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Wolfram|Alpha has a massive database of measurements that can help you solve everything from complex scientific conversions to common everyday questions. And because of the ever-connected world we live in today, we often come into contact with systems of measurement that may be unfamiliar to us.
Wolfram|Alpha.com has always been a great source for quick and easy unit conversions. But now, thanks to the newly announced Wolfram|Alpha Widgets and Widget Builder, you can create and share these Wolfram|Alpha-powered mini-apps on your blogs and with your social networks. Below is a sampling of the handy widgets that users have created in recent days—for everything from kitchen conversions to shoe sizes.
Give yourself, and perhaps readers of your cooking blog, a helping hand in the kitchen with this easy-as-pie kitchen conversion widget. This particular widget was designed to convert American units of measure. However, you can customize your own widget for other systems of measurement in just a few easy steps with the drag-and-drop Widget Builder.
Have you ever found yourself needing to convert currency when budgeting for an upcoming international trip? This simple widget allows you to convert currencies and take into account possible fees and commissions you may incur when buying or selling moneys.
Do you need a fast way to compute the distance between two physical locations in your preferred units of measurement?
Wondering whether you just awoke a friend several time zones away with a text message? Wolfram|Alpha can also perform a variety of time conversions. With this widget you can simply enter the location, such as “Dubai”, and Wolfram|Alpha will display the time difference between Dubai and your location in several different ways along with other details about the current time in Dubai.
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Wolfram|Alpha launched with an extensive database of United States economic data, derived from the Federal Reserve Bank’s FRED database. Over the past year, we’ve continued to improve our handling of this data in a variety of ways—teaching Wolfram|Alpha to return more related statistics along with any specific result, improving our linguistic abilities so we can answer more complex questions, and increasing the frequency with which we update this data. Wolfram|Alpha is now refreshing its collection of FRED-derived data on a daily basis, so you can always access the latest available data on the national economy.
We’ve also begun to expand our coverage of economic data for smaller geographic areas in the United States, starting with state-level statistics. This means Wolfram|Alpha users can now query for the latest available information on a variety of economic topics, including gross state product, unemployment, health insurance coverage, and housing-related data.
As always, one of the strengths of Wolfram|Alpha is that it allows you to compare and analyze different pieces of data—and with this data set, you can quickly uncover strong correlations between various economic properties. It’s easy to see that the house price index tends to move together with employment and state tax collections. You can also use Wolfram|Alpha to run simple calculations of productivity in U.S. states, or to find out a given state’s share of the national economy or workforce.
To make it even easier to explore this data, you can also use the new Wolfram|Alpha Widget Builder to create simple tools for analyzing and comparing the economic properties of states. To get you started, here’s a small selection of widgets focused on US state economies—ranging from the serious to the slightly silly. Try them out:
Feel free to customize and share these on Twitter or Facebook, in your blog, or anywhere else—and let us know in the comments if you create any useful new widgets of your own.
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The beta version of Wolfram|Alpha Widgets is here! What are Wolfram|Alpha Widgets? They’re free, Wolfram|Alpha-powered mini apps that are easy to make, customize, and share on your blog, website, and social networks. And they’re the next step toward our goal of making the vast knowledge and computational power of Wolfram|Alpha available to everyone, everywhere.
Widgets are a new and personal way to experience Wolfram|Alpha. Want to have an Wolfram|Alpha-powered app on your blog that calculates the adult height and weight of a child based on his or her current stats? Or how about an app that compares the financial data of two public companies? Want to create a customized nutritional label for any recipe you have? Calculate integrals on the fly? Or locate an object in the sky? The possibilities are limitless. For more examples of widgets, see the hundreds already in the Widget Gallery. You can freely take any of these widgets and put them on your own site as is or customize them any way you wish.
Don’t see an existing widget for your area of interest? Using the new drag-and drop Widget Builder, you can create your own widget using anything in Wolfram|Alpha’s vast knowledge base in just a few easy steps. Once you’ve built and customized your widget, it will automatically be added to the widget gallery where you can share it with others.
We fully expect to be blown away by all of the cool and innovative ways you harness the power of Wolfram|Alpha widgets. Here are just a few ways we want to help you share your use of widgets with the world!
- Once you’ve published your widget in the widget gallery, share the link with your social networks and ask to have your widget rated. Your widget will be rocking the ratings charts in no time.
- Show how you’re using widgets on your blog by sharing a link to your blog on Twitter. Be sure to include the hashtag #WolframAlphaWidget. Oh, and be sure to follow @Wolfram_Alpha!
- Post a link to your widget and/or blog on the the wall of the Wolfram|Alpha Facebook group, and ask your friends to “Like” it!
We’ll select the most interesting uses of widgets and highlight them on the Wolfram|Alpha Blog, in the Wolfram|Alpha Community, on Twitter, and on Facebook.
So, what will you widget? Click here to get started.
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Runners and cyclists can now get personalized physical activity and fitness results from Wolfram|Alpha. Our team has added enhanced activity formulas to provide specific results that account for the individual differences among all types of runners and cyclists. Whether preparing for a race or monitoring regular routines, athletes and enthusiasts alike can now calculate actual performance results and compute performance predictions and the impact of exercise on personal physical fitness.
You can calculate your own results in Wolfram|Alpha by using a natural language input such as “cycling 72.13 miles for 240 minutes” or you can type in “cycling” to explore all of the formula’s options. For example, a cyclist who is preparing for, or who has just completed, a race can calculate a variety of user-specific metabolic properties, like the amount of fat and the number of calories burned, by taking into account factors such as age, gender, height, weight, incline, resting heart rate, and wind speed and direction. Below are sample results from Wolfram|Alpha when calculating the speed a 25-year-old male cyclist needs to maintain to complete a race in 240 minutes:
To complement the results of Wolfram|Alpha’s calculations, cyclists can compare their speed or pace with world record times by clicking the “Show comparisons” link.
Runners can input similar information and calculate calories and fat burned; oxygen consumed; heart rate; equivalent activities; conversions for speed, pace, distance, and time; and performance predictions. For this example, we convinced a member of our team to share his post-race results from the 2009 Chicago Marathon: More »
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At the recent London Computational Knowledge Summit, Wolfram|Alpha content manager C. Alan Joyce gave attendees an insider’s look into Wolfram|Alpha. He shared how Wolfram|Alpha’s teams of Mathematica programmers, knowledge-domain experts, and data and linguistics curators have been able to transform raw data from public and private sources into “computable knowledge” that can be accessed and manipulated through natural-language input. Click the image below to view the video of his presentation:
Video by River Valley Technologies
Data acquisition, data curation, linguistics curation, and dynamic visualization are four of Wolfram|Alpha’s key focus areas. Which of those is most fascinating to you?
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A new medical diagnosis or drug treatment can often leave us with more questions than answers. A few weeks ago we introduced a disease dataset within Wolfram|Alpha that can be helpful for those wondering how their condition and treatment plans compare to those of other patients. Most notably, this dataset includes the fraction of patients within the United States that have been diagnosed with a medical condition in a given year. For each condition, Wolfram|Alpha has various levels of information, including commonly reported symptoms, co-occurring diseases, and lab tests used for diagnosis. Beyond this, Wolfram|Alpha also has carefully curated data on drug treatments. For example:
The data displayed from these inputs gives classes of drugs prescribed or administered to patients during health care provider visits. Wolfram|Alpha ranks the drug classes by the number of patients to whom they were administered. For example, “hypertension drug treatment”, initially shows us that, of all the patients diagnosed with hypertension, 25% were prescribed angiotensin converting enzyme inhibitors, 22% HMG-CoA reductase inhibitors, 21% cardioselective beta blockers, 19% antihypertensive combinations, and 16% calcium channel blocking agents. (That’s over 100% total because some patients are prescribed more than one medication.)
Looking above the ranked drug table we can see that there are a handful of useful options. Click “Show drugs”, and the table opens up and displays a ranked table of brand-name drugs prescribed within each class. From this table, you can see interesting differences in drug-prescribing patterns between the sexes. For example, the angiotensin converting enzyme inhibitor Lisinopril is more commonly prescribed to male hypertension patients than females, but looking further down the list, we can see that female patients are more commonly prescribed Enalapril than are males.
Wolfram|Alpha can also can also provide generic options for prescription drug treatments. More »
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The U.S. Department of Health and Human Services recommends that adults engage in at least 2.5 hours of moderate aerobic physical activity each week. Recommendations for children age 6 to 17 are even higher: at least 1 hour of moderate or vigorous activity each day.
Yet according to the CDC, only one-third of American adults regularly engage in some kind of physical activity, and the prevalence of childhood obesity has more than tripled in the past three decades—to nearly 20% among children age 6 to 19. The warm and sunny days of summer provide an excellent opportunity to try new outdoor activities, or spend more time engaged in old favorites. Wolfram|Alpha can perform useful computations for many popular summer water sports, including fishing, water skiing, and sailing. By adding time and/or body weight to these inputs, you can tailor the calculations to your own physical measurements and activity schedule:
- fishing for three hours »
- fat burned water skiing if I weigh 175 lbs »
- calories burned sailing for 45 minutes »
For queries about activities such as swimming and rowing, you can now incorporate other variables about speed and pace, along with age and physical measurements:
- rowing 50 m/min »
- going for a swim at 4 mph »
- rowing for 35 minutes at 4 meter/min 150 lbs male »
- swimming 9 min/mile for 30 minutes 25 years old »
In addition to basic information about calories and fat burned, the amount of oxygen consumed, and the metabolic equivalents required for the activity, Wolfram|Alpha also computes estimates of working heart rate and heart rate reserve.
Below the “Heart rate pod”, Wolfram|Alpha generates an “Equivalent activities” pod that displays the amount of time it would take to expend the same amount of energy performing other activities. Within the “Speed” and “Pace” pods that follow, you can click “Show comparisons” to see how your predicted performance measures up against various world records. Below the “Pace” pod, there are “Distance” and “Time” pods followed by the “Performance prediction” pod. Using Riegel’s endurance model, this pod displays the predicted time, speed, and pace over standard swimming race distances. More »
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This Sunday, July 11, is World Population Day—an event established in 1989 by the United Nations to raise awareness of global population issues. This year, the emphasis is on the 2010 World Population and Housing Census Programme and the importance of collecting, analyzing, and disseminating data in a way that supports good health and social policy development.
In the past few months, we’ve added a variety of international data sets to Wolfram|Alpha, such as data on food consumption and worldwide health indicators. But Wolfram|Alpha launched with an enormous collection of global socioeconomic data, much of it from the UN and other authoritative repositories of international statistics, and we’ve continued to expand and curate that collection.
As we’ve said before, we’re committed to “democratizing data”—to making it easier for everyone to access and understand the wealth of important data produced by a multitude of sources. For good examples of our own ability to analyze and disseminate relevant socioeconomic data, try some of the following queries pertaining to topics from past and present World Population Days:
- All countries’ population in 1900 »
- All countries’ population in 2050 »
- Poverty in all countries »
- Female literacy in all countries »
- Life expectancy in all countries »
We’ll soon be introducing some new functionality that will give “power users” the ability to do more advanced analysis and comparison of properties between groups of countries, and in other knowledge domains. And as always, if you’d like to see additional data in Wolfram|Alpha, please send us your suggestions.
PS: If you’re interested in the absolute latest information on world population, try asking Wolfram|Alpha for the current world population. Reload that page in your browser a few times and see how fast that number is going up!
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As a scientist and a technology CEO, Stephen Wolfram often thinks about the future—both near-term and long-term. On June 12 he gave an unusual keynote talk at the 2010 H+ Summit @ Harvard, titled “Computation and the Future of the Human Condition”.
Check out the transcript to find Stephen’s latest thoughts on our future…
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Sunday is the United States’ Independence Day, and one of the hottest days of the year in this part of the country. Many Americans will celebrate the day with outdoor activities such as barbecues, parades, and fireworks. Chances are that after all the corn on the cob and fun in the sun, they’ll be looking to celebrate with some air conditioning, too! All that cooling will require a few degree days!
What’s a degree day? A degree day quantifies the amount of heating or cooling required to heat or cool an inside space.
Suppose you want to maintain an inside temperature of 65°F. This 65°F is called the base temperature. (65°F might sound cool, but this artificially low number is used because the actual temperature in the building will be raised by bodies and other inside sources of heat.) If the weather forecast for Champaign is as hot as expected for U.S. Independence Day—definitely above 65°F—then you’ll need to cool the building. The amount of cooling required is the difference between the base temperature and the outdoor temperature, multiplied by the time over which the temperature is different. If it is cooler outside than 65°F then you’ll need to heat the building, again by an amount equal to the product of the temperature difference and the time.
To make sense out of that, just type “degree days” into Wolfram|Alpha.
The temperature history pod contains a plot of the temperature over the time period of the calculation—one month back by default. If you are used to using Wolfram|Alpha to check the weather this plot should look familiar, but with some differences. The horizontal red line across the plot is the base temperature. The part of the plot that is above the red line is shaded in blue. That’s because when the temperature is above the base temperature, you have to cool the building. The number of cooling degree days is the area of the blue region. Similarly, the number of heating degree days is the area of the red region, which extends from the red baseline down to temperatures below the base temperature. More »