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What are Data and Data Literacy: Study Hall Data Literacy #1: ASU + Crash Course

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Telling Stories with Data in 3 Steps (Quick Study)

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Factfulness by Hans Rosling – Animated Review and Summary

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How statistics can be misleading - Mark Liddell

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In this activity, students further explore the short film Popped Secret: The Mysterious Origin of Corn, by working through the mathematical concepts behind George Beadle's claim that teosinte is the wild ancestor of maize.

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Empowering Educators. Inspiring Students. Real science, real stories, and real data to engage students in exploring the living world.

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The activities are as follows:

When animals are born, some offspring are able to survive on their own, while others rely on parental care. Parental care can take many forms. One or both parents might help raise the young, or in some species other members of the group help them out. The more time and energy the parents invest, the more likely it is that their offspring will survive. However, parental care is costly for the parents. When a parent invests time, energy, and resources in their young, they are unable to invest as much in other activities, like finding food for themselves. This results in a tradeoff, or a situation where there are costs and benefits to the decisions that must be made. Parents must balance their time between caring for their offspring and other activities.

The severity of the tradeoff between parental care and other activities may depend on environmental conditions. For example, if there is a lot of food available, parents may spend more time tending to their young because finding food for themselves takes less time and energy. Scientists wonder if parents are able to adjust their parental care strategies in response to environmental changes.

Tina is a scientist studying the clown anemonefish. She is interested in how parental care in this species changes in response to the environment. She chose to study anemonefish because they use an interesting system to take care of their young, and because the environment is always changing in the coral reefs where they live.

Anemonefish form monogamous pairs and live in groups of up to six individuals. The largest female is in charge of the group. Only the largest male and female get to mate and take care of the young. Both parents care for eggs by tending them, mouthing the eggs to clean the nest and remove dead eggs, and fanning eggs with their fins to oxygenate them. A single pair may breed together tens or even hundreds of times over their lifetimes. But here is the cool part - anemonefish can change their sex! If the largest female dies, the largest male changes to female, and the next largest fish in line becomes the new breeding male. That means that a single parent may have the opportunity to be a mother and a father during its lifetime.

On the reef, anemonefish groups also experience shifts in how much food is available. In years with lots of food, the breeding pair has lots of young, and in years with little food they do not breed as often. Tina presumed that food availability determines how much time and energy the parents invest in parental care behaviors. She collected data from 20 breeding pairs of fish, 10 of which she gave half rations of food, and 10 of which she gave full rations. The experiment ran for six lunar months. Every time a pair laid a clutch of eggs, Tina waited 7 days and then took a 15-minute video of the parents and their nest. She watched the videos and measured three parental care behaviors: mouthing, fanning, and total time spent tending for both males and females. Some pairs laid eggs more than once, so she averaged these behaviors across the six months of the experiment. Tina predicted that parents fed a full ration would perform more parental care behaviors, and for a longer amount of time, than parents fed a half ration.

Watch video of the experimental trials, demonstrating the mouthing and fanning behaviors:
Featured scientist: Tina Barbasch from Boston University Flesch-Kincaid Reading Grade Level = 9.4
About Tina: I first became interested in science catching frogs and snakes in my backyard in Ithaca, NY. This inspired me to major in Biology at Cornell University, located in my hometown. As an undergraduate, I studied male competition and sperm allocation in the local spotted salamander, Ambystoma maculatum. After graduating, I joined the Peace Corps and spent 2 years in Morocco teaching environmental education and 6 months in Liberia teaching high school chemistry. As a PhD student in the Buston Lab, I study how parents negotiate over parental care in my study system the clownfish, Amphiprion percula, otherwise known as Nemo. More here!

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Raising Nemo: Parental care in the clown anemonefish | Data Nuggets

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The activities are as follows: When animals are born, some offspring are able to survive on their own, while others rely on parental care. Parental care can take many forms. One or both parents might...

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Free Data Sets & Dataset Samples | Maven Analytics

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Develop your data analytics skillset with our free data sets using real-world data, from flight delays and movie ratings to shark attacks and UFO sightings

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Hey, data is everywhere. You probably knew that by now, since it's kind of hard to overlook it when it's constantly in the news, a growing professional field, and data skills are increasingly valuable in every job market. However, data isn't just for big businesses and you don't have to collect your own data to analyze it. There are tons of public data sets out there!

If you're looking to learn how to analyze data, create data visualizations, or just boost your data literacy skills, public data sets are a perfect place to start. Here are some great public data sets you can analyze for free right now. If you need help with putting your findings into form, we also have write-ups on data visualization blogs to follow and the best data visualization examples for inspiration.

Curated by: Google
Example data set: "Cupcake" search results

This is one of the widest and most interesting public data sets to analyze. Google's vast search engine tracks search term data to show us what people are searching for and when. You can explore statistics on search volume for almost any search term since 2004. Enter in any search term, or a handful of search terms, and click the download button to analyze the data outside of the Trends website.

There are a variety of filters to narrow down trends according to location (worldwide or by country), various time ranges, categories, or even specific search types (web vs image vs YouTube search results). You can easily see what topics are popular at the moment and what is currently trending on the Trends homepage. Google also highlights several interesting examples of trends with data visuals on that homepage.

If you're interested in more Google data, check out Google Finance, Google Public Data, and Google Scholar.

Curated by: National Centers for Environmental Information (formerly NOAA)
Example data set: Local Climatological Data (LCD)

If weather and climate science is your thing, you can't get much more detailed than the National Climatic Data Center. They've done a little rebranding, merging the National Oceanic and Atmospheric Administration (NOAA) data centers to become the National Centers for Environmental Information (NCEI).

Here you can find an archive of climate and weather data sets across the US, the largest archive of environmental data in the world. It is a huge resource for all kinds of weather data, including meteorological, oceanic, climate, atmospheric, and geophysical data.

Curated by: World Health Organization (WHO)
Example data set: Universal access to reproductive health

As part of their core goal for better health information worldwide, the World Health Organization makes their data on global health publicly available through the Global Health Observatory (GHO). The GHO acts as a portal with which to access and analyze health situations and important themes.

The various data sets are organized according to themes, such as mortality, health systems, communicable and non-communicable diseases, medicines and vaccines, health risks, and so on. The WHO's health statistics are to go-to source for global health information and is also used in the work of the US Centers for Disease Control and Prevention.

Curated by: Singaporean government
Example data set: Singapore Residents By Age Group, Ethnic Group And Gender, End June, Annual (2017)

There are actually a lot of great government data websites on the internet. Most of them are incredible wealths of data and information. The US has one of the most known at data.gov, and the UK and Australia also have great corresponding sites. With all of those, and with large population samples, we have a lot of data to access. So why Singapore?

Frankly, Singapore's government data website is just so visually accessible. The homepage is full of small visualizations telling stories about each data set. Part of data visualization is making sure that not only does it display information in an accurate and relevant format, but also that it's appealing catch interest. Most of the government data sites are utilitarian and simple, enough to get the data across in an easy to understand way. Singapore, however, brightens it up with colorful visualizations, splashes of color in the graphs, and a "Similar Datasets" section at the bottom of every data set to encourage readers to explore.

Curated by: NASA
Example data set: Atmospheric Electricity (Lightning)

Earthdata is part of NASA's Earth Science Data Systems Program, specifically the Earth Observing System Data and Information System (EOSDIS). EOSDIS acts as a means to process and distribute Earth science data from the Earth observation satellites, aircraft, and field measurements.

Via Earthdata, the public can access NASA's data, news, and event information. It covers data from Earth's atmosphere, solar radiance, the cryosphere (arctic/frozen areas), the ocean, land surface (gravity, geomagnetism, tectonics), and human environments.

Curated by: Amazon
Example data set: 1000 Genomes Project

As more organizations make their data available for public access, Amazon has created a registry to find and share those various data sets. There are over 50 public data sets supported through Amazon's registry, ranging from IRS filings to NASA satellite imagery to DNA sequencing to web crawling. The data sets also include usage examples, showing what other organizations and groups have done with the data.

Curated by: Pew Research Center
Example data set: Teens, Social Media & Technology 2018

The Pew Research Center's mission is to collect and analyze data from all over the world. They cover all sorts of topics like politics, social media, journalism, the economy, online privacy, religion, and demographic trends. While they do their own nonpartisan, non-advocacy research and analysis, they also offer their raw data for public access. Access simply requires a brief registration on the site and credit to Pew Research Center as the source of the data, with a waiver that Pew is not responsible for alternative data conclusions.

In a way, making data accessible is also another research project for Pew. They already have all the information about how they use the data in their research and they are interested in learning how others use their data as well. They have one request - to contact them by email if anything is published as a result of the data acquired.

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7 public data sets you can analyze for free right now

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Hey, data is everywhere. You probably knew that by now, since it's kind of hard to overlook it when it's constantly in the news, a growing professional field, and data skills are increasingly valuable in every job market. However, data isn't just for big businesses and you don't have to collect your own data to analyze it.

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Data.gov is the United States government's open data website. It provides access to datasets published by agencies across the federal government. Data.gov is intended to provide access to government open data to the public, achieve agency missions, drive innovation, fuel economic activity, and uphold the ideals of an open and transparent government.

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If you're looking for a job in data analytics, you'll need a portfolio to demonstrate your expertise. Of course, if you're new to data analytics, you probably don't have much expertise! Not to worry. The fact you might not have worked on a paid project yet doesn't mean you can't whip up a compelling portfolio using some practice datasets.

Fortunately, the Internet is awash with these, most of which are completely free to download (thanks to the open data initiative). In this post, we'll highlight a few first-rate repositories where you can find data on everything from business to finance, planetary science and crime.

Prepare to geek out, and here we go:

It seems we turn to Google for everything these days, and data is no exception. Launched in 2018, Google Dataset Search is like Google's standard search engine, but strictly for data. While it's not the best tool if you prefer to browse, if you have a particular topic or keyword in mind, it won't disappoint. Google Dataset Search aggregates data from external sources, providing a clear summary of what's available, a description of the data, who it's provided by, and when it was last updated. It's an excellent place to start.

Like Google Dataset Search, Kaggle offers aggregated datasets, but it's a community hub rather than a search engine. Kaggle launched in 2010 with a number of machine learning competitions, which subsequently solved problems for the likes of NASA and Ford. It has since evolved into a renowned open data platform, offering cloud-based collaboration for data scientists, as well as educational tools for teaching artificial intelligence and data analysis techniques ...plus, of course, tonnes of great datasets covering almost any topic you can imagine.

In 2015, the US Government made all its data publicly available. With over 200,000 datasets covering everything from climate change to crime, you can lose yourself in the database for hours. For a government website, it has some surprisingly user-friendly search functions, including the ability to drill down by geographical area, organization type, and file format. Search results are also clearly labeled at federal, state, county, and city levels. If you're interested in more general data about the US population, you can also check out the US Census Bureau, offering a rich selection of data about US citizens, their geography, education, and population growth.

The goal of many data analysts is to help drive savvy business decisions. As such, using economic or business datasets for your portfolio project might be worth considering. While Datahub covers a variety of topics from climate change to entertainment, it mainly focuses on areas like stock market data, property prices, inflation, and logistics. Because many of the data on the portal are updated monthly (or even daily) you'll always have something fresh to work with, as well as data that covers broad timescales.

Generalized repositories are great if you're happy to browse. But if you're seeking something more niche, why not specialize? Enter the UCI Machine Learning Repository. Launched thirty years ago by the University of California Irvine, don't let the 90s vibe mislead you-the UCI repository has a strong reputation among students, teachers, and researchers as the go-to place for machine learning data. Datasets are clearly categorized by task (i.e. classification, regression, or clustering), attribute (i.e. categorical, numerical), data type, and area of expertise. This makes it easy to find something that's suitable, whatever machine learning project you're working on.

If you think space is awesome (let's face it, space is awesome!) look no further than Earth Data. Publicly available since 1994, this repository provides access to all of NASA's satellite observation data for our little blue planet. As you can imagine, there's plenty to peruse, from weather and climate measurements to atmospheric observations, ocean temperatures, vegetation mapping, and more. If Earth-based data isn't your thing, NASA's Planetary Data System takes things a step further with data from interplanetary missions, such as the Cassini probe (which orbited Saturn from 2004 to 2017). Who knows, you might even make a scientific discovery...

Want to demonstrate your ability to work with highly complex datasets? Head to the CERN Open Data Portal. It offers access to over two petabytes of information, including datasets from the Large Hadron Collider particle accelerator. Frankly, these data aren't for the faint of heart but if you're interested in particle physics, they're worth checking out. While even the names of these datasets are pretty complex, each entry has a helpful breakdown of what's included, as well as related datasets, and how to go about analyzing them. In many cases, they even provide sample code to get you started (thanks, CERN!)

The Global Health Observation data repository is the UN WHO's gateway to health-related statistics from across the globe. If you're looking to break into the healthcare industry (a key focus for many data scientists, especially in the area of machine learning), these datasets are a good option for your portfolio. Covering everything from malaria to HIV/AIDS, antimicrobial resistance, and vaccination rates, the portal even has a nice little feature that lets you preview data tables before downloading them. Not strictly necessary, but definitely nice to have!

If you're looking for some data that are a bit more digestible, the next few should be right up your street. First off: the British Film Institute industry statistics. Throughout the year, the BFI accrues and releases data on everything from UK box office figures, to audience demographics, home entertainment, movie production costs, and more. The best part though is their annual statistical yearbook. This breaks down the year's data with some excellent statistical analysis and visual reports-great if you're new to data analytics and want to check your work against the real thing.

Type of data: Transport
Data compiled by: New York City Taxi and Limousine Commission
Access: Free, no registration required
Sample dataset: Take your pick!

This is a weirdly fascinating one...since 2009, the NYC Taxi and Limousine Commission has been accruing transport data from across New York City. Find datasets covering pick-up/drop-off times and locations, trip distances, fares, rate and payment types, passenger counts, and more. It's pretty interesting to compare the differences in figures from 2009 to the present day, especially within such a small geographic area. The site also provides some additional tools, including user guides, taxicab zone maps, data dictionaries (for explaining the spreadsheet labels), and annual industry reports. All very intuitive and quite a helpful guide if you're new to data analytics.

If you're fascinated by crime, the FBI Crime Data Explorer is the one for you. It provides a broad collection of crime statistics from a variety of state organizations (universities and local law enforcement) and government (on a local, regional, and state-level). Pull data on hate crimes, officer assaults, homicides, and more. Like the last couple of entries on our list, it also includes some helpful user guides to support data navigation. Each dataset also has some pretty nice visual breakdowns and analysis, so you can see if it has the features you're looking for before downloading it.

Next steps

If you're anything like us, you'll lose hours simply browsing these vast repositories. From the quirky to the unashamedly geeky, there's no better evidence of data's ubiquity in our lives. So what do you do once you've found your dataset and analyzed it? If you want to feature your analysis as a project in your portfolio, there are certain steps you'll need to follow-you can learn how to build your data analytics portfolio in this guide.

If you're completely new to data analytics, why not try out a free, five-day introductory short course? You'll get a hands-on introduction to the field, complete with access to a workable dataset. And, if you'd like to learn more about what it takes to forge a career in data, check out the following:

This article is part of:

Contributor to the CareerFoundry blog

A British-born writer based in Berlin, Will has spent the last 10 years writing about education and technology, and the intersection between the two. He has a borderline fanatical interest in STEM, and has been published in TES, the Daily Telegraph, SecEd magazine and more. His fiction has been short- and longlisted for over a dozen awards.

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10 Great Places To Find Open, Free Datasets [2022 Guide]

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If you're looking for a job in data analytics, you'll need a portfolio to demonstrate your expertise. Of course, if you're new to data analytics, you probably don't have much expertise! Not to worry. The fact you might not have worked on a paid project yet doesn't mean you can't whip up a compelling portfolio using some practice datasets.

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Improve math literacy in the classroom with Kelly Turner's Graph of the Week

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Data talks are short 5-10 minute classroom discussions to help students develop data literacy. This pedagogical strategy is similar in structure to a number talk, but instead of numbers students are shown a data visual and asked what interests them. In a data talk the teacher does not have to be an…

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How to spot a misleading graph - Lea Gaslowitz

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Hans Rosling: Debunking third-world myths with the best stats you've ever seen

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ATLAS Science Achievement Level Descriptors - FINAL .xlsx

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Crosscutting Concepts — The Wonder of Science

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The Wonder of Science website aggregates the work of Paul Andersen around the NGSS (Next Generation Science Standards)

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Multilingual learners are the fastest-growing population of K-12 students in the U.S. Throughout the past 6 months, Tuva has taken a number of steps to ensure multilingual learners have access to rigorous STEM instruction.

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Data Literacy Basics Crash Course (FREE COURSE)

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Tuva’s Data Literacy Fundamentals Framework