From 8664e03a87c72985458778003fd9d5ebed53cc84 Mon Sep 17 00:00:00 2001
From: Justin Gosses <JustinGOSSES@users.noreply.github.com>
Date: Sun, 28 Jun 2020 14:48:33 -0500
Subject: [PATCH 1/4] changed link from personal webpage to github as its more
 direct to code side projects

---
 bios/gosses.md | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/bios/gosses.md b/bios/gosses.md
index 0a87cdc..ca710ab 100644
--- a/bios/gosses.md
+++ b/bios/gosses.md
@@ -1 +1 @@
-Justin is a data scientist. As a S.A.I.C. contractor for NASA, he supports the Office of the Chief Information Officer's Data Analytics team infusing modern data analytics into the non-science and non-engineering parts of NASA though consulting and prototypes. He also supports NASA's open-innovation program focused on code sharing internally and externally. Before NASA, Justin spent ten years as an oil and gas geologist where he learned how to code after maxing out the memory on Excel too many times. Justin keeps one toe in geology via side projects, which you can checkout at http://justingosses.com/code.
+Justin is a data scientist. As a S.A.I.C. contractor for NASA, he supports the Office of the Chief Information Officer's Data Analytics team infusing modern data analytics into the non-science and non-engineering parts of NASA though consulting and prototypes. He also supports NASA's open-innovation program focused on code sharing internally and externally. Before NASA, Justin spent ten years as an oil and gas geologist where he learned how to code after maxing out the memory on Excel too many times. Justin keeps one toe in geology via side projects, which you can checkout at https://github.com/JustinGOSSES.

From 06168f8909869f6a97f0e5ca7a8ecd872f9cd37c Mon Sep 17 00:00:00 2001
From: Justin Gosses <JustinGOSSES@users.noreply.github.com>
Date: Sun, 28 Jun 2020 14:56:17 -0500
Subject: [PATCH 2/4] Justin's image for headshot

Justin's image for headshot
- yes, I know this isn't actually a headshot, but I don't like putting those on public web.
---
 headshots/justin_gosses.jpeg | Bin 0 -> 23325 bytes
 1 file changed, 0 insertions(+), 0 deletions(-)
 create mode 100644 headshots/justin_gosses.jpeg

diff --git a/headshots/justin_gosses.jpeg b/headshots/justin_gosses.jpeg
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From 5b98759451310ac306f3327f52340e2f026b7c84 Mon Sep 17 00:00:00 2001
From: Justin Gosses <JustinGOSSES@users.noreply.github.com>
Date: Sun, 28 Jun 2020 17:54:33 -0500
Subject: [PATCH 3/4] Rearranged paragraphs and some sentence for better flow
 as review suggested.

---
 chapters/Gosses.md | 21 ++++++++++-----------
 1 file changed, 10 insertions(+), 11 deletions(-)

diff --git a/chapters/Gosses.md b/chapters/Gosses.md
index 4a7f1e9..5ec0439 100644
--- a/chapters/Gosses.md
+++ b/chapters/Gosses.md
@@ -4,19 +4,18 @@ Justin Gosses
  
 > “If I have seen further, it is by standing on the shoulders of giants.” ~ Isaac Newton.
 
-Issac Newton wrote this to Robert Hooke, a British scientist, describing how his work built on the work of his predecessors. In science, we often think of these giants as old, dead, men in history books. In computer science, many of the giants of the field are still alive. In open-source, they are people you meet at conferences. In innersource, they are your coworkers who write code, including those you’ve never met.
+Issac Newton wrote this to Robert Hooke, a British scientist, describing how his work built on the work of his predecessors. In science, we often think of these giants as old, dead, men in history books. In computer science, many of the giants of the field are still alive. In open source, they are people you meet at conferences. In innersource, they are your coworkers who write code, including those you’ve never met.
 
+> Open-source software is released under a license in which the copyright holder grants users the rights to use, change, and distribute the software to anyone for any purpose. 
 
-Innersource refers to the sharing, reuse, and distributed development of code inside an organization. While open-source has proved its value in terms of better code through more eyeballs and leveraging mindshare to organize development of code without centralized control, open-source is hard for companies and especially hard for oil and gas. Lawyers get involved. Release processes are slow, non-existent, or written for the worst-case scenario. Innersource offers many of the benefits with less institutional pushback. It can also be a stepping stone to open-source.
+> Innersource refers to the sharing, reuse, and distributed development of code inside an organization. 
 
- 
-Oil and gas companies are adept at information sharing within disciplines geographically distributed in multiple offices, one level up and down the organization hierarchy, or among disciplines operating in a local area. However, innersource needs code sharing across the entire company, not just within the normal communication silos. Financial analysts and geoscientists both use Pandas, a Python library for data analysis. Petrophysicists and procurement analysts both use natural language processing to find patterns in corpuses of text documents too large to read one at a time. Traditional boundaries in oil and gas aren't helpful when it comes to sharing code. The distinguishing characteristics for useful groupings are tools and techniques, not discipline, geography, or upstream versus downstream.
- 
-Although innersource can be evaluated entirely through the lens of contributions to projects that augment the work of the team that originated the code, this would be a mistake. In a company that does innersource well, code is more secure, because there are more people reading it. Projects are written faster, because more code can be reused. As the rate of code reuse and external contributions increase, code users have heightened expectations for good documentation, and the original developers have a greater need for better test coverage. This results in more reliable and maintainable code. 
+While open source has proved its value in terms of better code through more eyeballs and leveraging mindshare to organize development of code without centralized control, open source is hard for companies and especially hard for oil and gas. Lawyers get involved. Release processes are slow, non-existent, or written for the worst-case scenario. Innersource offers many of the benefits as open source with less institutional pushback. It can also be a stepping stone to open source.
 
-Microservices are becoming increasingly preferred over monolithic architectures, partly to take advantage of previously written code. Microservices and APIs together can punch holes in data silos, allowing data to flow more easily across the boundaries of software and people systems. GUI-based software tools that are already paid for can be leveraged to provide even more value when small scripts that can augment their capabilities are shared widely. When more people can find examples of similar code being written by others, opportunities for mentorship increase, development time decreases, and sparsely distributed expert knowledge can more efficiently be distributed to where it is needed.
- 
-A centralized enterprise instance of Github, Gitlab, or Bitbucket running behind the company firewall is the well-established answer to how to start innersourcing. However, organizational culture is likely to be the critical hurdle rather than tool choice. Managers need to give permission to contribute to projects outside of their main objectives and manage unplanned pull requests. It is not uncommon for code sharing tools to sprout up multiple times in large organizations, generating the need to enforce a single option or have methods for discoverability across platforms. Finding similar code projects and developers can be a challenge. A company-wide chat tool that enables topic-based communication can help connect people who in different organization. Recommendation engines that use enterprise code repositories to connect people writing similar code are an attractive idea, though there are not yet any off-the-shelf solutions.
- 
-There are a lot more young people who know how to program today, and many mid-career people are learning how to code, partly as a result of increasing interest in data science. As more people gain coding skills, and the time needed to write code decreases, the amount of code written will increase, the location of people writing code in the organization will radically diversify, and the need for effective means to share and manage code across large organizations will become more pressing. All oil and gas companies will eventually have an innersource program. The companies that implement a good innersource program soon will be at an advantage. When you can stand on the shoulders of someone in a different office, and they can stand on your shoulders, you can both make progress very quickly.
+Oil and gas companies are adept at information sharing up and down an organizational hierarchy and across the company within discipline groups. However, innersource needs code sharing across the entire company, not just within the normal communication silos. Financial analysts and geoscientists both use Pandas, a Python library for data analysis. Petrophysicists and procurement analysts both use natural language processing to find patterns in corpuses of text documents too large to read. Traditional boundaries aren't helpful when it comes to sharing code. The distinguishing characteristics for useful groupings are tools and techniques, not discipline, geography, or business unit. Being able to find and discover code written outside your own team or discipline is a necessary part of an effective innersource program.
+
+A centralized enterprise instance of Github, Gitlab, or Bitbucket running behind the company firewall is the well-established answer to how to start innersourcing. However, it is not uncommon for multiple code sharing systems to sprout up in large organizations, leading to many people only seeing a portion of the code projects. This generates the need to either enforce a single option or have methods for discoverability across platforms. Scrappers that grab metadata from code repositories and provide it at a central location is one method to ensure discovery.  Recommendation engines that use enterprise code repositories to connect people writing similar code are an attractive idea, though there are not yet any off-the-shelf solutions in 2019.
+
+Success in inner-source is difficult to measure. Although innersource can be quantified through the number of code contributions to existing projects from outside the original team, this only captures a small slice of the actual benefits. In a company that does innersource well, code is more secure, because there are more people reading it. Projects are written faster, because more code can be reused. As the rate of code reuse and external contributions increase, code users have heightened expectations for good documentation, and the original developers have a greater need for better test coverage. This results in more reliable and maintainable code. Code sharing also enables more effective use of data systems. Microservices are becoming increasingly preferred over monolithic architectures, partly to take advantage of previously written code. Shared microservices and APIs together can punch holes in data silos, allowing data to flow more easily. Small scripts shared between power users can augment the capabilities of costly GUI-based software tools. When more people can find examples of similar code being written by others, opportunities for mentorship increase, development time decreases, and sparsely distributed expert knowledge can more efficiently be distributed to where it is needed.
 
+As the number of people who can code continues to climb and the time required to write useful code decreases, the amount of code written inside organizations will increase, the disciplines of people writing code will diversity, and the need for effective means to share and discover code across large organizations will become even more pressing. All large organizations will eventually have an innersource program. The companies that implement a good innersource program earlier will be at an advantage. When you can stand on the shoulders of someone in a different office, and they can stand on your shoulders, you can both make progress very quickly.

From 24a89336cae4717ed35e7306e617149163d89df2 Mon Sep 17 00:00:00 2001
From: Justin Gosses <JustinGOSSES@users.noreply.github.com>
Date: Sun, 28 Jun 2020 18:26:12 -0500
Subject: [PATCH 4/4] small word changes for style purposes

---
 chapters/Gosses.md | 6 +++---
 1 file changed, 3 insertions(+), 3 deletions(-)

diff --git a/chapters/Gosses.md b/chapters/Gosses.md
index 5ec0439..9d8a735 100644
--- a/chapters/Gosses.md
+++ b/chapters/Gosses.md
@@ -12,10 +12,10 @@ Issac Newton wrote this to Robert Hooke, a British scientist, describing how his
 
 While open source has proved its value in terms of better code through more eyeballs and leveraging mindshare to organize development of code without centralized control, open source is hard for companies and especially hard for oil and gas. Lawyers get involved. Release processes are slow, non-existent, or written for the worst-case scenario. Innersource offers many of the benefits as open source with less institutional pushback. It can also be a stepping stone to open source.
 
-Oil and gas companies are adept at information sharing up and down an organizational hierarchy and across the company within discipline groups. However, innersource needs code sharing across the entire company, not just within the normal communication silos. Financial analysts and geoscientists both use Pandas, a Python library for data analysis. Petrophysicists and procurement analysts both use natural language processing to find patterns in corpuses of text documents too large to read. Traditional boundaries aren't helpful when it comes to sharing code. The distinguishing characteristics for useful groupings are tools and techniques, not discipline, geography, or business unit. Being able to find and discover code written outside your own team or discipline is a necessary part of an effective innersource program.
+Oil and gas companies are adept at information sharing up and down an organizational hierarchy and across the company within discipline groups. However, innersource needs code sharing across the entire company, not just within the normal communication silos. Financial analysts and geoscientists both use Pandas, a Python library for data analysis. Petrophysicists and procurement analysts both use natural language processing to find patterns in corpuses of text documents too large to read. Traditional boundaries aren't helpful when it comes to sharing code. The distinguishing characteristics for useful groupings are tools and techniques, not discipline, geography, or business unit. Being able to find and discover code written anywhere in an organization is a necessary part of an effective innersource program.
 
-A centralized enterprise instance of Github, Gitlab, or Bitbucket running behind the company firewall is the well-established answer to how to start innersourcing. However, it is not uncommon for multiple code sharing systems to sprout up in large organizations, leading to many people only seeing a portion of the code projects. This generates the need to either enforce a single option or have methods for discoverability across platforms. Scrappers that grab metadata from code repositories and provide it at a central location is one method to ensure discovery.  Recommendation engines that use enterprise code repositories to connect people writing similar code are an attractive idea, though there are not yet any off-the-shelf solutions in 2019.
+A centralized enterprise instance of Github, Gitlab, or Bitbucket running behind the company firewall is the typical answer for how to start innersourcing. However, it is not uncommon for multiple code sharing systems to sprout up in large organizations, leading to many people only seeing a portion of the code projects. This generates the need to either enforce a single option or have methods for discoverability across platforms. Scrappers that grab metadata from code repositories and provide it at a central location is one method to ensure discovery.  Recommendation engines that use enterprise code repositories to connect people writing similar code is another idea, though there are not yet any off-the-shelf solutions in 2019.
 
-Success in inner-source is difficult to measure. Although innersource can be quantified through the number of code contributions to existing projects from outside the original team, this only captures a small slice of the actual benefits. In a company that does innersource well, code is more secure, because there are more people reading it. Projects are written faster, because more code can be reused. As the rate of code reuse and external contributions increase, code users have heightened expectations for good documentation, and the original developers have a greater need for better test coverage. This results in more reliable and maintainable code. Code sharing also enables more effective use of data systems. Microservices are becoming increasingly preferred over monolithic architectures, partly to take advantage of previously written code. Shared microservices and APIs together can punch holes in data silos, allowing data to flow more easily. Small scripts shared between power users can augment the capabilities of costly GUI-based software tools. When more people can find examples of similar code being written by others, opportunities for mentorship increase, development time decreases, and sparsely distributed expert knowledge can more efficiently be distributed to where it is needed.
+Success in inner-source is difficult to measure. Although innersource can be quantified in terms of the number of code contributions to existing projects from outside the original team, this only captures a small slice of the actual benefits. In a company that does innersource well, code is more secure, because there are more people reading it. Projects are written faster, because more code can be reused. As the rate of code reuse and external contributions increase, code users have heightened expectations for good documentation, and the original developers have a greater need for better test coverage. This results in more reliable and maintainable code. Code sharing also enables more effective use of data systems. Microservices are becoming increasingly preferred over monolithic architectures, partly to take advantage of previously written code. Shared microservices and APIs together can punch holes in data silos, allowing data to flow more easily. Small scripts shared between power users can augment the capabilities of costly GUI-based software tools. When more people can find examples of similar code being written by others, opportunities for mentorship increase, development time decreases, and sparsely distributed expert knowledge can more efficiently be distributed to where it is needed.
 
 As the number of people who can code continues to climb and the time required to write useful code decreases, the amount of code written inside organizations will increase, the disciplines of people writing code will diversity, and the need for effective means to share and discover code across large organizations will become even more pressing. All large organizations will eventually have an innersource program. The companies that implement a good innersource program earlier will be at an advantage. When you can stand on the shoulders of someone in a different office, and they can stand on your shoulders, you can both make progress very quickly.