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What are some innovative ways to use data visualization tools and software for scientific research?

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Data visualization is the process of transforming complex and abstract data into graphical and interactive forms that can reveal patterns, trends, and insights. Data visualization tools and software are essential for scientific research, as they can help researchers communicate their findings, explore hypotheses, and discover new phenomena. In this article, you will learn about some innovative ways to use data visualization tools and software for scientific research, such as:

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Asha Kanta Sharma

Manager - Finance & Accounts @ Opendoors Fintech | Financial Accounting

1 Creating interactive dashboards

One way to use data visualization tools and software for scientific research is to create interactive dashboards that can display multiple charts, graphs, maps, and tables in a single interface. Interactive dashboards can help researchers monitor, compare, and analyze data from different sources, such as experiments, surveys, simulations, or databases. Interactive dashboards can also allow researchers to filter, sort, and drill down into data, as well as customize the appearance and layout of the visualizations. Some examples of data visualization tools and software that can create interactive dashboards are Tableau, Power BI, and R Shiny.

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Asha Kanta Sharma

Manager - Finance & Accounts @ Opendoors Fintech | Financial Accounting
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Data visualization tools are crucial in scientific research for analyzing and communicating complex data. Innovative methods include interactive dashboards, 3D visualization, network analysis, temporal data visualization, augmented reality, machine learning-enhanced visualization, storytelling, geospatial analysis, live data streaming, and wearable device integration. Collaborative visualization platforms encourage teamwork, while visual abstracts summarize findings. Semantic visualizations represent relationships, and data sonification converts data into sound for auditory interpretation. Automated data exploration saves time and helps researchers focus on critical areas.

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Samuel Momodu

Using data to solve business problems.
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Create key metrics that are relevant to the business goal, use visualisations to show the measurement of the business success or learnings, relative to the overarching goal. Have a brief meeting with the target audience of each visualisation to o reach them how-to and what next.

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Daniel Kofi Sarkodie Duah, Dip.CII, FMA

Transformation & Partnerships Manager @ iRisk || Linkedin Top Voice || Google Certified Data Analyst || Insurance Business Intelligence || Aspiring PMP
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Data visualization tools can transform complex scientific findings into easily understandable insights. Imagine representing DNA sequences as colorful patterns, making genetic research accessible. Heatmaps can highlight drug efficacy across various conditions, aiding pharmaceutical studies. Interactive graphs can show how climate change affects ecosystems, engaging the public in environmental research. Visualizing protein structures in 3D helps researchers understand their functions, potentially advancing drug design. In essence, these tools turn raw data into compelling stories, fostering collaboration and communication in the scientific community and beyond.

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2 Using 3D and VR/AR technologies

Another way to use data visualization tools and software for scientific research is to use 3D and VR/AR technologies that can create immersive and realistic representations of data. 3D and VR/AR technologies can help researchers visualize data that has multiple dimensions, such as spatial, temporal, or categorical data. 3D and VR/AR technologies can also help researchers interact with data in a more natural and intuitive way, such as by using gestures, voice, or eye movements. Some examples of data visualization tools and software that can use 3D and VR/AR technologies are Unity, Unreal Engine, and A-Frame.

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3 Applying machine learning and AI techniques

A third way to use data visualization tools and software for scientific research is to apply machine learning and AI techniques that can enhance the analysis and interpretation of data. Machine learning and AI techniques can help researchers identify patterns, anomalies, clusters, and correlations in data, as well as generate predictions, recommendations, and explanations. Machine learning and AI techniques can also help researchers create dynamic and adaptive visualizations that can respond to user input, feedback, and preferences. Some examples of data visualization tools and software that can apply machine learning and AI techniques are TensorFlow, D3.js, and Plotly.

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4 Developing custom and novel visualizations

A fourth way to use data visualization tools and software for scientific research is to develop custom and novel visualizations that can suit the specific needs and goals of the research project. Custom and novel visualizations can help researchers express their creativity, originality, and innovation, as well as address the challenges and limitations of existing visualizations. Custom and novel visualizations can also help researchers engage and inform their audiences, such as peers, reviewers, funders, or the public. Some examples of data visualization tools and software that can develop custom and novel visualizations are Python, R, and JavaScript.

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Samuel Momodu

Using data to solve business problems.
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Always develop custom visualisations for each business goal. This allows stakeholders to understand progress level and factors aiding success.

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5 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?

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Samuel Momodu

Using data to solve business problems.
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While it’s great to build out visuals, ensure the target audience of each visual understands Bothe the context of the visual (KPI’s) and how-to navigate the visualisation.

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What are some innovative ways to use data visualization tools and software for scientific research?

1

2

3

4

5

1 Creating interactive dashboards

2 Using 3D and VR/AR technologies

3 Applying machine learning and AI techniques

4 Developing custom and novel visualizations

5 Here’s what else to consider

Analytical Skills

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What are some innovative ways to use data visualization tools and software for scientific research?

1

2

3

4

5

1 Creating interactive dashboards

2 Using 3D and VR/AR technologies

3 Applying machine learning and AI techniques

4 Developing custom and novel visualizations

5 Here’s what else to consider

Analytical Skills

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