A female engineer working on an optical communications system test.
Women
are often under-represented in the academic and professional fields of
engineering; however, many women have contributed to the diverse fields
of engineering historically and currently. A number of organizations and programs have been created to understand
and overcome this tradition of gender disparity. Some have decried this
gender gap, saying that it indicates the absence of potential talent. Though the gender gap as a whole is narrowing, there is still a growing
gap with minority women compared to their white counterparts. Gender stereotypes, low rates of female engineering students, and
engineering culture are factors that contribute to the current situation
where men dominate in fields relating to engineering sciences.
The history of women as designers and builders of machines and
structures predates the development of engineering as a profession.
Prior to the creation of the term "engineer"
in the 14th century, women had contributed to the technological
advancement of societies around the globe. By the 19th century, women
who participated in engineering work often had academic training in
mathematics or science. Ada Lovelace was privately schooled in mathematics before beginning her collaboration with Charles Babbage on his analytical engine
that would earn her the designation of the "first computer programmer."
In the early years of the 20th century, greater numbers of women began
to be admitted to engineering programs, but they were generally looked
upon as anomalies by the men in their departments.
A 1953 Society of Women Engineers board meeting.
The first University to award an engineering's bachelor's degree for women was University of California, Berkeley. Elizabeth Bragg was the recipient of a bachelor's degree in civil engineering in 1876, becoming the first female engineer in the United States. Prior to the 19th century, it was very rare for women to earn
bachelor's degree in any field because they did not have the opportunity
to enroll in universities due to gender disparities. Some universities
started to admit women to their colleges by the early 1800s and by the
mid-1800s they started to admit them into all academic programs
including engineering.
In the United States, the entry into World War II
created a serious shortage of engineering talent, as men were drafted
into the armed forces. To address the shortage, initiatives like General Electric on-the-job engineering training for women with degrees in mathematics and physics and the Curtiss-Wright Engineering Program among others created new opportunities for women in engineering. Curtiss-Wright partnered with Cornell, Penn State, Purdue, the University of Minnesota, the University of Texas, Rensselaer Polytechnic Institute and Iowa State University to create an engineering curriculum that lasted ten months and focused primarily on aircraft design and production.
During this time, there were few public attacks on female
engineers. Chiefly, these attacks were kept quiet inside institutions
due to the fact that women did not pressure aggressively to shift the gender gap
between men and women in the engineering field. Another reason why
these “attacks” were kept private is due to how men believed that it was
impossible for engineering to stop being a male-dominated field.
Women's roles in the workforce, specifically in engineering
fields, changed greatly during the Post–World War II period. As women
started to marry at later ages, have fewer children, divorce more
frequently and stopped depending on male breadwinners
for economic support, they started to become even more active in the
engineering labor force despite the fact that their salaries were less
than men's.
Women also played a crucial role in programming the ENIAC from its construction during the World War II
period through the next several decades. Originally recruited by the
Army in 1943, female ENIAC programmers made considerable advancements in
programming techniques, such as the invention of breakpoints, now a standard debugging tool.
In addition to the wartime shortage of engineers, the number of
women in engineering fields grew due to the gradual increase of public
universities admitting female students. For example, Georgia Tech began to admit women engineering students in 1952, while the École Polytechnique in Paris, a premier French engineering institution, began to admit female students in 1972.
As a result, gender stereotypical roles have changed due to industrialization resolution.
Factors contributing to lower female participation
Gender stereotypes
Stereotype threat may contribute to the under-representation of women in engineering. Because engineering is a traditionally male-dominated field, women may
be less confident about their abilities, even when performing equally. At a young age, girls typically do not express the same level of interest in engineering as boys, possibly due in part to gender stereotypes. There is also significant evidence of the remaining presence of implicit bias against female engineers, due to the belief that men are mathematically superior and better suited to engineering jobs. The Implicit Association Test (IAT) shows that people subconsciously
connect men with science and women with art, according to the results
from over half a million people around the world between 1998 and 2010.
This unconscious stereotype also has negative impact on the performance
for women. Women who persist are able to overcome these difficulties, enabling
them to find fulfilling and rewarding experiences in the engineering
profession.
Due to this gender bias,
women's choice in entering an engineering field for college is also
highly correlated to the background and exposure they have had with mathematics
and other science courses during high school. Most women that do choose
to study engineering regard themselves as better at these types of
courses and as a result, they are capable of studying in a
male-dominated field.
Women's self-efficacy is also a contributor to the gender stereotype
that plays a role in the underrepresentation of women in engineering.
Women's ability to think that they can be successful and perform well is
correlated to the choices they make when choosing a college career.
Women that show high self-efficacy personalities are more likely to
choose to study in the engineering field. Self-efficacy is also
correlated to gender roles because men often present higher
self-efficacy than women, which can also be why when choosing a major
most women opt to not choose the engineering major.
Lower rates of female students in engineering degree programs
Over
the past few years, 40% of women have left the engineering field. There
are many factors leading to this, such as being judged about going into
a difficult major such as engineering, or working in difficult
workplace conditions. According to the Society of Women Engineers one in four females leave the field after a certain age.
Women are under-represented in engineering education programs as in the workforce (see Statistics).
Enrollment and graduation rates of women in post-secondary engineering
programs are very important determinants of how many women go on to
become engineers. Because undergraduate degrees are acknowledged as the
"latest point of standard entry into scientific fields", the
under-representation of women in undergraduate programs contributes
directly to under-representation in scientific fields. Additionally, in the United States, women who hold degrees in science,
technology, and engineering fields are less likely than their male
counterparts to have jobs in those fields.
This degree disparity varies across engineering disciplines.
Women tend to be more interested in the engineering disciplines that
have societal and humane developments, such as agricultural and environmental engineering. They are therefore well-represented in environmental and biomedical engineering
degree programs, receiving 40-50% of awarded degrees in the U.S.
(2017–18), and are far less likely to receive degrees in fields like mechanical, electrical and computer engineering.
A study by the Harvard Business Review
discussed the reasons why the rate of women in the engineering field is
still low. The study discovered that rates of female students in
engineering programs are continuous because of the collaboration aspects
in the field. The results of the study chiefly determined how women are
treated differently in group works in which there are more male than
female members and how male members “excluded women from the real
engineering work”. Aside from this, women in this study also described
how professors treated female students differently “just because they
were women”.[18]
Despite the fact that fewer women enroll in engineering programs
across the nation, the representation of women in STEM-based careers can
increase when college and university administrators work on
implementing mentoring programs and work-life policies for women.
Research shows that these rates are difficult to increase since women
are judged as less competent than men to perform supposedly “masculine
jobs”.
Engineering culture
Autodidact computer chip designer and inventor, Jeri Ellsworth, at the Bay Area "Maker Faire" in 2009.
Another
possible reason for lower female participation in engineering fields is
the prevalence of values associated with the male gender role in workplace culture. For example, some women in engineering have found it difficult to
re-enter the workforce after a period of absence. Because men are less
likely to take time off to raise a family, this disproportionately
affects women.
Men are also associated with taking leadership roles in the
workplace. By holding a position of power over women, they may create an
uncomfortable environment for them. For example, women may receive
lower pay, more responsibilities, or less appreciation as compared to
men. However, women may have more potential to become good leaders:
studies have indicated that women have more key leadership skills; for
example, the ability to motivate employees, build relationships, and
take initiative.
Communication
is also a contributing factor to the divide between men and women in
the workplace. Male-to-male communication is said to be more direct, but when men explain a task to a women, they tend to talk down, or “dumb down” terms. This comes from the stereotype
that men are more qualified than women, and can cause men to treat
women as inferiors instead of equals. Other typically masculine traits,
such as workplace sexual harassment and creating a hostile work
environment also certainly contribute to this atmosphere of domineering
attitudes towards women.
Part of the male dominance
in the engineering field is explained by their perception towards
engineering itself. A study in 1964 found that both women and men
believed that engineering was masculine in nature.
Over the past several decades, women's representation in the workforce in STEM
fields, specifically engineering, has slowly improved. In 1960, women
made up around 1% of all engineers, and by the year 2000, women made up
11% of all engineers, for an increase of 0.25 percentage points per
year. At this rate, one would not expect 50-50 gender parity in
engineering to occur until the year 2156.
Several colleges and universities nationwide are attempting to decrease the gender gap
between men and women in the engineering field by recruiting more women
into their programs. Their strategies include increasing women's
exposure to STEM courses during high school, planting the idea of a
positive outlook on female participation from the engineering culture,
and producing a more female-friendly environment inside and outside the
classroom. These strategies have helped institutions encourage more
women to enroll in engineering programs as well as other STEM-based majors. For universities to encourage women to enroll in their graduate programs,
institutions have to emphasize the importance of recruiting women,
emphasize the importance of STEM education at the undergraduate level,
offer financial aid, and develop more efficient methods for recruiting
women to their programs.
Statistics
Percentage of female undergraduate students with engineering degree in India, Australia, Canada, the UK, and US
In 2014, there were 7.9% female freshmen among all first-year
students planning to study in STEM (science, technology, engineering,
and mathematics) related majors. In comparison, 26.9% male freshmen
intended to major in STEM. For female students who chose engineering,
over 32% decided to switch to a different major.
Since 1997, the percentage of Asian females enrolling in
engineering majors has risen from about 30% to 34% but somehow also
dropped in 2002. African American females have increased their
representation in engineering from 21% to 33% in the same time frame.
Mexican American and Puerto Rican females have had an increase in their
representation from 25% to 31%. Even if ethnicities are included in
these statistics, men from all ethnicities still outnumber the
proportion of women who enroll in engineering bachelor programs.
The percentage of master's degrees awarded to women has not changed much from 2003 (22.3%) to 2012 (23.1%). The percentage of doctoral degrees awarded to women in engineering increased from 11.6% in 1995, to 17.4% in 2004, to 21.1% in 2008, then to 22.2% in 2012.
There is a significant drop-off rate regarding the number of
women who earn a bachelor's degree and the women who afterward enroll in
graduate school. Over the last 35 years, women have been more likely
than men to enroll in graduate school right after receiving their
bachelor's degree. Women who do not enroll in a graduate program right
after earning their bachelor's degree tend to be caregivers who face
work-family conflicts in the context of family women. The workforce remains the area of lowest representation for women. There
were 13% female engineers in 2016. Usually, the salary of female
engineers is 10% less than male engineers. The retention of female engineers is also disproportionally low; in
2006, 62.6% of qualified male engineers were employed in engineering
professions, as opposed to 47.1% of qualified female engineers.
Female engineering students in class
Canada
Though women tend to make up more than half of the undergraduate population in Canada, the number of women in engineering is disproportionately low. In 2017, 21.8% of undergraduate engineering students were women, and
20.6% of undergraduate engineering degrees were awarded to women. The enrollment of women in engineering climbed from 16% in 1991 to over 20% in 2001, but by 2009 this number had fallen to 17%. One commentator attributed this drop to a number of factors, such as
the failure of higher education programs to explain how engineering can
improve others' lives, a lack of awareness of what engineers do, lack of
networking opportunities and discomfort of being in a male-dominated
environment and the perception that women must adapt to fit in.
In the 1990s, undergraduate enrollment of women in engineering fluctuated from 17% to 18%, while in 2001, it rose to 20.6%. In 2010, 17.7% of students in undergraduate engineering were women.
2016 percentage of women enrolled in tertiary education programs in Canada
In 2017, the disciplines with the highest proportion of undergraduates who are women were environmental, biosystems, and geological engineering. Four out of the five disciplines with the largest percentages of
undergraduate who are women were also the disciplines with the fewest
overall undergraduate students enrolled. The lowest proportion of women
were found in mechanical (14.2%), software (14.6%), and computer
engineering (14.8%).
The number of women enrolled in undergraduate, graduate, and
doctoral engineering programs tends to vary by province, with the
proportion in Newfoundland and Labrador, Prince Edward Island, and
Alberta.
CCWE1992 goals for 1997 and actual 2009 percentage of women involved in engineering in Canada
Women in...
1997
2009
1st year undergraduate
25-25%
Undergraduate programs
17.4%
Master's studies
20%
24.1%
Doctoral studies
10%
22%
Faculty members: professors
5%
Full: 7% Associate: 11% Assistant: 18%
Eng. degree graduates
18%
17.6%
Profession
10.4%
In 2011, the INWES (International Network of Women Engineers and Scientists)
Education and Research Institute (ERI) held a national workshop,
Canadian Committee of Women in Engineering (CCWE+20), to determine ways
of increasing the number of women in the engineering field in Canada. CCWE+20 identified a goal of increasing women's interest in engineering
by 2.6% by 2016 to a total of 25% through more incentives such as
through collaboration and special projects. The workshop identifies early education as one of the main barriers in
addition to other factors, such as: "the popular culture of their
generation, the guidance they receive on course selection in high school
and the extent to which their parents, teachers, and counsellors
recognize engineering as an appropriate and legitimate career choice for
women." The workshop report compares enrollment, teaching, and professional
statistics from the goals identified in 1997 compared to the actual data
from 2009, outlining areas of improvement (see table, right).
United Kingdom
According to the Women's Engineering Society's
statistics document, 12.37% of engineers in the UK are female in 2018.
25.4% of females from 16 to 18 years old plan to have a career in the
engineering field, compared to 51.9% of males from the same age group.
The Royal Academy of Engineering
reported in 2020 that the gender pay gap in the engineering profession
is smaller than the average for all UK employment. The mean (10.8%) and
median (11.4%) pay gap for engineers in the sample analysed is around
two thirds the national average. In 2017, the average salary for female engineers across all engineering
fields was £38,109, whereas the average salary for male engineers
across all fields was £48,866. The industry average salary is £48,000
https://en.wikipedia.org/wiki/DataThese
are some of the different types of data: Geographical, Cultural,
Scientific, Financial, Statistical, Meteorological, Natural, Transport
Data (/ˈdeɪtə/DAY-tə, US also /ˈdætə/DAT-ə) are a collection of discrete or continuous values that convey information, describing the quantity, quality, fact, statistics, other basic units of meaning, or simply sequences of symbols that may be further interpreted formally. A datum is an individual value in a collection of data. Data are usually organized into structures such as tables that provide additional context and meaning, and may themselves be used as data in larger structures. Data may be used as variables in a computational process. Data may represent abstract ideas or concrete measurements. Data are commonly used in scientific research, economics, and virtually every other form of human organizational activity. Examples of data sets include price indices (such as the consumer price index), unemployment rates, literacy rates, and census data. In this context, data represent the raw facts and figures from which useful information can be extracted.
Data can be seen as the smallest units of factual information
that can be used as a basis for calculation, reasoning, or discussion.
Data can range from abstract ideas to concrete measurements, including,
but not limited to, statistics. Thematically connected data presented in some relevant context can be viewed as information. Contextually connected pieces of information can then be described as data insights or intelligence.
The stock of insights and intelligence that accumulate over time
resulting from the synthesis of data into information, can then be
described as knowledge. Data has been described as "the new oil of the digital economy". Data, as a general concept, refers to the fact that some existing information or knowledge is represented or coded in some form suitable for better usage or processing.
Advances in computing technologies have led to the advent of big data,
which usually refers to very large quantities of data, usually at the
petabyte scale. Using traditional data analysis methods and computing,
working with such large (and growing) datasets is difficult, even
impossible. (Theoretically speaking, infinite data would yield infinite
information, which would render extracting insights or intelligence
impossible.) In response, the relatively new field of data science uses machine learning (and other artificial intelligence) methods that allow for efficient applications of analytic methods to big data.
The Latin word data is the plural of datum, "(thing) given," and the neuter past participle of dare, "to give". The first English use of the word "data" is from the 1640s. The word
"data" was first used to mean "transmissible and storable computer
information" in 1946. The expression "data processing" was first used in
1954.
When "data" is used more generally as a synonym for "information", it is treated as a mass noun in singular form. This usage is common in everyday language and in technical and scientific fields such as software development and computer science. One example of this usage is the term "big data".
When used more specifically to refer to the processing and analysis of
sets of data, the term retains its plural form. This usage is common in
the natural sciences, life sciences, social sciences, software
development and computer science, and grew in popularity in the 20th and
21st centuries. Some style guides do not recognize the different
meanings of the term and simply recommend the form that best suits the
target audience of the guide. For example, APA style as of the 7th edition requires "data" to be treated as a plural form.
Data, information, knowledge, and wisdom
are closely related concepts, but each has its role concerning the
other, and each term has its meaning. According to a common view, data
is collected and analyzed; data only becomes information suitable for
making decisions once it has been analyzed in some fashion. One can say that the extent to which a set of data is informative to
someone depends on the extent to which it is unexpected by that person.
The amount of information contained in a data stream may be
characterized by its Shannon entropy.
Knowledge
is the awareness of its environment that some entity possesses, whereas
data merely communicates that knowledge. For example, the entry in a
database specifying the height of Mount Everest
is a datum that communicates a precisely measured value. This
measurement may be included in a book along with other data on Mount
Everest to describe the mountain in a manner useful for those who wish
to decide on the best method to climb it. Awareness of the
characteristics represented by this data is knowledge.
Data are often assumed to be the least abstract concept, information the next least, and knowledge the most abstract. In this view, data becomes information by interpretation; e.g., the
height of Mount Everest is generally considered "data", a book on Mount
Everest geological characteristics may be considered "information", and a
climber's guidebook containing practical information on the best way to
reach Mount Everest's peak may be considered "knowledge". "Information"
bears a diversity of meanings that range from everyday usage to
technical use. This view, however, has also been argued to reverse how
data emerges from information, and information from knowledge. Generally speaking, the concept of information is closely related to
notions of constraint, communication, control, data, form, instruction,
knowledge, meaning, mental stimulus, pattern, perception, and representation. Beynon-Davies uses the concept of a sign
to differentiate between data and information; data is a series of
symbols, while information occurs when the symbols are used to refer to
something.
Before the development of computing devices and machines, people
had to manually collect data and impose patterns on it. With the
development of computing devices and machines, these devices can also
collect data. In the 2010s, computers were widely used in many fields to
collect data and sort or process it, in disciplines ranging from marketing, analysis of social service
usage by citizens to scientific research. These patterns in the data
are seen as information that can be used to enhance knowledge. These
patterns may be interpreted as "truth"
(though "truth" can be a subjective concept) and may be authorized as
aesthetic and ethical criteria in some disciplines or cultures. Events
that leave behind perceivable physical or virtual remains can be traced
back through data. Marks are no longer considered data once the link
between the mark and observation is broken.
Mechanical computing devices are classified according to how they represent data. An analog computer represents a datum as a voltage, distance, position, or other physical quantity. A digital computer represents a piece of data as a sequence of symbols drawn from a fixed alphabet.
The most common digital computers use a binary alphabet, that is, an
alphabet of two characters typically denoted "0" and "1". More familiar
representations, such as numbers or letters, are then constructed from
the binary alphabet. Some special forms of data are distinguished. A computer program
is a collection of data, that can be interpreted as instructions. Most
computer languages make a distinction between programs and the other
data on which programs operate, but in some languages, notably Lisp and similar languages, programs are essentially indistinguishable from other data. It is also useful to distinguish metadata,
that is, a description of other data. A similar yet earlier term for
metadata is "ancillary data." The prototypical example of metadata is
the library catalog, which is a description of the contents of books.
Data sources
With
respect to ownership of data collected in the course of marketing or
other corporate collection, data has been characterized according to
"party" depending on how close the data is to the source or if it has
been generated through additional processing. "Zero-party data" refers
to data that customers "intentionally and proactively shares". This kind of data can come from a variety of sources, including:
subscriptions, preference centers, quizzes, surveys, pop-up forms, and
interactive digital experiences. "First-party data" may be collected by a company directly from its customers. The secure exchange of first-party data among companies can be done using data clean rooms. "Second-party data" refers to data obtained from other organizations or
partners, through purchase or other means and has been described as
"another organization's first-party data". "Third-party data" is data collected by other organizations and
subsequently aggregated from different sources, websites, and platforms.
Summary of data sources
Data source
Owned by
Accuracy
Use case
Privacy risk
First-party
The business
High
Personalization, retargeting
Low
Second-party
Partner
Moderate
Partnership campaigns
Moderate
Third-party
External entity
Low
Broad targeting
High
"No-party" data can sometimes refer to synthetic data that is generated based on patterns from original data.
Data documents
Whenever data needs to be registered, data exists in the form of a data document. Kinds of data documents include:
Some of these data documents (data repositories, data studies, data sets, and software) are indexed in Data Citation Indexes, while data papers are indexed in traditional bibliographic databases, e.g., Science Citation Index.
Data collection
Gathering
data can be accomplished through a primary source (the researcher is
the first person to obtain the data) or a secondary source (the
researcher obtains the data that has already been collected by other
sources, such as data disseminated in a scientific journal). Data
analysis methodologies vary and include data triangulation and data
percolation. The latter offers an articulate method of collecting, classifying, and
analyzing data using five possible angles of analysis (at least three)
to maximize the research's objectivity and permit an understanding of
the phenomena under investigation as complete as possible: qualitative
and quantitative methods, literature reviews (including scholarly
articles), interviews with experts, and computer simulation. The data is
thereafter "percolated" using a series of pre-determined steps so as to
extract the most relevant information.
Data longevity and accessibility
An important field in computer science, technology, and library science is the longevity of data. Scientific research generates huge amounts of data, especially in genomics and astronomy, but also in the medical sciences, e.g. in medical imaging. In the past, scientific data has been published in papers and books, stored in libraries, but more recently practically all data is stored on hard drives or optical discs.
However, in contrast to paper, these storage devices may become
unreadable after a few decades. Scientific publishers and libraries have
been struggling with this problem for a few decades, and there is still
no satisfactory solution for the long-term storage of data over
centuries or even for eternity.
Data accessibility. Another problem is that much scientific data is never published or deposited in data repositories such as databases.
In a recent survey, data was requested from 516 studies that were
published between 2 and 22 years earlier, but less than one out of five
of these studies were able or willing to provide the requested data.
Overall, the likelihood of retrieving data dropped by 17% each year
after publication. Similarly, a survey of 100 datasets in Dryad found that more than half lacked the details to reproduce the research results from these studies. This shows the dire situation of access to scientific data that is not
published or does not have enough details to be reproduced.
A solution to the problem of reproducibility is the attempt to require FAIR data,
that is, data that is Findable, Accessible, Interoperable, and
Reusable. Data that fulfills these requirements can be used in
subsequent research and thus advances science and technology.
In other fields
Although
data is also increasingly used in other fields, it has been suggested
that their highly interpretive nature might be at odds with the ethos of
data as "given". Peter Checkland introduced the term capta (from the Latin capere, "to take") to distinguish between an immense number of possible data and a sub-set of them, to which attention is oriented. Johanna Drucker has argued that since the humanities affirm knowledge production as "situated, partial, and constitutive," using data may introduce assumptions that are counterproductive, for example, that phenomena are discrete or are observer-independent. The term capta, which emphasizes the act of observation as constitutive, is offered as an alternative to data for visual representations in the humanities.
The term data-driven is a neologism applied to an activity which is primarily compelled by data over all other factors.Data-driven applications include data-driven programming and data-driven journalism.
Around the 1970s/1980s the term information engineering methodology (IEM) was created to describe database design and the use of software for data analysis and processing. These techniques were intended to be used by database administrators (DBAs) and by systems analysts
based upon an understanding of the operational processing needs of
organizations for the 1980s. In particular, these techniques were meant
to help bridge the gap between strategic business planning and
information systems. A key early contributor (often called the "father"
of information engineering methodology) was the Australian Clive Finkelstein, who wrote several articles about it between 1976 and 1980, and also co-authored an influential Savant Institute report on it with James Martin. Over the next few years, Finkelstein continued work in a more
business-driven direction, which was intended to address a rapidly
changing business environment; Martin continued work in a more data
processing-driven direction. From 1983 to 1987, Charles M. Richter,
guided by Clive Finkelstein, played a significant role in revamping IEM
as well as helping to design the IEM software product (user data), which
helped automate IEM.
In the early 2000s, the data and data tooling was generally held by the information technology (IT) teams in most companies. Other teams then used data for their work (e.g. reporting), and there
was usually little overlap in data skillset between these parts of the
business.
In the early 2010s, with the rise of the internet, the massive increase in data volumes, velocity, and variety led to the term big data to describe the data itself, and data-driven tech companies like Facebook and Airbnb started using the phrase data engineer. Due to the new scale of the data, major firms like Google, Facebook, Amazon, Apple, Microsoft, and Netflix started to move away from traditional ETL and storage techniques. They started creating data engineering, a type of software engineering focused on data, and in particular infrastructure, warehousing, data protection, cybersecurity, mining, modelling, processing, and metadata management. This change in approach was particularly focused on cloud computing. Data started to be handled and used by many parts of the business, such as sales and marketing, and not just IT.
Tools
Compute
High-performance
computing is critical for the processing and analysis of data. One
particularly widespread approach to computing for data engineering is dataflow programming, in which the computation is represented as a directed graph (dataflow graph); nodes are the operations, and edges represent the flow of data. Popular implementations include Apache Spark, and the deep learning specific TensorFlow.More recent implementations, such as Differential/Timely Dataflow, have used incremental computing for much more efficient data processing.
Storage
Data
is stored in a variety of ways, one of the key deciding factors is in
how the data will be used.
Data engineers optimize data storage and processing systems to reduce
costs. They use data compression, partitioning, and archiving.
Databases
If the data is structured and some form of online transaction processing is required, then databases are generally used. Originally mostly relational databases were used, with strong ACID transaction correctness guarantees; most relational databases use SQL for their queries. However, with the growth of data in the 2010s, NoSQL databases have also become popular since they horizontally scaled more easily than relational databases by giving up the ACID transaction guarantees, as well as reducing the object-relational impedance mismatch. More recently, NewSQL databases — which attempt to allow horizontal scaling while retaining ACID guarantees — have become popular.
If the data is structured and online analytical processing is required (but not online transaction processing), then data warehouses are a main choice. They enable data analysis, mining, and artificial intelligence on a much larger scale than databases can allow, and indeed data often flow from databases into data warehouses. Business analysts, data engineers, and data scientists can access data warehouses using tools such as SQL or business intelligence software.
The
number and variety of different data processes and storage locations
can become overwhelming for users. This inspired the usage of a workflow management system (e.g. Airflow) to allow the data tasks to be specified, created, and monitored. The tasks are often specified as a directed acyclic graph (DAG).
Lifecycle
Business planning
Business
objectives that executives set for what's to come are characterized in
key business plans, with their more noteworthy definition in tactical
business plans and implementation in operational business plans. Most
businesses today recognize the fundamental need to grow a business plan
that follows this strategy. It is often difficult to implement these
plans because of the lack of transparency at the tactical and
operational degrees of organizations. This kind of planning requires
feedback to allow for early correction of problems that are due to
miscommunication and misinterpretation of the business plan.
Systems design
The design of data systems involves several components such as architecting data platforms, and designing data stores.
This is the process of producing a data model, an abstract model to describe the data and relationships between different parts of the data.
Roles
Data engineer
A data engineer is a type of software engineer who creates big dataETL
pipelines to manage the flow of data through the organization. This
makes it possible to take huge amounts of data and translate it into insights. They are focused on the production readiness of data and things like
formats, resilience, scaling, and security. Data engineers usually hail
from a software engineering background and are proficient in programming
languages like Java, Python, Scala, and Rust. They will be more familiar with databases, architecture, cloud computing, and Agile software development.
https://en.wikipedia.org/wiki/Women_in_computing Women in computing were among the first programmers in the
early 20th century, and contributed substantially to the industry. As
technology and practices altered, the role of women as programmers has
changed, and the recorded history of the field has downplayed their
achievements. Since the 18th century, women have developed scientific
computations, including Nicole-Reine Lepaute's prediction of Halley's Comet, and Maria Mitchell's computation of the motion of Venus.
The first algorithm intended to be executed by a computer was designed by Ada Lovelace who was a pioneer in the field. Grace Hopper was the first person to design a compiler for a programming language. Throughout the 19th and early 20th century, and up to World War II, programming was predominantly done by women; significant examples include the Harvard Computers, codebreaking at Bletchley Park and engineering at NASA. After the 1960s, the computing work that had been dominated by women evolved into modern software, and the importance of women decreased.
The gender disparity
and the lack of women in computing from the late 20th century onward
has been examined, but no firm explanations have been established.
Nevertheless, many women continued to make significant and important
contributions to the IT industry, and attempts were made to readdress
the gender disparity in the industry. In the 21st century, women held
leadership roles in multiple tech companies, such as Meg Cushing Whitman, president and chief executive officer of Hewlett Packard Enterprise, and Marissa Mayer, president and CEO of Yahoo! and key spokesperson at Google.
One of the first computers for the American Nautical Almanac was Maria Mitchel. Her work on the assignment was to compute the motion of the planet Venus. The Almanac never became a reality, but Mitchell became the first astronomy professor at Vassar.
Ada Lovelace was the first person to publish an algorithm intended to be executed by the first modern computer, the Analytical Engine created by Charles Babbage. As a result, she is often regarded as the first computer programmer. Lovelace was introduced to Babbage's difference engine when she was 17. In 1840, she wrote to Babbage and asked if she could become involved with his first machine. By this time, Babbage had moved on to his idea for the Analytical Engine. A paper describing the Analytical Engine, Notions sur la machine analytique, published by L.F. Menabrea, came to the attention of Lovelace, who not only translated it into English, but corrected mistakes made by Menabrea. Babbage suggested that she expand the translation of the paper with her
own ideas, which, signed only with her initials, AAL, "synthesized the
vast scope of Babbage's vision." Lovelace imagined the kind of impact of the Analytical Engine might have on society. She drew up explanations of how the engine could handle inputs, outputs, processing and data storage. She also created several proofs to show how the engine would handle calculations of Bernoulli Numbers on its own. The proofs are considered the first examples of a computer program. Lovelace downplayed her role in her work during her life, for example,
in signing her contributions with AAL so as not be "accused of
bragging."
After the Civil War in the United States, more women were hired as human computers. Many were war widows looking for ways to support themselves. Others were hired when the government opened positions to women because of a shortage of men to fill the roles.
Photograph of the Harvard Computers (unflatteringly known as "Pickering's Harem")Annie Jump Cannon working at Harvard
Anna Winlock asked to become a computer for the Harvard Observatory in 1875 and was hired to work for 25 cents an hour. By 1880, Edward Charles Pickering had hired several women to work for him at Harvard because he knew that women could do the job as well as men and he could ask them to volunteer or work for less pay. The women, described as "Pickering's harem" and also as the Harvard Computers, performed clerical work that the male employees and scholars considered to be tedious at a fraction of the cost of hiring a man. The women working for Pickering cataloged around ten thousand stars, discovered the Horsehead Nebula and developed the system to describe stars. One of the "computers," Annie Jump Cannon, could classify stars at a rate of three stars per minute. The work for Pickering became so popular that women volunteered to work for free even when the computers were being paid. Even though they performed an important role, the Harvard Computers were paid less than factory workers.
By the 1890s, women computers were college graduates looking for jobs where they could use their training in a useful way. Florence Tebb Weldon, was part of this group and provided computations relating to biology and evidence for evolution, working with her husband, W.F. Raphael Weldon. Florence Weldon's calculations demonstrated that statistics could be used to support Darwin's theory of evolution. Another human computer involved in biology was Alice Lee, who worked with Karl Pearson. Pearson hired two sisters to work as part-time computers at his Biometrics Lab, Beatrice and Frances Cave-Brown-Cave.
1910s
During World War I, Karl Pearson and his Biometrics Lab helped produce ballistics calculations for the British Ministry of Munitions. Beatrice Cave-Browne-Cave helped calculate trajectories for bomb shells. In 1916, Cave-Brown-Cave left Pearson's employ and started working full-time for the Ministry. In the United States, women computers were hired to calculate ballistics in 1918, working in a building on the Washington Mall. One of the women, Elizabeth Webb Wilson, worked as the chief computer. After the war, women who worked as ballistics computers for the U.S. government had trouble finding jobs in computing and Wilson eventually taught high school math.
1920s
A group of operators working on an AT&T telephone switchboard
In the early 1920s, Iowa State College, professor George Snedecor worked to improve the school's science and engineering departments, experimenting with new punch-card machines and calculators. Snedecor also worked with human calculators most of them women, including Mary Clem. Clem coined the term "zero check" to help identify errors in calculations. The computing lab, run by Clem, became one of the most powerful computing facilities of the time.
Women computers also worked at the American Telephone and Telegraph company. These human computers worked with electrical engineers to help figure out how to boost signals with vacuum tube amplifiers. One of the computers, Clara Froelich, was eventually moved along with
the other computers to their own division where they worked with a
mathematician, Thornton Fry, to create new computational methods. Froelich studied IBM tabulating equipment and desk calculating machines to see if she could adapt the machine method to calculations.
Edith Clarke was the first woman to earn a degree in electrical engineering and who worked as the first professionally employed electrical engineer in the United States. She was hired by General Electric as a full engineer in 1923. Clarke also filed a patent in 1921 for a graphical calculator to be used in solving problems in power lines. It was granted in 1925.
The Works Progress Administration hired women as human calculators in order to support engineers during World War II. This was largely seen as menial labor, and much of the work was focused on calculations and less on problem solving.
Barbara “Barby” Canright
was recruited for California’s Jet Propulsion Laboratory in 1939 as a
human calculator, largely working with engineers in order to determine
thrust-to-weight ratios and other various important aeronautics
calculations.
"Tedious" computing and calculating was seen as "women's work" through the 1940s resulting in the term "kilogirl", invented by a member of the Applied Mathematics Panel in the early 1940s. A kilogirl of energy was "equivalent to roughly a thousand hours of computing labor." While women's contributions to the United States war effort during World War II was championed in the media, their roles and the work they did was minimized. This included minimizing the complexity, skill and knowledge needed to work on computers or work as human computers. During WWII, women did most of the ballistics computing, seen by male engineers as being below their level of expertise. Black women computers worked as hard (or more often, even harder) as their white counterparts, but in segregated situations. By 1943, almost all people employed as computers were women; one report
said "programming requires lots of patience, persistence and a capacity
for detail and those are traits that many girls have".
NACA expanded its pool of women human computers in the 1940s. NACA recognized in 1942 that "the engineers admit themselves that the
girl computers do the work more rapidly and accurately than they could." In 1943 two groups, segregated by race, worked on the east and west side of Langley Air Force Base. The black women were the West Area Computers. Unlike their white counterparts, the black women were asked by NACA to
re-do college courses they had already passed and many never received
promotions.
Women were also working on ballistic missile calculations. In 1948, women such as Barbara Paulson were working on the WAC Corporal, determining trajectories the missiles would take after launch.
Women worked with cryptography and, after some initial resistance, many operated and worked on the Bombe machines. Joyce Aylard operated the Bombe machine testing different methods to break the Enigma code. Joan Clarke was a cryptographer who worked with her friend, Alan Turing, on the Enigma machine at Bletchley Park. When she was promoted to a higher salary grade, there were no positions
in the civil service for a "senior female cryptanalyst," and she was
listed as a linguist instead. While Clarke developed a method of increasing the speed of
double-encrypted messages, unlike many of the men, her decryption
technique was not named after her. Other cryptographers at Bletchley included Margaret Rock, Mavis Lever (later Batey), Ruth Briggs and Kerry Howard. In 1941, Batey's work enabled the Allies to break the Italians' naval code before the Battle of Cape Matapan. In the United States, several faster Bombe machines were created. Women, like Louise Pearsall, were recruited from the WAVES to work on code breaking and operate the American Bombe machines.
Hedy Lamarr and co-inventor, George Antheil, worked on a frequency hopping method to help the Navy control torpedoes remotely. The Navy passed on their idea, but Lamarr and Antheil received a patent for the work on August 11, 1942. This technique would later be used again, first in the 1950s at
Sylvania Electronic Systems Division and is used in everyday technology
such as Bluetooth and Wi-Fi.
The programmers of the ENIAC computer in 1944, were six female mathematicians; Marlyn Meltzer, Betty Holberton, Kathleen Antonelli, Ruth Teitelbaum, Jean Bartik, and Frances Spence, who were human computers at the Moore School's computation lab. Adele Goldstine was their teacher and trainer and they were known as the "ENIAC girls." The women who worked on ENIAC were warned that they would not be promoted into professional ratings which were only for men. Designing the hardware was "men's work" and programming the software was "women's work." Sometimes women were given blueprints and wiring diagrams to figure out how the machine worked and how to program it. They learned how the ENIAC worked by repairing it, sometimes crawling
through the computer, and by fixing "bugs" in the machinery. Even though the programmers were supposed to be doing the "soft" work
of programming, in reality, they did that and fully understood and
worked with the hardware of the ENIAC. When the ENIAC was revealed in 1946, Goldstine and the other women
prepared the machine and the demonstration programs it ran for the
public. None of their work in preparing the demonstrations was mentioned in the official accounts of the public events. After the demonstration, the university hosted an expensive celebratory dinner to which none of the ENIAC six were invited.
Grace Hopper was the first person to create a compiler for a programming language and one of the first programmers of the Harvard Mark I
computer, an electro-mechanical computer based on Analytical Engine.
Hopper's work with computers started in 1943, when she started working
at the Bureau of Ordnance's Computation Project at Harvard where she programmed the Harvard Mark I. Hopper not only programmed the computer, but created a 500-page comprehensive manual for it. Even though Hopper created the manual, which was widely cited and published, she was not specifically credited in it. Hopper is often credited with the coining of the term "bug" and "debugging" when a moth caused the Mark II to malfunction. While a moth was found and the process of removing it called
"debugging," the terms were already part of the language of programmers.
Grace Hopper continued to contribute to computer science through the
1950s. She brought the idea of using compilers from her time at Harvard
to UNIVAC which she joined in 1949.Other women who were hired to program UNIVAC included Adele Mildred Koss, Frances E. Holberton, Jean Bartik, Frances Morello and Lillian Jay. To program the UNIVAC, Hopper and her team used the FLOW-MATIC programming language, which she developed. Holberton wrote a code, C-10, that allowed for keyboard inputs into a general-purpose computer. Holberton also developed the Sort-Merge Generator in 1951 which was used on the UNIVAC I. The Sort-Merge Generator marked the first time a computer "used a program to write a program." Holberton suggested that computer housing should be beige or oatmeal in color which became a long-lasting trend. Koss worked with Hopper on various algorithms and a program that was a precursor to a report generator.
Klara Dan von Neumann was one of the main programmers of the MANIAC, a more advanced version of ENIAC. Her work helped the field of meteorology and weather prediction.
Mary Tsingou developed and ran code on MANIAC to model the evolution of interacting waves on a string, a problem suggested by Enrico Fermi, John Pasta, and Stanislaw Ulam. They discovered a paradox whereby a system expected to thermalise instead showed quasi-periodic behaviour. The problem became known as the Fermi-Pasta-Ulam-Tsingou problem, and spawned the use of computers for numerical experiments in nonlinear science.
The NACA, and subsequently NASA, recruited women computers following World War II. By the 1950s, a team was performing mathematical calculations at the Lewis Research Center in Cleveland, Ohio, including Annie Easley, Katherine Johnson and Kathryn Peddrew. At the National Bureau of Standards, Margaret R. Fox was hired to work as part of the technical staff of the Electronic Computer Laboratory in 1951. In 1956, Gladys West was hired by the U.S. Naval Weapons Laboratory as a human computer. West was involved in calculations that let to the development of GPS.
At Convair Aircraft Corporation, Joyce Currie Little was one of the original programmers for analyzing data received from the wind tunnels. She used punch cards on an IBM 650 which was located in a different building from the wind tunnel. To save time in the physical delivery of the punch cards, she and her colleague, Maggie DeCaro, put on roller skates to get to and from the building faster.
In Israel, Thelma Estrin worked on the design and development of WEIZAC, one of the world's first large-scale programmable electronic computers. In the Soviet Union a team of women helped design and build the first digital computer in 1951. In the UK, Kathleen Booth worked with her husband, Andrew Booth on several computers at Birkbeck College. Kathleen Booth was the programmer and Andrew built the machines. Kathleen developed Assembly Language at this time.
Mary Coombs (of England) was employed in 1952 as the first female programmer to work on the LEO computers, and as such she is recognized as the first female commercial programmer.
PFC Patricia Barbeau operates a tape-drive on the IBM 729 at Camp Smith.
Milly Koss who had worked at UNIVAC with Hopper, started work at Control Data Corporation (CDC) in 1965. There she developed algorithms for graphics, including graphic storage and retrieval.
Mary K. Hawes of Burroughs Corporation set up a meeting in 1959 to discuss the creation a computer language that would be shared between businesses. Six people, including Hopper, attended to discuss the philosophy of creating a common business language (CBL). Hopper became involved in developing COBOL (Common Business Oriented Language) where she innovated new symbolic ways to write computer code. Hopper developed programming language that was easier to read and "self-documenting." After COBOL was submitted to the CODASYL Executive Committee, Betty Holberton did further editing on the language before it was submitted to the Government Printing Office in 1960. IBM were slow to adopt COBOL, which hindered its progress but it was
accepted as a standard in 1962, after Hopper had demonstrated the
compiler working both on UNIVAC and RCA computers. The development of COBOL led to the generation of compilers and
generators, most of which were created or refined by women such as Koss,
Nora Moser, Deborah Davidson, Sue Knapp, Gertrude Tierney and Jean E. Sammet.
Sammet, who worked at IBM starting in 1961 was responsible for developing the programming language, FORMAC. She published a book, Programming Languages: History and Fundamentals (1969), which was considered the "standard work on programming languages," according to Denise Gürer It was "one of the most used books in the field," according to The Times in 1972.
Margaret Hamilton in 1969, standing next to listings of the software she and her MIT team produced for the Apollo project
Between 1961 and 1963, Margaret Hamilton began to study software reliability while she was working at the US SAGE air defense system. In 1965, she was responsible for programming the software for the onboard flight software on the Apollo mission computers. After Hamilton had completed the program, the code was sent to Raytheon
where "expert seamstresses" called the "Little Old Ladies" actually
hardwired the code by threading copper wire through magnetic rings. Each system could store more than 12,000 words that were represented by the copper wires.
In 1964, the British Prime MinisterHarold Wilson announced a "White-Hot" revolution in technology, that would give greater prominence to IT work. As women still held most
computing and programming positions at this time, it was hoped that it
would give them more positive career prospects. In 1965, Sister Mary Kenneth Keller became the first American woman to earn a doctorate in computer science. Keller helped develop BASIC while working as a graduate student at Dartmouth, where the university "broke the 'men only' rule" so she could use its computer science center.
In 1966, Frances "Fran" Elizabeth Allen who was developing programming language compilers at IBM Research,
published a paper entitled "Program Optimization,". It laid the
conceptual basis for systematic analysis and transformation of computer
programs. This paper introduced the use of graph-theoretic structures to
encode program content in order to automatically and efficiently derive
relationships and identify opportunities for optimization.
Christine Darden began working for NASA's computing pool in 1967 having graduated from the Hampton Institute. Women were involved in the development of Whirlwind, including Judy Clapp. She created the prototype for an air defense system for Whirlwind which
used radar input to track planes in the air and could direct aircraft
courses.
In 1969, Elizabeth "Jake" Feinler, who was working for Stanford, made the first Resource Handbook for ARPANET. This led to the creation of the ARPANET directory, which was built by Feinler with a staff of mostly women. Without the directory, "it was nearly impossible to navigate the ARPANET."
By the end of the decade, the general demographics of programmers had
shifted away from being predominantly women, as they had before the
1940s. Though women accounted for around 30 to 50 percent of computer
programmers during the 1960s, few were promoted to leadership roles and
women were paid significantly less than their male counterparts. Cosmopolitan ran an article in the April 1967 issue about women in programming called "The Computer Girls." Even while magazines such as Cosmopolitan
saw a bright future for women in computers and computer programming in
the 1960s, the reality was that women were still being marginalized.
Using an NCR 796-201 cathode-ray terminal, circa 1972
In the early 1970s, Pam Hardt-English led a group to create a computer network they named Resource One and which was part of a group called Project One. Her idea to connect Bay Area bookstores, libraries and Project One was an early prototype of the Internet. To work on the project, Hardt-English obtained an expensive SDS-940 computer as a donation from TransAmerica Leasing Corporation in April 1972. They created an electronic library and housed it in a record store called Leopold's in Berkeley. This became the Community Memory database and was maintained by hacker Jude Milhon. After 1975, the SDS-940 computer was repurposed by Sherry Reson, Mya
Shone, Chris Macie and Mary Janowitz to create a social services
database and a Social Services Referral Directory. Hard copies of the directory, printed out as a subscription service, were kept at city buildings and libraries. The database was maintained and in use until 2009.
In the early 1970s, Elizabeth "Jake" Feinler, who worked on the Resource Directory for ARPANET, and her team created the first WHOIS directory. Feinler set up a server at the Network Information Center (NIC) at Stanford which would work as a directory that could retrieve relevant information about a person or entity. She and her team worked on the creation of domains, with Feinler suggesting that domains be divided by categories based on where the computers were kept. For example, military computers would have the domain of .mil, computers at educational institutions would have .edu. Feinler worked for NIC until 1989.
Jean E. Sammet served as the first woman president of the Association for Computing Machinery (ACM), holding the position between 1974 and 1976.
In the late 1970s, women such as Paulson and Sue Finley wrote programs for the Voyager mission. Voyager continues to carry their codes inside its own memory banks as it leaves the Solar System. In 1979, Ruzena Bajcsy founded the General Robotics, Automation, Sensing and Perception (GRASP) Lab at the University of Pennsylvania.
In the mid-70s, Joan Margaret Winters began working at IBM as part of a "human factors project," called SHARE. In 1978, Winters was the deputy manager of the project and went on to lead the project between 1983 and 1987. The SHARE group worked on researching how software should be designed to consider human factors.
Erna Schneider Hoover developed a computerized switching system for telephone calls that would replace switchboards. Her software patent for the system, issued in 1971, was one of the first software patents ever issued.
1980s
Shelley Lake working on computer graphics at Digital Productions, 1983
Gwen Bell developed the Computer Museum in 1980. The museum, which collected computer artifacts became a non-profit organization in 1982 and in 1984, Bell moved it to downtown Boston. Adele Goldberg served as president of ACM between 1984 and 1986.
In 1981, Deborah Washington Brown
became the first African American woman to earn a Ph.D. in computer
science from Harvard University (at the time the degree was part of the
applied mathematics program). Her thesis was titled "The solution of difference equations describing array manipulation in program loops". Shortly after, in 1982, Marsha R. Williams became the second African American woman to earn a Ph.D. in computer science.
Sometimes known as the "Betsy Ross of the personal computer," according to the New York Times, Susan Kare worked with Steve Jobs to design the original icons for the Macintosh. Kare designed the moving watch, paintbrush and trash can elements that made using a Mac user-friendly. Kare worked for Apple until the mid-1980s, going on to work on icons for Windows 3.0. Other types of computer graphics were being developed by Nadia Magnenat Thalmann in Canada. Thalmann started working on computer animation to develop "realistic virtual actors" first at the University of Montréal in 1980 and later in 1988 at the École Polytechnique Fédérale de Lausanne.
Computer and video games became popular in the 1980s, but many
were primarily action-oriented and not designed from a woman's point of
view. Stereotypical characters such as the damsel in distress featured prominently and consequently were not inviting towards women. Dona Bailey designed Centipede, where the player shoots insects, as a reaction to such games, later saying "It didn't seem bad to shoot a bug". Carol Shaw, considered to be the first modern female games designer, released a 3D version of tic-tac-toe for the Atari 2600 in 1980. Roberta Williams and her husband Ken, founded Sierra Online and pioneered the graphic adventure game format in Mystery House and the King's Quest series. The games had a friendly graphical user interface
and introduced humor and puzzles. Cited as an important game designer,
her influence spread from Sierra to other companies such as LucasArts and beyond. Brenda Laurel ported games from arcade versions to the Atari 8-bit computers in the late 1970s and early 1980s. She then went to work for Activision and later wrote the manual for Maniac Mansion.
1984 was the year of Women into Science and Engineering (WISE Campaign). A 1984 report by Ebury Publishing
reported that in a typical family, only 5% of mothers and 19% of
daughters were using a computer at home, compared to 25% of fathers and
51% of sons. To counteract this, the company launched a series of
software titles designed towards women and publicized in Good Housekeeping. Anita Borg, who had been noticing that women were under-represented in computer science, founded an email support group, Systers, in 1987.
As Ethernet became the standard for networking computers locally, Radia Perlman,
who worked at Digital Equipment Corporation (DEC), was asked to "fix"
limitations that Ethernet imposed on large network traffic. In 1985, Perlman came up with a way to route information packets from
one computer to another in an "infinitely scalable" way that allowed
large networks like the Internet to function. Her solution took less than a few days to design and write up. The name of the algorithm she created is the Spanning Tree Protocol. In 1986, Lixia Zhang was the only woman and graduate student to participate in the early Internet Engineering Task Force (IETF) meetings. Zhang was involved in early Internet development.
In Europe, project was developed in the mid-1980s to create an academic network in Europe using the Open System Interconnection (OSI) standards. Borka Jerman Blažič, a Yugoslavian computer scientist was invited to work on the project. She was involved in establishing a Yugoslav Research and Academic Network (YUNAC) in 1989 and registered the domain of .yu for the country.
In the field of human–computer interaction (HCI), French computer scientist, Joëlle Coutaz developed the presentation-abstraction-control (PAC) model in 1987. She founded the User Interface group at the Laboratorire de Génie
Informatique of IMAG where they worked on different problems relating to
user interface and other software tools.
In 1988, Stacy Horn, who had been introduced to bulletin board systems (BBS) through The WELL, decided to create her own online community in New York, which she called the East Coast Hang Out (ECHO). Horn invested her own money and pitched the idea for ECHO to others after bankers refused to hear her business plan. Horn built her BBS using UNIX, which she and her friends taught to one another. Eventually ECHO moved an office in Tribeca in the early 1990s and started getting press attention. ECHO's users could post about topics that interested them, and chat with one another, and were provided email accounts. Around half of ECHO's users were women. ECHO was still online as of 2018.
1990s
Jaime Levy helped popularise the e-Zine in the 1990s.
By the 1990s, computing was dominated by men. The proportion of
female computer science graduates peaked in 1984 around 37 per cent, and
then steadily declined. Although the end of the 20th century saw an increase in women
scientists and engineers, this did not hold true for computing, which
stagnated. Despite this, they were very involved in working on hypertext and hypermedia projects in the late 1980s and early 1990s. A team of women at Brown University, including Nicole Yankelovich and Karen Catlin, developed Intermedia and invented the anchor link. Apple partially funded their project and incorporated their concepts into Apple operating systems. Sun Microsystems Sun Link Service was developed by Amy Pearl. Janet Walker developed the first system to use bookmarks when she created the Symbolics Document Examiner. In 1989, Wendy Hall created a hypertext project called Microcosm, which was based on digitized multimedia material found in the Mountbatten archive. Cathy Marshall worked on the NoteCards system at Xerox PARC. NoteCards went on to influence Apple's HyperCard. As the Internet became the World Wide Web, developers like Hall adapted their programs to include Web viewers. Her Microcosm was especially adaptable to new technologies, including animation and 3-D models. In 1994, Hall helped organize the first conference for the Web.
Following the increased popularity of the Internet in the 1990s,
online spaces were set up to cater for women, including the online
community Women's WIRE and the technical and support forum LinuxChix. Women's WIRE, launched by Nancy Rhine and Ellen Pack in October 1993,
was the first Internet company to specifically target this demographic. A conference for women in computer-related jobs, the Grace Hopper Celebration of Women in Computing, was first launched in 1994 by Anita Borg.
Game designer Brenda Laurel started working at Interval Research in 1992, and began to think about the differences in the way girls and boys experienced playing video games. After interviewing around 1,000 children and 500 adults, she determined
that games weren't designed with girls' interests in mind. The girls she spoke with wanted more games with open worlds and characters they could interact with. Her research led to Interval Research giving Laurel's research team their own company in 1996, Purple Moon. Also in 1996, Mattel's game, Barbie Fashion Designer, became the first best-selling game for girls. Purple Moon's first two games based on a character called Rockett, made
it to the 100 best-selling games in the years they were released. In 1999, Mattel bought out Purple Moon.
Jaime Levy created one of the first e-Zines in the early 1990s, starting with CyberRag, which included articles, games and animations loaded onto diskettes that anyone with a Mac could access. Later, she renamed the zine to Electronic Hollywood.Billy Idol commissioned Levy to create a disk for his album, Cyberpunk. She was hired to be the creative director of the online magazine, Word, in 1995.
In the late 1990s, research by Jane Margolis led Carnegie Mellon to try to correct the male-female imbalance in computer science.
From the late 1980s until the mid-1990s, Misha Mahowald developed several key foundations of the field of Neuromorphic engineering, while working at the California Institute of Technology and later at the ETH Zurich. More than 20 years after her untimely death, the Misha Mahowald Prize was named after her to recognize excellence in the field which she helped to create.
2000s
Former vice-president of Google Search Products and User Experience, former president and CEO of Yahoo!, Marissa Mayer
In the 21st century, several attempts have been made to reduce the
gender disparity in IT and get more women involved in computing again. A
2001 survey found that while both sexes use computers and the internet
in equal measure, women were still five times less likely to choose it
as a career or study the subject beyond standard secondary education. Journalist Emily Chang said a key problem has been personality tests
in job interviews and the belief that good programmers are introverts,
which tends to self-select the stereotype of an asocial white male nerd.
In 2004, the National Center for Women & Information Technology was established by Lucy Sanders to address the gender gap. Carnegie Mellon University
has made a concerted attempt to increase gender diversity in the
computer science field, by selecting students based on a wide criteria
including leadership ability, a sense of "giving back to the community"
and high attainment in maths and science, instead of traditional
computer programming expertise. As well as increase the intake of women
into CMU, the programme produced better quality students because of the
increased diversity making a stronger team.
In 2017, Michelle Simmons founded the first quantum computing company in Australia. The team, which has made "great strides" in 2018, plans to develop a 10-qubit prototype silicon quantum integrated circuit by 2022. In the same year, Doina Precup became the head of DeepMind Montreal, working on artificial intelligence. Xaviera Kowo is a programmer from Cameroon, who won the Margaret award, for programming a robot which processes waste in 2022.
2020s
In
2023 the EU-Startups the leading online publication with a focus on
startups in Europe published the list of top 100 of the most influential
women in the startup and venture capital space in Europe. The theme of the list reflects the era of innovation and technological
change. That being said, there are plenty of inspiring women in Europe's
startup and all around the world in VC space who are making daily
changes possible and encouraging a new generation of female for
entrepreneurship and innovation.
While computing began as a field heavily dominated by women, this
changed in western countries shortly after World War II. In the US,
recognizing software development was a significant expense, companies
wanted to hire an "ideal programmer". Psychologists William Cannon and
Dallis Perry were hired to develop an aptitude test for programmers, and
from an industry that was more than 50% women they selected 1400
people, 1200 of whom were male. This paper was highly influential and
claimed to have "trained the industry" in hiring programmers, with a
heavy focus on introverts and men. In Britain, following the war, women programmers were selected for
redundancy and forced retirement, leading to the country losing its
position as computer science leader by 1974.
Popular theories are favored about the lack of women in computer
science, which discount historical and social circumstances. In 1992, John Gray's Men Are from Mars, Women Are from Venus
theorized that men and women tend to differ in ways of thinking,
leading to them approaching technology and computing in different ways. A significant issue is that women find themselves working in an
environment that is largely unpleasant, so they decline to continue in
those careers. A further issue is that if a class of computer scientists contains few
women, those few can be singled out, leading to isolation and feelings
of non-belonging, which can culminate in leaving the area.
The gender disparity in IT is not global. The ratio of female to male computer scientists is significantly higher in India compared to the West, and in 2015, over half of internet entrepreneurs in China were women. In Europe, Bulgaria and Romania have the highest rates of women going into computer programming. In government universities in Saudi Arabia in 2014, Arab women made up 59% of students enrolled in computer science. It has been suggested there is a greater gap in countries where people
of both sexes are treated more equally, contradicting any theories that
society in general is to blame for any disparity. However, the ratio of African American female computer scientists in the US is significantly lower than the global average. In IT-based organisations, the ratio of men to women can vary between roles; for example, while most software developers at InfoWatch are male, half of usability designers and 80% of project managers are female.
In 1991, Massachusetts Institute of Technology undergraduate Ellen Spertus wrote an essay "Why Are There So Few Women in Computer Science?", examining inherent sexism in IT, which was responsible for a lack of women in computing. She subsequently taught computer science at Mills College, Oakland in order to increase interest in IT for women. A key problem is a lack of female role models in the IT industry,
alongside computer programmers in fiction and the media generally being
male.
The University of Southampton's Wendy Hall
has said the attractiveness of computers to women decreased
significantly in the 1980s when they "were sold as toys for boys", and
believes the cultural stigma has remained ever since, and may even be
getting worse. Kathleen Lehman, project manager of the BRAID Initiative at UCLA has said a problem is that typically women aim for perfection and feel disillusioned when code does not compile, whereas men may simply treat it as a learning experience. A report in the Daily Telegraph
suggested that women generally prefer people-facing jobs, which many
computing and IT positions do not have, while men prefer jobs geared
towards objects and tasks. One issue is that the history of computing has focused on the hardware,
which was a male dominated field, despite software being written
predominantly by women in the early to mid 20th century.
In 2013, a National Public Radio report said 20% of computer programmers in the US are female. There is no general consensus for any key reason there are less women in computing. In 2017, an engineer was fired from Google after claiming there was a biological reason for a lack of female computer scientists.
Dame Stephanie Shirley using the name Steve Shirley
addressed some of the problems facing women in computing in the UK by
setting up the software company Freelance Programmers (later F.I, then
Xansa now Steria Sopra) offering the chance for women to work from home
and part-time work.
The Association for Computing MachineryTuring Award,
sometimes referred to as the "Nobel Prize" of computing, was named in
honor of Alan Turing. This award has been won by three women between
1966 and 2015.
The British Computer Society
Information Retrieval Specialist Group (BCS IRSG) in conjunction with
the British Computer Society created an award in 2008 to commemorate the
achievements of Karen Spärck Jones, a Professor Emerita of Computers and Information at the University of Cambridge and one of the most remarkable women in computer science. The KSJ award has been won by four women between 2009 and 2017:
The Women's Technology Empowerment Centre (W.TEC) is a non-profit organization focused on providing technology education and mentoring to Nigerian women and girls. Black Girls Code is a non-profit focused on providing technology education to young African-American women.
Other organisations dedicated to women in IT include Girl Develop It,
a nonprofit organization that provides affordable programs for adult
women interested in learning web and software development in a
judgment-free environment, Girl Geek Dinners, an International group for women of all ages, Girls Who Code: a national non-profit organization dedicated to closing the gender gap in technology, LinuxChix, a women-oriented community in the open source movement and Systers, a moderated listserv dedicated to mentoring women in the IT industry.
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