span><\/span><\/span><\/p>\n