6 ms·

This kind of history is so important, and even this fairly recent history seems kind of hard to access. I am curious how you learned it? (Books? Articles? Findi

This kind of history is so important, and even this fairly recent history seems kind of hard to access. I am curious how you learned it? (Books? Articles? Finding people involved to interview? usenet posts?) I learned almost none of it in my formal computer science education in the laste 90s -- maybe because at that time it was recent enough that "middle-aged prime of their career" people still remembered it, it didn't seem necessary to teach it to newcomers as "history". I wonder how much post-1950 history is taught in current undergrad CS programs, like if a "databases" course will include a summary of any of the material you summarize.

shimonabi 5y ago
I was taught exactly this history in my college DB course in Slovenia. I even had to know the years when each model was proposed and by whom.
gnuvince 5y ago
You can read this article by Michael Stonebraker about the evolution of database systems: https://people.cs.umass.edu/~yanlei/courses/CS691LL-f06/papers/SH05.pdf https://people.cs.umass.edu/~yanlei/courses/CS691LL-f06/pape.... It's the first article in the Red Book[1]. [1] http://www.redbook.io/ http://www.redbook.io/
- dunkelheit 5y ago
  We left the exact same comment :)
dunkelheit 5y ago
There is quite a lot about DBMS history in the Red Book and references therein: http://www.redbook.io/index.html http://www.redbook.io/index.html For the history of data model proposals in particular, there is this paper: https://scholar.google.com/scholar?cluster=7366182905777149494 https://scholar.google.com/scholar?cluster=73661829057771494... So the info is definitely out there if you are interested in that sort of thing.
Sharlin 5y ago
History of science, as a scholarly discipline, is unfortunately rather decoupled from science (or engineering) itself. Practitioners of a field are rarely as interested in the field's history as they probably should. History of CS in particular has not attracted much academical interest even among science historians, possibly due to its relative youth and technical nature.
- seirl 5y ago
  It's a good thing that the two are separate. You really want good scientific advances to be put in textbooks, and the rest should be left for history books. You really don't want to have the scientific debate get muddled in pointless historical fights like in heterodox economics where people are still debating what mArX rEaLlY mEaNt centuries later. Scientists should read textbooks that reflect the current state of the art, not 40 years old papers that will necessarily be flawed.
  - Sharlin 5y ago
    That only works if you assume a linear model of scientific progress. Those who don't know history are doomed to repeat it, and this is extremely evident in the field of software engineering (granted, SE is not science and not even a good example of an engineering discipline) where old wisdoms are forgotten and then reinvented every five years.
geophile 5y ago
Lived it. I remember taking my first course on databases, in 1977, and feeling like I was hopelessly and permanently behind because it had been seven years since Codd's paper. I taught an intro database course recently, and only touched on some of that history. It wasn't the main point, and it was an undergrad course. But you point out a real problem. There is so much reinvention by people who simply don't know what was done previously. * I have seen research I did in the 70s/80s get redone in the last 20 years, with no awareness that the problem had already been solved. * I saw a horrifying takedown at an academic conference, (late 80s?) Someone on the original System R research team was pretty furious at a young researcher for being completely oblivious to the fact that he had repeated some System R work. (He blamed the conference reviewers as much as the author.)
- spockz 5y ago
  My late professor used to lament quite a lot about work being redone. Not a week went by without one or two papers/submissions/talks/works being mentioned with an immediate followup like “this is the same as this paper from the 70/80/90” or “this is the same as this paper by that author”. I found it quite sad, both because of the apparent double work and because this whole catalogue of computer science material went unused because of the tirades instead of their being a constructive way to share it. Although I very well can imagine the frustration, as I have seen the same things with libraries being reinvented, I think there is value in revisiting some problems in a different context. Maybe the problems are just not that of a big deal anymore in newer languages/eco systems even though they are fundamentally the same problem as in the 70s.
  - geophile 5y ago
    Of course there is value in revisiting a problem. But you should know that you're doing it, and be able to say how your work relates to the earlier work. (Not denying that reimplementing things can be fun ...)
    - leetrout 5y ago
      I think some of it is pure exposure. Developing a new interest in a topic can be inspirational to build things and without adequate access to prior art or knowing the right search terms can leave you lost and ignorant.
pmcjones 5y ago
More history here: https://www.mcjones.org/System_R/SQL_Reunion_95/ https://www.mcjones.org/System_R/SQL_Reunion_95/
tuatoru 5y ago
The Association for Computing Machinery[1] (usually "ACM") seems to be nearly invisible now. It was the forum for advancing the state of the art in those days. Its archives are primary sources for this history. The database debate was carried out mostly in ACM SIGMOD, the "Special Interest Group for Management of Data". 1. https://www.acm.org/ https://www.acm.org/
amw-zero 5y ago
Some references to the state of the data world in the 70s is found Codd’s initial paper itself: https://www.seas.upenn.edu/~zives/03f/cis550/codd.pdf https://www.seas.upenn.edu/~zives/03f/cis550/codd.pdf. I strongly recommend everyone pick up basic set theory notation so that you can read seminal papers like these. There is so much amazing information in them, yet they’re treated as if they’re incomprehensible. You can understand the relational model with undergraduate-level discrete math and set theory knowledge. These are the papers that formed our industry. Let’s not forget them.
saghm 5y ago
> I wonder how much post-1950 history is taught in current undergrad CS programs, like if a "databases" course will include a summary of any of the material you summarize. My databases course (circa 2014 or so) covered the gist of this; we didn't spend much time talking about database systems before it, but we read the Codd paper and discussed how various companies began working on implementations over the next couple of decades.
lstodd 5y ago
> This kind of history is so important, and even this fairly recent history seems kind of hard to access. I am curious how you learned it? This sort of touches upon the general inadequacy of CS education in general. The way I learned all this history is by digging it up myself, that was in early 2000s - old journals, papers, listening to people who witnessed all this themselves. That's the cornerstone skill that should be taught - research and the understanding that no single course can give you much in actual knowledge, only skill to acquire it.

shimonabi 5y ago

I was taught exactly this history in my college DB course in Slovenia. I even had to know the years when each model was proposed and by whom.

gnuvince 5y ago

You can read this article by Michael Stonebraker about the evolution of database systems: https://people.cs.umass.edu/~yanlei/courses/CS691LL-f06/papers/SH05.pdf https://people.cs.umass.edu/~yanlei/courses/CS691LL-f06/pape.... It's the first article in the Red Book[1]. [1] http://www.redbook.io/ http://www.redbook.io/

dunkelheit 5y ago
We left the exact same comment :)

dunkelheit 5y ago

There is quite a lot about DBMS history in the Red Book and references therein: http://www.redbook.io/index.html http://www.redbook.io/index.html For the history of data model proposals in particular, there is this paper: https://scholar.google.com/scholar?cluster=7366182905777149494 https://scholar.google.com/scholar?cluster=73661829057771494... So the info is definitely out there if you are interested in that sort of thing.

Sharlin 5y ago

History of science, as a scholarly discipline, is unfortunately rather decoupled from science (or engineering) itself. Practitioners of a field are rarely as interested in the field's history as they probably should. History of CS in particular has not attracted much academical interest even among science historians, possibly due to its relative youth and technical nature.

seirl 5y ago
It's a good thing that the two are separate. You really want good scientific advances to be put in textbooks, and the rest should be left for history books. You really don't want to have the scientific debate get muddled in pointless historical fights like in heterodox economics where people are still debating what mArX rEaLlY mEaNt centuries later. Scientists should read textbooks that reflect the current state of the art, not 40 years old papers that will necessarily be flawed.
- Sharlin 5y ago
  That only works if you assume a linear model of scientific progress. Those who don't know history are doomed to repeat it, and this is extremely evident in the field of software engineering (granted, SE is not science and not even a good example of an engineering discipline) where old wisdoms are forgotten and then reinvented every five years.

geophile 5y ago

Lived it. I remember taking my first course on databases, in 1977, and feeling like I was hopelessly and permanently behind because it had been seven years since Codd's paper. I taught an intro database course recently, and only touched on some of that history. It wasn't the main point, and it was an undergrad course. But you point out a real problem. There is so much reinvention by people who simply don't know what was done previously. * I have seen research I did in the 70s/80s get redone in the last 20 years, with no awareness that the problem had already been solved. * I saw a horrifying takedown at an academic conference, (late 80s?) Someone on the original System R research team was pretty furious at a young researcher for being completely oblivious to the fact that he had repeated some System R work. (He blamed the conference reviewers as much as the author.)

spockz 5y ago
My late professor used to lament quite a lot about work being redone. Not a week went by without one or two papers/submissions/talks/works being mentioned with an immediate followup like “this is the same as this paper from the 70/80/90” or “this is the same as this paper by that author”. I found it quite sad, both because of the apparent double work and because this whole catalogue of computer science material went unused because of the tirades instead of their being a constructive way to share it. Although I very well can imagine the frustration, as I have seen the same things with libraries being reinvented, I think there is value in revisiting some problems in a different context. Maybe the problems are just not that of a big deal anymore in newer languages/eco systems even though they are fundamentally the same problem as in the 70s.
- geophile 5y ago
  Of course there is value in revisiting a problem. But you should know that you're doing it, and be able to say how your work relates to the earlier work. (Not denying that reimplementing things can be fun ...)
  - leetrout 5y ago
    I think some of it is pure exposure. Developing a new interest in a topic can be inspirational to build things and without adequate access to prior art or knowing the right search terms can leave you lost and ignorant.

pmcjones 5y ago

More history here: https://www.mcjones.org/System_R/SQL_Reunion_95/ https://www.mcjones.org/System_R/SQL_Reunion_95/

tuatoru 5y ago

The Association for Computing Machinery[1] (usually "ACM") seems to be nearly invisible now. It was the forum for advancing the state of the art in those days. Its archives are primary sources for this history. The database debate was carried out mostly in ACM SIGMOD, the "Special Interest Group for Management of Data". 1. https://www.acm.org/ https://www.acm.org/

amw-zero 5y ago

Some references to the state of the data world in the 70s is found Codd’s initial paper itself: https://www.seas.upenn.edu/~zives/03f/cis550/codd.pdf https://www.seas.upenn.edu/~zives/03f/cis550/codd.pdf. I strongly recommend everyone pick up basic set theory notation so that you can read seminal papers like these. There is so much amazing information in them, yet they’re treated as if they’re incomprehensible. You can understand the relational model with undergraduate-level discrete math and set theory knowledge. These are the papers that formed our industry. Let’s not forget them.

saghm 5y ago

> I wonder how much post-1950 history is taught in current undergrad CS programs, like if a "databases" course will include a summary of any of the material you summarize. My databases course (circa 2014 or so) covered the gist of this; we didn't spend much time talking about database systems before it, but we read the Codd paper and discussed how various companies began working on implementations over the next couple of decades.

lstodd 5y ago

> This kind of history is so important, and even this fairly recent history seems kind of hard to access. I am curious how you learned it? This sort of touches upon the general inadequacy of CS education in general. The way I learned all this history is by digging it up myself, that was in early 2000s - old journals, papers, listening to people who witnessed all this themselves. That's the cornerstone skill that should be taught - research and the understanding that no single course can give you much in actual knowledge, only skill to acquire it.