I Code Like a Girl

I Code Like a Girl

Programmers Betty Jean Jennings (left) and Fran Bilas (right) operate ENIAC's main control panel at the Moore School of Electrical Engineering. (U.S. Army photo from the archives of the ARL Technical Library)

Programmers Betty Jean Jennings (left) and Fran Bilas (right) operate ENIAC’s main control panel at the Moore School of Electrical Engineering. (U.S. Army photo from the archives of the ARL Technical Library)

The American computer industry seems dominated by people like me – males. But it was not always this way, in fact I stand on the shoulders of women.

While writing about SAGE in previous posts, I learned that at the beginning of the computer age, most programmers were women. My skills, including programming languages and tools, have a foundation built on the contributions of those who came before me. It turns out that I code like a girl, using concepts pioneered by women.

Computers: Human Women or Machine?

In the 1940’s and 50’s, there was a peak in women working as computers. Mathematically intensive industries like nuclear research, ballistics, and engineering often employed women to perform computations.

Do you remember “When Computers Were Women?” The article reminds us that a “computer” was actually a human being until around 1945. Afterward, a computer was a machine and humans were called operators.


In 1946, the first electronic general-purpose computer called ENIAC (Electronic Numerical Integrator And Computer) was built. This began a process of reducing and automating manual calculations.

A select number of women operators and former “computers” were enlisted to become programmers for ENIAC. Notably, the first ENIAC programming team was comprised entirely of women: Kay McNulty, Betty Jennings, Betty Snyder, Marlyn Wescoff, Fran Bilas, and Ruth Lichterman.

Women programmer School of Electrical Engineering. (U.S. Army photo from the archives of the ARL Technical Library)

School of Electrical Engineering. (U.S. Army photo from the archives of the ARL Technical Library)

At the time, there was a strong division between the male domain of hardware and the female sphere of software. Male electronic engineers built the ENAIC system. But since software design and programming were considered clerical work, women instructed the the 27-ton hand-built mass of wires and vacuum tubes to perform calculations in sequence.

In true programmer fashion, the women learned by doing. The hardware engineers dropped the blueprints and wiring documents on them and said, “Here figure out how the machine works and then figure out how to program it.” So the women crawled around the massive frame and learned how each component worked. They successfully understood the interplay between hardware and software and how the computer’s behavior could be traced to a hardware or a software issue.

Unfortunately, all the credit for creating ENIAC went to the men who conceived it and built the hardware. The media covered the debut of ENIAC in February 1946, which showed off the centerpiece calculation of a trajectory. The program created by Betty Snyder and Betty Jennings impressed the VIPs because it allowed the computer to calculate faster than the projectile itself. But the women were not mentioned, seen in pictures of the event, nor invited to the press lunch with the men. In the end, the computer was the star of the show, depicted as an autonomous brain.

Gender Code

Words powerfully describe gender roles. What is now considered a male-dominated field, was once defined as “women’s work.” In the days of the first computers, the norms were as follows:

Male Female
Hard sciences Soft sciences
Engineering Programming
Hardware Software

Society was keen on recognizing men’s contributions, while neglecting those of women. In the book, _Recoding Gender: Women’s Changing Participation in Computing_, Janet Abbate found that publicity materials for ENIAC state that the machine reduced 25 man-months of human computer time to two hours on the ENIAC. However, it fails to mention that most of the human computers were really women. The materials also neglect to highlight the years of labor by both men (on the hardware) and women (writing software) to create the system. The only human labor noted in the press was the initial design of the machine, which was performed by men.

But even women of the time seemed to define their computer jobs as gender specific. Elise Shutt was a programmer on a later version of ENIAC called ORDVAC. When she was hired by Raytheon in 1953, she said, “It really amazed me that these men were programmers, because I thought it was women’s work.”

In another example, Grace Hopper compared programming to tasks like sewing clothes, making a recipe, and the work of a mother teaching a child. Thus, she defined programming as a female occupation. But this seems to have been lost on her supervisor, Howard Aiken who said in praise of Grace, “Grace was a good man.

Recruiting materials were also used to attract women to programming with various metaphors and generalizations. In the 1940s, MIT had a shortage of men and highlighted skills such as needlework and knitting as characteristics useful for programmers. Others noted that female pursuits like crosswords and puzzles would make good programmers.


The first women who pioneered programming on the ENIAC finally gained the recognition they deserved in 1997 when they were inducted into the Women in Technology Hall of Fame in 1997 and IEEE in 1997 and 2008.

It seems that we continue to struggle with metaphors and defining skills used to train and attract the next generation to computer work. From recent statistics, we are finding a wider gender gap in the computer industry. The reasons for this are inconclusive and give us a reason for self-evaluation and consideration of language used to hire and promote, treatment of women, and how skills are evaluated.

It becomes increasingly important to value each member of a programming team regardless of gender, age, race, or creed to attract and keep the best minds to build our future software. There seems to be no end to the amount of programming work needed. Code on!


Check out more of our work at Volume Integration and follow us on Twitter.


10+ Surprising Geospatial Technologies

Data Organized on Map

I’ve spent years in the geospatial arena, so I’m a bit of a geospatial technology geek. But now it seems like the rest of the world is increasingly interested in this technology too.

You may remember the old latitude and longitude numbers that you learned about in school. Perhaps they didn’t seem very useful or relevant to life at the time, but these coordinates are now tracked constantly with our various GPS enabled gadgets. It’s becoming increasingly common to use coordinates to define the location of data collected, a person, landmark, and more. We can add even further accuracy by recording elevation and point in time.

I would like to describe some of the components that fall under the umbrella of geospatial technology. You might find some surprises!


First, let’s discuss some of the tools used to collect geospatial data.

1. GPS

Global Positioning System (GPS) technology is the software and equipment needed to provide the location of things on the planet. This is most often done with the use of special satellites but is often augmented by other methods like WiFi signals. There are even technologies in use that determine location by looking at the stars.

2. Field Sensors

Field sensors are electronic devices that are placed to collect information about weather, soil, or other environmental conditions. These data collecting devices could be anything from a camera to a cell phone. During collection, the data is tagged with geospatial information, so the location of the event is known and can be mapped.

Overhead Imagery

My next geospatial category is overhead imagery. This includes all the imagery from aircrafts and satellites.

3. Visual Overhead Imagery

Visual overhead imagery includes what you see in Google Maps and Google Earth when you use the satellite function. This imagery could be collected via satellite or aircraft, and the technology used involves cameras, aircraft, satellites, global positioning systems, altimeters, and microwave transmission equipment. Today, even video is collected overhead by Planet Labs.

If you don’t own an airplane or satellite, can you collect visual overhead imagery? Yes! It doesn’t have to be expensive. Some hobbyists and students are cutting their teeth on low-cost imagery collection using kites and balloons.

Balloon mapping of Lake Borgne, Louisiana (Cartographer: Stewart Long/

4. Hyperspectral Overhead Imagery

Hyperspectral refers to the waves of light that are beyond human sight. Engineers have developed sensors that can gather these waves from space, but it can also be done from aircraft. The data is then transformed into a visual representation through analysis and processing to create hyperspectral overhead imagery.

This type of geospatial technology has some surprising uses. Over at the US Geological Survey (USGS), they have used hyperspectral overhead imagery collected via satellite to detect the presence of arsenic in the leaves of ferns. Further analysis led them to aid in locating arsine gas canisters buried in Washington, DC. For more information, check out the full dissertation entitled _Remote Sensing Investigations of Furgative Soil Arsenic and its Effects on Vegetation Reflectance_.


Light Detection and Ranging (LIDAR) is a technology that uses an airborne system to measure distance by shining a laser to the ground and measuring the reflected light. This yields a very accurate contour of the earth’s surface as shown in the image of the Three Sisters below.

LIDAR image of the Three Sisters volcanic peaks in Oregon (DOGAMI)

LIDAR can also measure objects on the ground such as trees and houses. This type of data is used to determine elevation and is often used when processing other imagery to improve accuracy.

How do autonomous vehicles “see” where they are going and what is in the way? LIDAR, of course! Plus, it’s even used in various industries to make 3D models of buildings and topography.


So now that we collected all this imagery, how do we use it?

6. Imagery Processing Systems

The overhead imagery produced from satellites and aircraft is not perfect for human viewing in raw form. So we use imagery processing systems to help automate the manipulation of images and data collected. This collection of computer systems makes the images and data useful to us.

Most images are taken from an angle and must be adjusted or warped. Imagery processing systems assign each pixel a geographic coordinate and an elevation. This is done by combining GPS data that was collected with each click of the camera.

Often this process is called orthorectification. To see a simplified illustration, take a look at this orthorectification animation from Satellite Imaging Corporation.

7. Geospatial Mapping

Geospatial mapping is the process and technology involved in placing information on a map. It is often the final stage of geospatial processing.

Mapping combines data from many sources and layers it onto a map, so conclusions can be drawn about the data. There are different degrees of accuracy required in this process. For some applications, showing data in an approximate relation to each other is sufficient. But other applications, like construction and military exercises, require specialized software and equipment to be as precise as possible.

In an earlier post, I wrote about creating maps with D3. The goal was to build a heat map to display the count of documents for each place name as shown in the image below.

Data Organized on Map


Let’s explore the some of the applications of all this geospatial technology.

8. Geospatial Marketing

Geospatial marketing is the concept of using geospatial tools and the collection of location information to improve marketing to customers. This is often a subset of geospatial mapping, but this application combines data about customers’ locations. This can help determine where to place a store or how many customers purchase from a particular location. For example, companies can use data about where people typically go after a ballgame to determine where advertisements should be placed.

Another widespread application of geospatial data in marketing is using the IP addresses gained from customers browsing websites and viewing advertisements. These IP addresses can be geographically located, sometimes as specifically as a person’s house, and then used to target advertisements or redesign a website.

9. Location-Aware Applications

Location-aware applications are a category of technologies that are cognizant of their location and provide feedback based that location. In fact, if an IP address can be tied to a location, almost any application can be location-aware.

With the advent of smart phones, location-aware applications have become even more common. Of course, your phone’s mapping application can display your location on a map.

There are also smartphone apps that will trigger events or actions on a phone when you cross into a geospatial area. Some examples are Geofencer and PhoneWeaver.

Additionally, the cameras on smart phones can collect the location of the phone when taking a picture. This is imbedded within the picture and can be used by Facebook, Picasa, Photoshop, and other photo software to display locale information on a map. (You may want to disable this feature if you would rather not have people know where you live.)

10. Internet of Things

The Internet of Things (IoT) is the category of technology that includes electronic objects that connect to the internet and transmit their location. This is a broad and emerging area of geospatial technology that will add even more location data to the world.

IoT could contain objects like cars, fire alarms, energy savings devices like Nest and Neurio, fitness tracking bands like the ones from Jawbone or Nike, and more. For these IoT applications and devices to work optimally, they need to know your location and combine it with other information sensed around them.

Nike+ FuelBand (Peter Parkes/

11. Geospatial Virtual Reality

Virtual reality that makes use of geospatial data is another emerging category. This technology will allow for an immersive experience in realistic geospatial models.

Geospatial virtual reality incorporates all of the technologies listed above to put people into the middle of simulated real-word environments. It’s already been implemented with new hardware like the Oculus Rift, which is a virtual reality headset that enables players to step inside their favorite games and virtual worlds.

Oculus Rift (Sebastian Stabinger/

Show Me the Data!

At the base of all of this technology is data. Increasingly, we have to invent more ways to store geospatial data in order for it to be processed and analyzed. The next steps of geospatial technologies involve attaching geospatial information to all data collection and then processing and filtering the massive amounts of data, which is known as big data.

This is my list of surprising geospatial technologies that matter today. It started out as a top 10 list, but evolved to 11 because I just couldn’t leave out geospatial virtual reality. It’s so cool! Feel free to add your suggestions of geospatial technologies in the comments below or as a pingback.