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"Detail Science" is a concept created by Stephen Widener.
Currently, "Detail Science" includes Data Observation and Data Reporting. It is the complete set of knowledges, techniques, and discernments that were initiated and implemented in the federal government, starting back as early as 2003.
The purpose of the "Detail Science" concept is to encapsulate the drive, purpose, and meaning behind the creation of Detail Science techniques in the federal government. Widener also wants to share insights into the intentions that fed his passion for the development of these techniques. These are the techniques that launched what eventually became known as Data Science.
Data Science is a profession that developed outside of the federal government, in the years after Detail Science reached maturity inside the federal government.
Widener also intends to expand everyone's understanding of his creation of the Details Sciences in the federal government. Why did Detail Science come in to existence in the first place? Who was involved? When did it happen?
Finally, Widener wants to share what he would like to happen for the future of the Detail Sciences profession.
Enjoy the read!
P.S. In keeping with the traditional legal rationales and precedents that have been set for intellectual property in the United States, all ideas, written text, concepts, and techniques created by Stephen Widener are the intellectual property of Stephen Widener, and therefore others are prohibited from duplicating or using said intellectual property in part or in whole as a basis for or to create any other intellectual property, which includes the position that employment in a company does not implicitly or explicitly convey any of Stephen Widener's intellectual property rights to that employer in any way, shape or form, unless an explicit intellectual property agreement is in place; no exceptions.
Data Science is something that is currently defined online.
Wikipedia describes data science as follows: “Data science is an interdisciplinary field focused on extracting knowledge from typically large data sets and applying the knowledge and insights from that data to solve problems in a wide range of application domains.”
Wikipedia describes a data scientist as someone who creates programming code and combines it with statistical knowledge to create insights from data. According to Wikipedia, a data scientist uses scientific methods, processes, algorithms and systems to extract knowledge and insights from noisy, structured and unstructured data.
Wikipedia states that “In 2015 the American Statistical Association identified database management, statistics, machine learning, and distributed and parallel systems as the three emerging foundational professional communities.”
Many people believe these to be the main ingredients that make up Data Science. And some people describe data science as a branch of statistics.
“There is still no consensus on the definition of data science, and it is considered by some to be a buzzword. Big data is a related marketing term. Data scientists are responsible for breaking down big data into usable information and creating software and algorithms that help companies and organizations determine optimal operations.”
The idea of Detail Science is a new concept.
Detail Science is defined using a conglomerate definition which consists of Data Observation, Data Construction, and Data Reporting.
On Wikipedia, there is currently no definition for Detail Science, Data Observation, or Data Reporting. There is also no definition of these terms anywhere else online.
Definitions for these terms only exist on this website.
What is the proper definition of a detail scientist? Read below.
We consider Art to be the most important factor in the proliferation of the detail sciences. Therefore, the true name of a detail scientist should actually be an "artistic scientist" or someone who uses an artistic approach to detail in creating the artifacts of the science.
The reason for the way these terms are worded is simple: art is separate than data. Furthermore, the world of technology is not the only place where scientific advances are made.
Wikipedia states that data science incorporates the following skills:
Computer science
Statistics
Information Science
Mathematics
Data Visualization
Information Visualization
Data Sonification
Data Integration
Graphic Design
Complex Systems
Communications
Business
According our own views on detail science we beleive the skillset of a detail scientist encompasses all those facets of a data scientist and also includes these characteristics:
Artistically Inclined
Elevated Level of the Senses (Touch, Smell, Eyesight, Taste, etc.)
Abilities Related to a Sixth Sense
High Emotional IQ
Ability to Switch Between High Level Thinking and Micro (Detail) Level Thinking
Presence of a Cerebral Brain-Based Internal Dialogue
The first difference between a data scientist and a detail scientist is that a detail scientist posseses all the skills necessary to become a great data scientist, but that is not necessarily true of a data scientist.
A great data scientist is great because they learned the profession, but, that profession first had to exist. This person was able to go to school, learn the science, and perform in it, just like a mathematician might do. In other words, a data scientist can adhere to rules of that science; rarely can they create more rules.
The second difference between a data scientist and a detail scientist is that a detail scientist can take any profession, science, activity, or task ... and ... with enough time ... re-create it, re-imagine it, re-birth it, and re-organize ... in to something that others would not even believe was possible.
A detail scientist is therefore capable of giving rise to entirely new sciences and adding rules to current sciences, even if they do not yet exist.
Widener makes it clear that he believes that the most important skillset that went into the creation of Detail Science was not Math, it was Art.
In Widener’s opinion, after the Artistic Mind went through to process of creating Detail Science, it was easier logically and more straight-forward to take that achievement and transform it into Data Science.
According to Widener, the "secret sauce" that went in to the creation of all of the sciences was never Math, it was always Art.
Widener also believes that there needs to be a additional “letter” added to the group term commonly referred to as “S.T.E.M.” This term stands for Science, Technology, Engineering, and Math.
Widener believes that a more acronym would be one that ads an "A" to the concept. The term would represent Science, Technology, Engineering, Math, and Art.
Hence, the revised acronym would be called “S.T.E.A.M.”
Science
Technology
Engineering
Math
Art
Detail Science is most likely the very first Artistic Science to ever exist. Widener says that without the artistic mind it is far more difficult to discern the problems and issues that you need to identify in order to bring to life a new systematic approach to solving a scientific problem.
Without the ability to “build from nothing” it is not possible to "build from nothing."
Furthermore, Widener states that in his opinion:
“Detail Science cannot be taught. It can only be identified. You either have it; or you don’t.”
This example is not an example of detail science; it is an example of detailed creativity.
One example of the detailed creativity that is typically involved in creating "something from nothing" in an area not related to science is the story of Ken Miles. Ken Miles is a detail creativitist.
Miles was portrayed in the 2019 movie: "Ford vs. Ferrari."
In this 1966-based movie, American car salesman Carroll Shelby solicits the help of experienced driver Ken Miles to build a revolutionary race car for Ford capable of beating Ferrari at Le Mans in 1966.
Throughout the movie, Miles races project cars over and over and over again. He complains about this. Complains about that. He "feels" that the suspension is not right. Or he yells at this person or that person because something could be better. Most of the time the others simply can not keep up with what he is saying. He seems to be the only one who knows what he's talking about. And they listen. And in the end? The car beats Ferrari.
What is important here is to note a few things: (1) there are no computers in this movie, (2) no science in Miles, and (3) no one really believes or supports much of what he is saying even while they are doing what he says.
You see, with Miles: the computer was his head; the database was his memories; and the spirit of his soul. Miles displayed his "data" in the most disorganized hard-to-understand manner. He barked commands. And somehow they got the car improved and that brought about a win. And changed history. This guy was about as low-tech as you can get!
Miles is a good example of detail and creativity hard at work. He had all the detail he needed about cars in his head.
This example is not an example of detail science; it is an example of detailed creativity.
Another example of detailed creativity is Carl Boenish, also known as the "Sunshine Superman." And, once again, he is someone who has never set foot in a lab and is not a scientist. Carl Boenish is a detail creativitist.
Carl Boenish lived in California and is the pioneer behind the creation of BASE Jumping. BASE Jumping is a hobby sport where someone puts on a parachute, leaps from a cliff, soars through the air next to the cliff, and then lands on the ground.
"Sunshine Superman" is a documentary about BASE jumping directed by Marah Strauch, and it is clear in the film that Carl is a detailed creationist. He created something out of nothing. He gave it a name. He gave it rules. He gave it a science.
The BASE Jumping hobby went from something that Carl and a few others did in California to something done for millions to see in a multi-million dollar feature film: Tomb Raider 2.
See for yourself!
Sunshine Superman:
https://vimeo.com/828667080/c145ffdf69?share=copy
Tomb Raider 2:
https://vimeo.com/828671685/0969a4f912?share=copy
Stephen Widener started working for the Department of Labor's Bureau of Labor Statistics in July of 2001, following the death of his maternal grandmother who he was taking care of.
Stephen Widener was raised in the California Bay Area; born in Berkeley, California.
Widener is of American Indian descent while also an African American.
His American Indian ancestry is that of the Maidu tribe of the Northern California Mountains. The tribe has existed for over 20,000 years on the West Coast. They are known for being persistent and riding horses without a saddle.
Stephen Widener is the son of Mary Lee Widener, who was Chief Executive Officer of Neighborhood Housing Services of America (NHSA).
NHSA was an organization that grew out of the hard work that was already being done by a White Jewish woman named Gale Cincotta. She was the original “brain trust” who identified and spear-headed national awareness for Bank Red Lining in Chicago, IL.
Gale’s work lives on even though she is now deceased. You can find her organization still doing great things in Washington D.C.: The National Community Reinvestment Coalition.
National Community Reinvestment Coalition and Neighborhood Housing Services of America were both grassroots member organizations that created opportunities for people to build wealth. They worked with community leaders, policymakers and financial institutions to champion fairness and end discrimination in lending, housing, and in business.
Stephen Widener is also the son to the First Black Mayor of Berkeley, Mayor Warren Widener. Warren Widener is a descendant of the California tribe to which Stephen belongs.
Stephen remembers the many things that his father did for the community, including installing crime-deterrent concrete directional blocks through the Berkeley streets and tearing down train tracks near his childhoold home and replacing them with a community center for the local youth.
Stephen also remembers his father's work on re-building and re-routing of the West Oakland Cyprus Freeway Onramp. The onramp was flattened after the 1989 Loma Prieta Earthquake that occurred near Pacifica, California, in the Santa Cruz Mountains.
Stephen Widener was physically in those mountains at the time of the earthquake, and the resulting chaos had a lasting effect on him.
Loma Prieta Earthquake:
https://www.conservation.ca.gov/cgs/earthquakes/loma-prieta
In the first week that Widener arrived at the federal government, he was immediately thrust in to the "mixed bag" of work that is what he called "the federal experience."
Widener was getting literally over 100 emails per day, and a almost non-stop mix of new employee orientations, online coursework, trainings, forms to fill out, management introductions, coworker introductions, visits of people from other departments, etc..
The activity was so much that Stephen thinks he has the record for the fastest failure in the federal government. He wasn't ready for federal work. And he was hospitalized and had to go on leave within just a few weeks of starting his new job.
Some of the people who later became his coworkers and his closest friends later told him that they thought he had quit.
Upon his return and recovery ... Widener finally started his federal career.
He appreciated the support that "up-until-now-strangers" showed him at the federal government. The support that they gave Widener was not only appreciated but it was also (according to Widener) ... infectious.
Simply put ... the feds became his only family.
In the weeks that followed Widener's recovery, he continued to learn about his federal job as an Economist. He also continued to participate in events involving his political friends back in California and his family back there.
This included a visit to a charity event held by the Pew Charitable Trusts. It was at this event that Widener sat next to Colin Powell's wife and was the same dinner table with her and Gregg Petersmeyer, who was also a friend of the family.
Gregg Petersmeyer is the chair of America’s Promise Alliance, a foundation he began with Colin Powell and others. Gregg learned that Widener was working at the Department of Labor. He leaned in and said to Stephen: "Tell the secretary I said hello."
So ... Widener ... well ... did what he was told. When he got back to his desk at the Bureau of Labor Statistics, he sent the Secretary of Labor Elaine Chao an email saying "hello." And would you believe she responded? Widener was so excited!
In the email that Widener wrote, he didn't shine the light on himself. He shined the light on his superiors. He congratulated them for giving him the support and encouragement he needed while working for the Consumer Price Index (CPI).
Widener still has the email.
The use of detail science is believed to have first showed up on the federal scene from within the Department of Labor's Bureau of Labor Statistics.
In 2003, the Department of Labor's Bureau of Labor Statistics was involved in the planning process for converting their paper-based data collection to electronic-based collection. The official term of this new approach to collecting pricing information for the United States Economy was dubbed Computer-Assisted Data Collection (CADC). With the introduction of this new electronic approach to data collection came additional database layers that sat on top of the mainframe that had been used to process the paper-collected data.
As a result, information became available for the first time for traditional database scripting against Microsoft Windows Operating System enterprise server databases. While the department that monitored data collection was receiving electronic reports drawn from the mainframe, this newly implemented electronic approach made it possible to do more.
It was Stephen Widener who envisioned, created, and implemented the first Structured Query Language (SQL) reports for the Department of Labor’s Bureau of Labor Statistics and used them to monitor live data collection for the Consumer Price Index (CPI).
The scripting was an extension of programs that Widener created for testing. The testing had resulted from when Widener was on the C.P.I. Systems Integration Team (SIT) that designed the infrastructure that was used in deploying the computer-assisted data collection system now used by the C.P.I.
When testing started for the new system yet to be developed, a Systems Integration Testing (SIT) team was created. For testing, Widener created simple SQL scripts to assist him with verifying data. Widener worked together with other team members to test data and assist the team with its project goals. Sometimes they would even work late into the evening, coming back to the office after taking a break after the work day was over.
After electronic data collection was implemented, Widener saw an opportunity to provide managers in the field with real-time feedback from live-data movements found in the new databases. The original databases were in the mainframe whereas the new ones were in a Windows Server environment, affording the opportunity for the first time in the history of the C.P.I. to access the data in a live manner. It is with this in mind that Widener expanded his original SQL scripts in more elaborate reports.
It is believed that these expanded SQL scripts are the first Detail Science products that were ever used by the Consumer Price Index (CPI).
Throughout the years Widener's accomplishments in this area have been well-documented and were instrumental in making history in the area of Federal S.T.E.M., Federal Big Data Projects, Federal Research, and Federal Live-Data Quality Control Monitoring.
In 2004, Widener made history within his department by receiving the largest bonus ever given to a department employee to date. Branch Chief Jane Martinez wrote:
"Stephen - in addition to your bonus you will be receiving a Quality Step Increase for your work in the past year. Your data mining and analytical skills are much appreciated. ... The full bonus amount is $4,000 before deductions. This is the highest bonus that I've ever had the pleasure to give. In addition to receiving the performance bonus for your Outstanding Rating, ... money was added to your bonus to reflect your special contributions to the organization. I want to thank you for your continued outstanding efforts on behalf of the CPI program. Your combination of enthusiasm, initiative, and intelligence would make you a star in any organization. I am very glad that you are in my organization." [Branch Chief, 2004.]
Then, in 2005, Widener's supervisor made some of the first official congratulatory comments in Widener's 2005 Performance Appraisal:
“Mr. Widener has worked independently of his supervisor to introduce database query tools to our daily monitoring activities. The ability to use these query tools for daily monitoring and problem investigation has taken the primary mission of our office to a new level. … He recognizes the importance of this activity to the Consumer Price Index (CPI) Program and is dedicated to providing our customers with the best tools to do their jobs. … Every month, Stephen continues to push the limits of his knowledge and creates solution that I never imagined.” [Supervisor, 2005.]
In the early 2000s, the Bureau of Labor Statistic's Consumer Price Index was in the process of boldly going where no survey had gone before ... electronic dat collection! Every one hoped to end the gigantic expense of overnight packages and endless "box-with-paper" drop offs all across the country.
As a recent addition to the team working for the Consumer Price Index, Mr. Widener was placed on several software development teams. He was placed on the Computer-Assisted Data Collection Systems Integration Team and later on the Computer-Assisted Data Collection Software Development Team.
Although Mr. Widener has never had any formal computer science training, he has always been familiar with technology. The first computer arrived at Mr. Widener's house back in 1975 after his father and his mother joined a White House Task Force that involved his father as Mayor of Berkeley. The first computer was a Wang PC with Multi-Plan and Multi-Mate ... and 5 1/4" large floppy disks as the storage devices. Mr. Widener learned to type as a toddler, sitting on his mother's lap. (Since she wouldn't leave the computer and was always busy ... Mr. Widener realized that the best way to spend time with his mother was to learn how to use the computer.)
Mr. Widener's lifelong experience with technology showed up over and over again as he continued to be placed on development teams and eventually also on the Consumer Price Index Production Team.
Mr. Widener had already been involved in software development work as a part of the data collection software teams mentioned, previously. But while on the production team Mr. Widener developed his first stand-alone system that he presented to the team.
Mr. Widener used the features he had already placed in one of his Microsoft Access party databases (from before he moved to DC) and added those same features to the production team's production log, which was created in Microsoft Access. He improved forms, created queries, added data entry restrictions, and wrote a manual.
The result was the that team members were compelled to enter information more completely. This resulted in more information coming to the team for production problems, and went a long way in improving the quality of data collection.
The word got out that Mr. Widener had overhauled the Consumer Price Index Production Problem Log.
This resulted in his being chosen by Senior Management to chair a team chartered to improve the problem reporting process. Mr. Widener worked with others to come up with the Quarterly Analysis Review System (QARS).
Mr. Widener modified the problem log data base to produce more reports and also added categorization so that the problems could be quantified, statistically.
The result was a new way of the team communicating with Senor Management and it was also well-received by team members.
As the years went on, Mr. Widener continued to enjoy his time spent working on the Consumer Price index.
He was added to the Acceptance Testing team and wrote dozens of test cases for the data collection software (in between flag football games, of course).
Mr. Widener also participated in research projects that used his understanding of technology to gain valuable information about the new database layers that drove electronic data collection. For example , Mr. Widener constructed and implemented a test of the system called the "TR Project." This research project allowed him to send data through the system and then time how long it took for the data to go from one place in the database layers to another.
The Consumer Price Index used this valuable information to construct proxies and measures for taking action when ever data flow fell out of a certain timeframe.
Throughout the years, Mr. Widener was exposed to several different kinds of software development lifecycle models. Mr. Widener was first involved in projects that used the
Waterfall Software Development Lifecycle Model and the Spiral Software Development Lifecycle Model.
The Waterfall Model is a linear, sequential approach to software development that uses a logical progression of steps for a project, similar to the direction water flows over the edge of a cliff.
The Spiral Model is an iterative approach to software development attempts to save time and mitigate risks involved in large-scale projects that can be both expensive and complicated.
Mr. Widener was later introduced to the Rational Unified Process Software Development Lifecyle Model through his membership on the Sample Maintenance System improvement project.
Rational Unified Process an Agile software development methodology. This model splits the project lifecycle into four phases. During each of the phases, all six core development disciplines take place: business modelling, requirements, analysis and design, implementation, testing, and deployment.
Mr. Widener wrote many of the Use Case documents for his department's functional role in the project. These documents were ultimately used to develop and deploy the software, and they were updated when ever a discrepancy was found that needed a repair.
Mr. Widener learned a lot about software development and design by being a part of these teams.
Mr. Widener also used his own instincts and creativity when participating in projects. For example, he was tasked with leading a team involved in making a feature change to the already-existing data collection software.
Mr. Widener knew that the change was something that the current developer of the software would know how to implement. And because the Consumer Price Index was already using the software, Mr. Widener decided to implement a Rapid Prototype Software Development Lifecycle Model for the team's work.
This was solely Mr. Widener's decision ... and the decision was well-received. The Rapid Prototype Model allowed him to let the developer take the lead on the feature change, implement it in her test environment, and then give it to Mr. Widener so he could reverse-construct the requirements and design documents.
This approach saved a lot of time and effort, and ensured that the new feature was implemented, properly.
Many people may not be aware that Cloud Computing was around for many years before the name was changed to "cloud computing." Cloud Computing was initially called "Thin Client Computing."
Thin Clients were computers that functioned by connecting to a server as opposed to be able to process information by themselves. Some people do not realize that this approach was originally the system used by the Mainframe. For example, in banks, they had "green terminals." If the connection went down, you couldn't make a bank deposit.
The personal computer decentralized computing so that each computer could process information, which led to the introduction of color and the "windows environment" which moved the entire world away from the "command prompt" computer screen.
However, eventually, computing became so advanced that it was possible to go back to centralized computing but still maintain a graphical mouse-driven colored and windowed environment. This is what prompted the growth of the new "mainframe" computing system: the thin client client-server based system.
The first company to develop technology in this manner was Citrix: they created Winframe and Metaframe for Microsoft Windows 3.11 and Windows NT, back in the 80s and the 90s. Microsoft entered in to a partnership with Citrix, and added members to the Board of Directors at Citrix. Then, they obtained the technology from Citrix and used it to create Windows Terminal Services.
Then, the competition began!
When Mr. Widener arrived in Washington, D.C., to start his career as an Economist, he was already familiar with thin client technology, including Independent Client Architecture and Remote Desktop Protocol. As a matter of fact, Mr. Widener had followed the stocks of several companies in this industry in the late 1990s and had read several books on the subject.
Therefore, when the Consumer Price Index moved to an electronic data collection infrastructure, Mr. Widener knew intuitively that the agency could save money by improving the system they had designed.
Mr. Widener has a proven ability to perform in-depth literature review, cultivate and maintain partnerships with stakeholders, plan and conduct stakeholder workshops and interviews.
Mr. Widener has always been a passionate member of the CPI community, therefore, in an effort to effect change, he researched and wrote a Cloud Computing research paper titled CPI Data and Wireless Host-Based Distributed Systems.
This research paper involved a detailed fact-finding journey that included research and analysis on data-collection-related technologies, as well as interviews with senior IT managers and seasoned IT professionals at the Bureau of Labor Statistics.
The research paper recommended that the CPI convert their dial-up client-server distributed system to a wireless host-based distributed system. The research paper also quantified that the Consumer Price Index could save millions of dollars per year by implementing this architecture.
After reading the research paper, here were some of the comments made by senior professions at the CPI community: on Thursday, March 1st, 2012 at 12:43pm, Senior Economist Jenny Rudd wrote “Simply fascinating!!”; on Thursday, October 8th, 2015 at 10:52am, Senior Security Specialist Lawrence Scott wrote “Great paper. … your logic is sound and very wise.”; on Monday, September 28th, 2015 at 5:43pm, Senior Computer Scientist Joshua Chapman wrote “Why wasn’t this implemented? We were looking to change the infrastructure to a more web-based model with a ‘thin client’ being a tablet that accessed the application through a browser. … This idea will take a long time to implement. But your idea? Yours would take less time and less development work.”
It was clear that Mr. Widener's idea was a smashing success, and he was excited to have sparked a conversation about this approach in the agency.
Mr. Widener enjoyed exposure to many different aspects of the Consumer Price Index, including being placed on teams that gave him opportunities to provide value.
Mr. Widener has a proven ability to support the evaluation, investigation, and analysis of market transformation strategies, including performing statistical analyses and model development.
As a member of the New Goods Initiative team, Mr. Widener was tasked with addressing concerns of “New Goods Bias and Substitution Bias” raised in the book, At What Price, written by the National Statistics Committee in cooperation with the Behavioral and Social Sciences and Education Commission.
As a result of Mr. Widener's individual efforts while on the team, he created a process for identifying which items needed to be included in Item Rotation processing for each quarter. Mr. Widener's process called for each item to be ranked according to economic factors in the marketplace as well as the item's relative importance in the Consumer Price Index.
The technique also called for disclosure of the source of that item’s bias in the Index (i.e., innovation, changes in distribution, or discontinuance).
But Mr. Widener did not end his innovative efforts here. After Item Rotation was underway, there was another team chartered to review the progress of the new samples. On this team, Mr. Widener developed the first-ever automated statistical model that could scientifically calculate the percentage of new items introduced in any given CPI data sample.
Mr. Widener called this tool the Initiation-in-Pricing Sample Evaluation Equation Tool (IPSEE). There was another tool that he created called RESEE, which was for the Re-Initiation sample. These tools ran in real-time against a fully functioning live Consumer Price Index database that was constantly receiving updated pricing information from all across the United States.
IPSEE and RESEE were examples of the first Data Science tools ever to be produced by Consumer Price Index. As a result of his efforts, Mr. Widener received a Good Job Award that stated: “[Stephen] made numerous contributions to the development of a new evaluation tool that for the first time will enable the CPI program to measure and assess the sample changes that are introduced into the CPI through the Item Rotation Initiative.”
Mr. Widener's statistical achievements continued when he was able to work on a regression research project. Mr. Widener possess a proven ability to support the evaluation, investigation, and analysis of emerging technologies, including performing statistical analyses and model development.
For the house price research, Mr. Widener analyzed single-family home prices within a Metropolitan Statistical Area. The project used the Census Bureau’s American Housing Survey dataset as well as their Codebook.
Mr. Widener used StatTransfer to convert the files into a format consistent with the STATA 8 Statistical software interface and then used the dataset’s summary statistics to validate the data. Next, Mr. Widener spent a good deal of time cleaning and standardizing the dataset using the reference material in the Codebook as well as standard statistical data concepts. Next, Mr. Widener conducted statistical analysis involving several multiple regression runs while observing each variable’s significance and sign, including programmatic tests for heteroscedasticity, multicollinearity, and omitted variables.
Finally, Mr. Widener created a final mathematical equation and model for predicting a house’s sales price and then validated the equation by plotting the model’s fitted values against its actual values.
Mr. Widener had eventually made a name for himself as an expert in technology.
(It was never these accolades that motivated Mr. Widener ... it was always the long walks, cookouts, birthday parties, and all of the other events that he was constantly invited to by his coworkers who he viewed as his family.)
Mr. Widener's technical knowledge landed him on the Sample Refinement Software Development Team, tasked with creating a streamlined process for dealing with address improvement. Mr. Widener invented a concept called "Orphan Processing" and it was introduced in to the Consumer Price Index sample creation process. And "orphan" was a record that "did not have a home." The new system was designed so that records could be moved from one place to another in the United States ... so that price records could be called in the right part of the United States for when it was time to collect the prices.
During this development process, however, developers realized that they did not know how to maintain the CPIs identifier-creation process. The CPI used a numbering scheme that managers and data collectors in the field were already familiar with. Mr. Widener was in a meeting with developers when he suggested that they used a "Two Sequence Object" for creating the identifying numbers.
Developers realized that the approach would work and they implemented it. As a result, all the managers and data collectors in the field were able to stay familiar with how the location records were numbered.
Mr. Widener spent almost two decades working f or the Consumer Price Index. For most of that time he had the same supervisor.
But in later years, Widener's supervisor left the Washington DC area and became a technical expert.
In his place, in 2011, the agency showed vision in making a bold move ... it hired its First-Ever African American Supervisor of Mr. Widener's division.
She spent several years as Widener's supervisor, where she oversaw and protected his continued efforts at database programming innovation. She commended Widener's outstanding performance on his 2011 Performance Appraisal:
"Mr. Widener has expertise in the area of database querying and created or re-wrote several scripts to improve the reporting process for the C&S Initiation survey and to solve a problem with incomplete PSU-level data. ... He provides assistance to several members of the CPI Operations Team to assist in their monitoring and problem-solving efforts. Mr. Widener prepared and presented the SQL lecture series which covered topics on script writing and the C&S CADC database variables. His topics and examples were relevant to the tasks performed by the CPI Operations Team." [Supervisor, 2011.]
Widener did not hesitate to return the favor and show gratitude towards her during her time as his department's supervisor.
During one busy week of work at the agency, Widener's supervisor was getting ready for a presentation on the department's new technology. It was an important presentation because every one who worked for the Consume Price Index were not necessarily supporting the approach.
Early Friday, Widener's supervisor was getting things ready, including preparing to fly out of town and also setting up her demonstration computer ... she would use it to illustrate the new techniques the department had been designing.
However, much to her surprise, the test computer had been set up with really crappy test data! Specifically, all of the store information was ... well ... bogus. The systems staff setting up the data did not fully realize what she was going to do with it, so, they figured it wasn't a big deal if they simply repeated the same exact phase for all of the data. It was "test data." Repeated for each field in the software, about 90,000 times.
The ridiculous level of repetition that Widener's supervisor found in her presentation data sent shock waves down her spine!
This was a disaster! Why? Because Widener's supervisor would not have been able to demonstration data collection actions with that data. Specifically, she would not have been able to illustrate how our new techniques made the job of our managers out in the field easier if the data did not show any kind of diversity. The data did not have different retail store names; it didn't have different addresses; it didn't have different outlet types. The people she would be trying to convince were already not being supportive.
In a panic, just several hours before the day was to end and she was to fly out of town for her presentation, she came in to Widener's office with the problem.
"Ok," Widener said: "So we can just replace it." "What?" Widener's supervisor asked. Widener then took the computer and connected it up to the main network inside the office. He used a back-door little-known technical "trick" to connect the local database to the consolidated database, and replaced about 90,000 records with diverse and detailed data. This gave his supervisor the ability to demonstrate the departments new techniques, property.
It went well at her presentation, and, to this day, the systems staff still wonder: "How did he update 90,000 records in just 2 hours?" Apparently, Widener doesn't "Diss and Tell." So, it's still a secret.
Widener and others in the department supported the accomplishments of the First African American Supervisor for Consumer Price Index (CPI) Operations. She was later rewarded by becoming the First African American Director of Operations for all of the Consumer Price Programs, which included the Producer Price Index, the Consumer Price Index, the Employment Cost Index, and others.
Widener went on to enjoy a lengthy career with the Department of Labor's Bureau of Labor Statistics, and continued to work under the outstanding direction that the agency provided with their multi-tiered forward-thinking management structure.
As time went on, Widener's accomplishments became more widely known throughout the agency. This resulted in it becoming commonplace for him to sometimes be the only non-manager on a all-management oversight group. He was also often the only person able to be able to deliver very important technical information, and was required to present stakeholder presentations to all six of the regional management groups throughout the United States responsible for Consumer Price Index (CPI) national data collection.
The problem ended up being that Widener was not cut out for high-level leadership ... he always preferred to be "Thurgood Marshall" not "Martin Luther King."
In the end, the added pressure of more and more responsibility started to weigh on his health. And in 2018, his deteriorating diabetic condition compelled him to depart from the agency. He was then able to slow down his routine and focus instead on a complete medical recovery.
Presently, Widener is happy and proud that his health problems have been solved and he is good spirits.
Nowadays, he can be found consulting in the private sector and dabbling in the entrepreneurial and entertainment world.
He enjoys learning about all kinds of new products, and also enjoys discovering new approaches to seemingly already-solved problems.
Besides the routine of traditional daytime work, Widener enjoys research, horseback riding, reading Economics books, and keeping up with technology. Oh ... and video games.
He also enjoys tending to his "side hustles" which include performing at local entertainment venues and running a few other online businesses.
Some people have invited Widener back to re-join the ranks of the 9-to-5, Monday - Friday, S.T.E.M. Working World ... back in the office.
Widener has always responded with the same comment: “If I go back to the office, I would prefer it to be with the feds. Once a fed; always a fed.”
Widener says it was with the feds where he found a life of meaning; that was where he found his calling. Widener always gives the same response when people ask him if he still thinks about the feds:
"It all started with the feds; no one will ever be able to take that truth away from me or any one else who was involved. And, absolutely, I still think about them. Every single day. I will always love all of them. To me, it is as simple that. They were my family. They are my family. They always will be my family. And anything I do code-wise from here on out is a result of support from the feds. Once a fed; always a fed.”
Stephen Widener was once asked about his feelings about his time at the Department of Labor's Bureau of Labor Statistics. He was quoted as saying:
"The BLS was never just a workplace for me. And the CPI was never just a job. It was my life. My whole life. My only life. I was there for it all: the September 11th bombings, the Sniper Shootings, and the long walks past the country's most breath-taking and awe-inspiring monuments on the National Mall. Being a fed was everything to me. And it always will be. Even now."
Widener was also asked if there was anything in particular about his time at the BLS of which he was most fond. Widener said:
"That's easy. The people. They were my dearest and closest friends. They were from all walks of life. We protected each other. It didn’t matter where we were from; we were from all over. But we were all feds. This is my S.T.E.M. family. Nerds of a feather will always flock together. Never another flock like a fed flock."
Widener was once asked if there were any special moments that stood out in his mind from his time with the feds. This is what he said:
[Quote]
Yes. Without a doubt. The moments were my director's giggles. There were several of those moments. But, the moments were always the same. And the moments were always with her.
You see, my Director was my boss's boss. And she was a certified beast … don’t mess with her. I was kinda like a beast of sorts, myself, too. But I didn't "beast it up" with class like she did. I was more of a maverick.
So, whenever I didn’t like the direction she was taking or something she had decided to do, I would let her know. If she didn't let me have my way, we would fight like cats and dogs. From the day she was promoted, I was a royal pain in her butt.
But, during a crisis or an emergency, there would be nothing but silence between us. Each time an instant unspoken partnership would magically develop. There would be long hours, long conversations, hard work, and togetherness. And we would fix it. What ever got broke. We would fix it.
And after the crisis was over, we would pick up where we left off ... with the tit for tat. (Or maybe it was just me starting things up, all over again, and not her.)
The point I am making is that there was sometimes a giggle. I mean, right in the thick of a disagreement, at just the right moment, when she was trying to be serious, I would let out just the right impromptu joke ... I would fire it off straight out of my mouth like a rocket. And if I timed it just right, no matter how serious she was trying to be ... she'd let out an involuntarily impromptu giggle.
And at that moment it would seem worth it. And each time I successfully pulled another incident of "giggle-gate" ... I felt that much more human. And it helped me see the humanity in her, too.
I will never forget the feds. I will never forget her. I will never forget the people. The laughs. The good. The bad. And the ugly. And every thing in between.
Those were the best days of my life. Once a fed. Always a fed.
[End Quote - Stephen Widener.]
Stephen Widener hopes that one day there will be more recognition for the federal government's role in creating the field of Detail Science and also the field of Data Science that evolved from it. Read below for some of specifics.
Stephen Widener hopes that one day there will be proper acknowledgement for all that has been put in to the creation of the Detail Sciences. Hopefully, God permitting, this will include the story of the transformation of Detail Science into Data Science. He looks forward to working with any person or group who would assist in making this dream a reality.
Widener hopes one day to witness the unveiling of an exhibit at the National Museum of Native American History (NMNH) in Washington, D.C. which would showcase his work as a Native American creator in the field of Detail Science.
Furthermore, Widener believes that artistic ability played a very important role in this journey. Therefore, he also hopes that there would one day be an exhibit for Detail Science in New York's Museum of Modern Art (NOMA).
Widener not only wants to be proud of what he was able to do, but he also wants the whole world to know that he did it for his country. Furthermore, without help, support, and the protection of his managers, friends, and coworkers at the federal government, none of it would have ever happened.
Widener also hopes to one day witness the unveiling of the first-ever Museum of Federal S.T.E.A.M. He would hope that this museum would showcase all the awesome things that federal employees have created; along with all that they have witnessed. And he hopes that the fact that it was a Jewish Manager who supported him throughout the entire process would also find its way in to the presentation.
Widener would want this museum to be presented in a manner that makes it clear that federal employees take risks; and these risks can be dangerous. There is the constant possibility of unauthorized access to critical infrastructure and the resulting life-threatening situations that can arise as a result. No other industry takes the kind of risks that federal employees must take.
According to Widener: "Everybody is always bad-mouthing the feds, but they've never been one. They wouldn't last a week doing what we do, or in the circumstances under under which we work."
The feds need to be acknowledged, thanked, and appreciated for the risks that they take for their country.
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