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  • Measurement and Data
Data Analysis and Visualization in R for Ecologists
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CC BY
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Data Carpentry lesson from Ecology curriculum to learn how to analyse and visualise ecological data in R. Data Carpentry’s aim is to teach researchers basic concepts, skills, and tools for working with data so that they can get more done in less time, and with less pain. The lessons below were designed for those interested in working with ecology data in R. This is an introduction to R designed for participants with no programming experience. These lessons can be taught in a day (~ 6 hours). They start with some basic information about R syntax, the RStudio interface, and move through how to import CSV files, the structure of data frames, how to deal with factors, how to add/remove rows and columns, how to calculate summary statistics from a data frame, and a brief introduction to plotting. The last lesson demonstrates how to work with databases directly from R.

Subject:
Computer Science
Computer, Networking and Telecommunications Systems
Ecology
Information Science
Life Science
Mathematics
Measurement and Data
Material Type:
Module
Provider:
The Carpentries
Date Added:
04/11/2023
Data Analysis and Visualization with Python for Social Scientists
Unrestricted Use
CC BY
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Python is a general purpose programming language that is useful for writing scripts to work effectively and reproducibly with data. This is an introduction to Python designed for participants with no programming experience. These lessons can be taught in a day (~ 6 hours). They start with some basic information about Python syntax, the Jupyter notebook interface, and move through how to import CSV files, using the pandas package to work with data frames, how to calculate summary information from a data frame, and a brief introduction to plotting. The last lesson demonstrates how to work with databases directly from Python.

Subject:
Computer Science
Computer, Networking and Telecommunications Systems
Information Science
Mathematics
Measurement and Data
Material Type:
Module
Provider:
The Carpentries
Date Added:
04/11/2023
Data Carpentry for Biologists
Unrestricted Use
CC BY
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The Biology Semester-long Course was developed and piloted at the University of Florida in Fall 2015. Course materials include readings, lectures, exercises, and assignments that expand on the material presented at workshops focusing on SQL and R.

Subject:
Biology
Computer Science
Computer, Networking and Telecommunications Systems
Information Science
Life Science
Mathematics
Measurement and Data
Material Type:
Module
Provider:
The Carpentries
Date Added:
04/11/2023
Data Cleaning with OpenRefine for Ecologists
Unrestricted Use
CC BY
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A part of the data workflow is preparing the data for analysis. Some of this involves data cleaning, where errors in the data are identified and corrected or formatting made consistent. This step must be taken with the same care and attention to reproducibility as the analysis. OpenRefine (formerly Google Refine) is a powerful free and open source tool for working with messy data: cleaning it and transforming it from one format into another. This lesson will teach you to use OpenRefine to effectively clean and format data and automatically track any changes that you make. Many people comment that this tool saves them literally months of work trying to make these edits by hand.

Subject:
Computer Science
Computer, Networking and Telecommunications Systems
Information Science
Mathematics
Measurement and Data
Material Type:
Module
Provider:
The Carpentries
Date Added:
04/11/2023
Data-Driven Learning Personas
Only Sharing Permitted
CC BY-ND
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Learn how instructional designers use data to inform the creation of a Learning Persona. Learning Personas help determine the needs of the training and help ...

Subject:
Business and Communication
Career and Technical Education
Communication
Education
English Language Arts
Mathematics
Measurement and Data
Material Type:
Lesson
Date Added:
04/08/2023
Data Management with SQL for Ecologists
Unrestricted Use
CC BY
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Databases are useful for both storing and using data effectively. Using a relational database serves several purposes. It keeps your data separate from your analysis. This means there’s no risk of accidentally changing data when you analyze it. If we get new data we can rerun a query to find all the data that meets certain criteria. It’s fast, even for large amounts of data. It improves quality control of data entry (type constraints and use of forms in Access, Filemaker, etc.) The concepts of relational database querying are core to understanding how to do similar things using programming languages such as R or Python. This lesson will teach you what relational databases are, how you can load data into them and how you can query databases to extract just the information that you need.

Subject:
Computer Science
Computer, Networking and Telecommunications Systems
Information Science
Mathematics
Measurement and Data
Material Type:
Module
Provider:
The Carpentries
Date Added:
04/11/2023
Data Management with SQL for Social Scientists
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CC BY
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This is an alpha lesson to teach Data Management with SQL for Social Scientists, We welcome and criticism, or error; and will take your feedback into account to improve both the presentation and the content. Databases are useful for both storing and using data effectively. Using a relational database serves several purposes. It keeps your data separate from your analysis. This means there’s no risk of accidentally changing data when you analyze it. If we get new data we can rerun a query to find all the data that meets certain criteria. It’s fast, even for large amounts of data. It improves quality control of data entry (type constraints and use of forms in Access, Filemaker, etc.) The concepts of relational database querying are core to understanding how to do similar things using programming languages such as R or Python. This lesson will teach you what relational databases are, how you can load data into them and how you can query databases to extract just the information that you need.

Subject:
Computer Science
Computer, Networking and Telecommunications Systems
Information Science
Mathematics
Measurement and Data
Social Science
Material Type:
Module
Provider:
The Carpentries
Date Added:
04/11/2023
Data Organization in Spreadsheets for Ecologists
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CC BY
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Good data organization is the foundation of any research project. Most researchers have data in spreadsheets, so it’s the place that many research projects start. We organize data in spreadsheets in the ways that we as humans want to work with the data, but computers require that data be organized in particular ways. In order to use tools that make computation more efficient, such as programming languages like R or Python, we need to structure our data the way that computers need the data. Since this is where most research projects start, this is where we want to start too! In this lesson, you will learn: Good data entry practices - formatting data tables in spreadsheets How to avoid common formatting mistakes Approaches for handling dates in spreadsheets Basic quality control and data manipulation in spreadsheets Exporting data from spreadsheets In this lesson, however, you will not learn about data analysis with spreadsheets. Much of your time as a researcher will be spent in the initial ‘data wrangling’ stage, where you need to organize the data to perform a proper analysis later. It’s not the most fun, but it is necessary. In this lesson you will learn how to think about data organization and some practices for more effective data wrangling. With this approach you can better format current data and plan new data collection so less data wrangling is needed.

Subject:
Computer Science
Computer, Networking and Telecommunications Systems
Information Science
Mathematics
Measurement and Data
Material Type:
Module
Provider:
The Carpentries
Date Added:
04/11/2023
Data Wrangling and Processing for Genomics
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CC BY
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Data Carpentry lesson to learn how to use command-line tools to perform quality control, align reads to a reference genome, and identify and visualize between-sample variation. A lot of genomics analysis is done using command-line tools for three reasons: 1) you will often be working with a large number of files, and working through the command-line rather than through a graphical user interface (GUI) allows you to automate repetitive tasks, 2) you will often need more compute power than is available on your personal computer, and connecting to and interacting with remote computers requires a command-line interface, and 3) you will often need to customize your analyses, and command-line tools often enable more customization than the corresponding GUI tools (if in fact a GUI tool even exists). In a previous lesson, you learned how to use the bash shell to interact with your computer through a command line interface. In this lesson, you will be applying this new knowledge to carry out a common genomics workflow - identifying variants among sequencing samples taken from multiple individuals within a population. We will be starting with a set of sequenced reads (.fastq files), performing some quality control steps, aligning those reads to a reference genome, and ending by identifying and visualizing variations among these samples. As you progress through this lesson, keep in mind that, even if you aren’t going to be doing this same workflow in your research, you will be learning some very important lessons about using command-line bioinformatic tools. What you learn here will enable you to use a variety of bioinformatic tools with confidence and greatly enhance your research efficiency and productivity.

Subject:
Computer Science
Computer, Networking and Telecommunications Systems
Genetics
Information Science
Life Science
Mathematics
Measurement and Data
Material Type:
Module
Provider:
The Carpentries
Date Added:
04/11/2023
Databases and SQL
Unrestricted Use
CC BY
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Software Carpentry lesson that teaches how to use databases and SQL In the late 1920s and early 1930s, William Dyer, Frank Pabodie, and Valentina Roerich led expeditions to the Pole of Inaccessibility in the South Pacific, and then onward to Antarctica. Two years ago, their expeditions were found in a storage locker at Miskatonic University. We have scanned and OCR the data they contain, and we now want to store that information in a way that will make search and analysis easy. Three common options for storage are text files, spreadsheets, and databases. Text files are easiest to create, and work well with version control, but then we would have to build search and analysis tools ourselves. Spreadsheets are good for doing simple analyses, but they don’t handle large or complex data sets well. Databases, however, include powerful tools for search and analysis, and can handle large, complex data sets. These lessons will show how to use a database to explore the expeditions’ data.

Subject:
Computer Science
Computer, Networking and Telecommunications Systems
Information Science
Mathematics
Measurement and Data
Material Type:
Module
Provider:
The Carpentries
Date Added:
04/11/2023
Dating Students: Relative vs. Numerical Time
Conditional Remix & Share Permitted
CC BY-NC-SA
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In this lab, students are introduced to the difference between relative and absolute dating, using the students themselves as the material to be ordered. Initially, the students are asked to develop physical clues to put themselves in order from youngest to oldest (exposing the inferences we make unconsciously about people's ages), and this will be refined/modified using a list of current events from an appropriate historical period that more and more of the students will remember, depending on their age (among other variables). Absolute age is introduced by having the students order themselves by birth decade, year, month, and day, and comparing the absolute age order to the order worked out in the relative-dating exercise, with a discussion of dating precision and accuracy.

(Note: this resource was added to OER Commons as part of a batch upload of over 2,200 records. If you notice an issue with the quality of the metadata, please let us know by using the 'report' button and we will flag it for consideration.)

Subject:
Applied Science
Biology
Computer, Networking and Telecommunications Systems
Earth and Space Science
Environmental Science
Geology
Information Science
Life Science
Mathematics
Measurement and Data
Material Type:
Activity/Lab
Provider:
Science Education Resource Center (SERC) at Carleton College
Provider Set:
Teach the Earth
Date Added:
08/10/2019
Decibels and Acoustical Engineering
Read the Fine Print
Educational Use
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In this lesson, students learn that sound is energy and has the ability to do work. Students discover that sound is produced by a vibration and they observe soundwaves and how they travel through mediums. They understand that sound can be absorbed, reflected or transmitted. Through associated activities, videos and a PowerPoint presentation led by the teacher, students further their exploration of sound through discussions in order to build background knowledge.

Subject:
Applied Science
Engineering
Mathematics
Measurement and Data
Physical Science
Statistics and Probability
Material Type:
Lesson
Provider:
TeachEngineering
Provider Set:
Lessons
Date Added:
03/01/2019
Deciviews from Look Rock, Great Smoky Mountains National Park: How Hazy is it?
Conditional Remix & Share Permitted
CC BY-NC-SA
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Spreadsheets Across the Curriculum/Geology of National Parks module. Students calculate the haze index and standard visual range from concentrations of particulate matter.

(Note: this resource was added to OER Commons as part of a batch upload of over 2,200 records. If you notice an issue with the quality of the metadata, please let us know by using the 'report' button and we will flag it for consideration.)

Subject:
Atmospheric Science
Biology
Earth and Space Science
Life Science
Mathematics
Measurement and Data
Statistics and Probability
Material Type:
Activity/Lab
Provider:
Science Education Resource Center (SERC) at Carleton College
Provider Set:
Teach the Earth
Date Added:
07/31/2020
Delta County Mines
Read the Fine Print
Educational Use
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This Western Mining History database uses Mineral Resources Data System to list known Colorado historical mines by county. Each county site has links to the known mines within its borders. Some are known and named, others are unnamed. Mines should be assumed to be on private property unless other research is conducted. Data provided for each mine site include: Name, State, County, Elevation, Primary Mineral Mined, Latitude and Longitude and a link to Google Maps. Photos are provided where available. Additional information for some Mines are satellite photos, and ownership, business and historical records. Mining History is an historical site that provides information on mining, mining towns, the gold and silver rush, and Photos and maps of the western United States. This is a great database for student historical research or data and statistics classes. Consider becoming a member or making a donation to help further the work of the site.

Subject:
Anthropology
Applied Science
Chemistry
Cultural Geography
Earth and Space Science
Economics
English Language Arts
Environmental Science
Geology
Geoscience
History
Mathematics
Measurement and Data
Physical Geography
Physical Science
Reading Informational Text
Social Science
Sociology
U.S. History
Material Type:
Data Set
Primary Source
Reading
Provider:
Western Mining History
Provider Set:
Historical Colorado Mines
Date Added:
02/06/2023
Delta environments and paleogeography
Conditional Remix & Share Permitted
CC BY-NC-SA
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Students are given 4 hypothetical stratigraphic columns (each roughly 30 m thick) of deltaic deposits, 3 base maps with section locations, and a map scale. Students subdivide the stratigraphic units into subfacies and interpret subenvironments (delta plain, delta front, prodelta, marine) and describe/list features used to make these interpretations. Using depositional interpretations, 3 bentonite marker beds, and paleocurrent information, students draw 3 successive paleogeographic maps of the region showing delta migration through time.

(Note: this resource was added to OER Commons as part of a batch upload of over 2,200 records. If you notice an issue with the quality of the metadata, please let us know by using the 'report' button and we will flag it for consideration.)

Subject:
Biology
Life Science
Mathematics
Measurement and Data
Statistics and Probability
Material Type:
Activity/Lab
Provider:
Science Education Resource Center (SERC) at Carleton College
Provider Set:
Teach the Earth
Date Added:
08/10/2019
Demonstration of radioactive decay using pennies
Conditional Remix & Share Permitted
CC BY-NC-SA
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A demonstration (with full class participation) to illustrate radioactive decay by flipping coins. Shows students visually the concepts of exponential decay, half-life and randomness. Works best in large classes -- the more people, the better.

(Note: this resource was added to OER Commons as part of a batch upload of over 2,200 records. If you notice an issue with the quality of the metadata, please let us know by using the 'report' button and we will flag it for consideration.)

Subject:
Biology
Earth and Space Science
Geology
Life Science
Mathematics
Measurement and Data
Statistics and Probability
Material Type:
Simulation
Provider:
Science Education Resource Center (SERC) at Carleton College
Provider Set:
Teach the Earth
Date Added:
08/25/2019
Density Driven Flows
Conditional Remix & Share Permitted
CC BY-NC-SA
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This hands-on lab activity is designed to teach students about how density differences, due to salinity, drive the flow of currents in the ocean. It also helps develop skills in performing and designing simple laboratory measurements; data entry, calculations and graph plotting in a spreadsheet; and comparing experimental data with a theoretical equation.
Key words: ocean circulation; density driven flows; salinity; ocean density; thermohaline circulation.

Subject:
Applied Science
Earth and Space Science
Environmental Science
Mathematics
Measurement and Data
Oceanography
Material Type:
Activity/Lab
Provider:
Science Education Resource Center (SERC) at Carleton College
Provider Set:
Teach the Earth
Date Added:
04/12/2023
Density of Earth - Using Some Field Data
Conditional Remix & Share Permitted
CC BY-NC-SA
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This module addresses the problem of how to determine the density of the earth and has students do some field experiments to get the data they need to answer the problem.

(Note: this resource was added to OER Commons as part of a batch upload of over 2,200 records. If you notice an issue with the quality of the metadata, please let us know by using the 'report' button and we will flag it for consideration.)

Subject:
Biology
Life Science
Mathematics
Measurement and Data
Physical Science
Physics
Statistics and Probability
Material Type:
Activity/Lab
Provider:
Science Education Resource Center (SERC) at Carleton College
Provider Set:
Teach the Earth
Date Added:
09/05/2019
Density of Rocks - How large is a ton of rock?
Conditional Remix & Share Permitted
CC BY-NC-SA
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This module addresses the problem of how to determine the size of a ton of rocks of a given composition and invites the student to figure out how to solve the problem.

(Note: this resource was added to OER Commons as part of a batch upload of over 2,200 records. If you notice an issue with the quality of the metadata, please let us know by using the 'report' button and we will flag it for consideration.)

Subject:
Biology
Life Science
Mathematics
Measurement and Data
Statistics and Probability
Material Type:
Activity/Lab
Provider:
Science Education Resource Center (SERC) at Carleton College
Provider Set:
Teach the Earth
Date Added:
09/05/2019
Density of the Earth - How to Solve It
Conditional Remix & Share Permitted
CC BY-NC-SA
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This module addresses the real problem of determining the density of the Earth and invites the student to figure out how to solve the problem.

(Note: this resource was added to OER Commons as part of a batch upload of over 2,200 records. If you notice an issue with the quality of the metadata, please let us know by using the 'report' button and we will flag it for consideration.)

Subject:
Biology
Life Science
Mathematics
Measurement and Data
Physical Science
Physics
Statistics and Probability
Material Type:
Activity/Lab
Provider:
Science Education Resource Center (SERC) at Carleton College
Provider Set:
Teach the Earth
Date Added:
09/05/2019