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Last updated on 2024年7月12日

Here's how you can make data-driven decisions in geology.

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Understanding the foundational role of data in geology is paramount. As a geologist, you navigate an intricate world of rocks, minerals, and the processes that shape the Earth. To make informed decisions in this complex field, it's essential to rely on data. Data-driven decision-making involves collecting, analyzing, and interpreting geological data to guide your explorations and conclusions. This approach minimizes guesswork and maximizes the accuracy and efficiency of your geological assessments. Whether you're investigating plate tectonics, searching for mineral deposits, or assessing natural hazards, embracing a data-centric mindset can vastly improve your outcomes.

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Geoffrey Thyne

Chief Technology Officer at ESal

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Hedieh Alvan, PhD

Manager of Technology Solutions at Esri Canada
Onesmus Shithigona (Pr. Sci. Nat)

Senior Project Geologist: Portfolio/Capital Projects (Debmarine Namibia) | MRes: Marine Geophysics

1 Gather Data

The first step in making data-driven decisions is to gather high-quality geological data. This can involve fieldwork, where you collect samples and make observations, or remote sensing techniques using satellites and aerial photography. You should also consider historical data and research from geological databases and publications. The goal is to compile a comprehensive dataset that represents the geological phenomena you are studying. Remember, the quality of the data you collect directly impacts the reliability of your decisions, so meticulous collection and recording are crucial.

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Geoffrey Thyne

Chief Technology Officer at ESal
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Data is the fundamental basis of knowledge. Any interpretation/conclusion/recommendation must honor the data. How? Let the data speak to you. Start with a simple description of the data and its' trends. Build out from there. Be aware that any simplification, while valuable in recognizing and analyzing trends, must stand up when returning the full data. Simplification/processing reduces loses information. Your analysis has to go back up to the full dataset, all the different forms that may be in, and still be coherent. BUT - the real information may be in the 'doesn't fit' category. That's where the really great stuff comes from. Isn't science fun!

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Hedieh Alvan, PhD

Manager of Technology Solutions at Esri Canada
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Data-driven decisions are crucial in geology. Using advanced analytics and machine learning, we can enhance geological models, optimize resource management, and predict environmental impacts more accurately. This approach drives innovation and efficiency in geological studies.

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Emmett (Van) Reed

USA Insurance Products, with focus on services available to Foreign Nationals
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I expect geologists face a broad range of technical challenges, ie, project objectives. And each project likely requires specific data/information to satisfy project objectives. As part of this, AI and associated data may be seen as a useful tool able to help at the project planning stage, or later is helping to analyze data. However we as professionals (geologists or whatever) are the key players. We should always remember that AI is a tool (and a powerful one at that). But if we accept the responsibilities of being a professional, then we accept the responsibility of checking and rechecking results/data presented to us. As professionals, reliable data and useful information serves as the “gold” of our trade.

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2 Analyze Trends

Once you have your data, the next step is to analyze it for trends and patterns. This often involves statistical analysis and modeling to understand the relationships between different geological variables. For example, you might use regression analysis to predict the location of mineral deposits based on geological formations. Sophisticated software can assist in visualizing data trends, allowing you to make predictions and hypotheses about geological processes. Accurate analysis is critical for interpreting the data correctly and making informed decisions.

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Sean Meadon

Geology Mentor
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Remember not to look at a specific dataset in isolation only, consider relationships with other data, with other controls such as structure. Different analyses from a single sample share at least one common trait, location! Investigate how they interact. Now on a different point, get your QAQC right, your data is expensive, so ensure you can trust it.

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3 Technology Use

Technology plays a crucial role in handling and interpreting geological data. Geographic Information Systems (GIS) are invaluable tools for mapping and analyzing spatial data, providing a visual representation of geological features. Similarly, specialized software can simulate geological processes and model different scenarios based on your data. Staying abreast of technological advancements and learning how to leverage these tools effectively can significantly enhance your decision-making capabilities in geology.

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4 Risk Assessment

In geology, risk assessment is a key component of decision-making . You must evaluate the potential risks associated with natural events like earthquakes, volcanic eruptions, or landslides. Data-driven risk assessments involve analyzing historical data, frequency of events , and current geological conditions to estimate the likelihood and potential impact of such events. This information is vital for informing safety measures, emergency preparedness, and land-use planning, ensuring that you make decisions that prioritize safety and sustainability.

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5 Collaborative Input

Collaboration with other experts can enrich your decision-making process. Sharing data and insights with colleagues from different geoscience disciplines can provide a more holistic understanding of geological issues. Interdisciplinary teams can combine expertise in geology, hydrology, geochemistry, and other fields to analyze data from multiple perspectives. This collaborative approach can lead to more robust and well-rounded decisions, as it allows for cross-validation of data and hypotheses.

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6 Continuous Learning

Finally, the geological landscape is ever-changing, and so should be your knowledge and skills. Continuous learning is vital in staying updated with the latest research, technological tools, and best practices in data analysis. Attend conferences, participate in workshops, and engage with the scientific community to keep your expertise sharp. Embracing lifelong learning ensures that your data-driven decisions are based on the most current knowledge and that you remain a competent and effective geologist.

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Onesmus Shithigona (Pr. Sci. Nat)

Senior Project Geologist: Portfolio/Capital Projects (Debmarine Namibia) | MRes: Marine Geophysics
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The days of being an abstract Geologist are long gone. Geoscientists now have to embrace the advent of Machine Learning principles and therefore need to upskill themselves. Python programming is particularly a must to remain relevant in the field. The Edx web platform currently has a very useful free course in Python Programming that I found very useful. The Orange Data Mining Software (also free) is also useful to learn if you want to look at data trends and allow the data to help you make decisions.

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7 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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clid Ekiki

Géologue d’exploration??Spécialité : Recherche et Développement des gisements aurifères ,manganésifère et ferrifère
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- Je suis parfaitement d'accord avec tout ce qui a été dit plus haut. - J'aimerais juste ajouter, qu'il de la passion, pour faire le métier que nous avons choisi. -De plus une bonne préparation cad analyse des données, facilite grandement, le travail sur le terrain.

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Here's how you can make data-driven decisions in geology.

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1 Gather Data

2 Analyze Trends

3 Technology Use

4 Risk Assessment

5 Collaborative Input

6 Continuous Learning

7 Here’s what else to consider

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