This is my comp-sci-stuff blog, for more general essays on issues of applied computer science.
If you are interested in material more specific to the Vilno Table programming language, and why it can help get work done five times faster than the SAS programming language, my other blog is:
http://fivetimesfaster.blogspot.com
That blog has a more specific focus.
For more general issues of statistical software and data programming languages, I'll use the blog you are looking at.
Robert
Tuesday, August 7, 2012
Wednesday, May 2, 2012
Vilno Table Programming Language White Paper
Here is a link to the
"Vilno Table Programming Language White Paper"
It is a .PDF file stored in a Google Documents area :
https://docs.google.com/open? id= 0B2oCqHJ9cxhCNkp2T0dnMFFBdlE
Rather than viewing it in the Google Documents area, download it and open it after downloaded, the viewing within Google Docs of a .PDF file might show a couple of pages as blurry.
The first 8 table examples in the appendix are the most intuitive way to get a feel for how this language works.
"Vilno Table Programming Language White Paper"
It is a .PDF file stored in a Google Documents area :
https://docs.google.com/open?
Rather than viewing it in the Google Documents area, download it and open it after downloaded, the viewing within Google Docs of a .PDF file might show a couple of pages as blurry.
The first 8 table examples in the appendix are the most intuitive way to get a feel for how this language works.
Tuesday, March 27, 2012
Data Languages: So Much To Fix
Computer programmer:
"Too much imagination can be disruptive"
Programming Language Researcher:
"Too little imagination can have harmful long term effects"
Data-focused programming languages include both data management programming languages (SQL) and statistical programming languages ( SAS and R(same as S) ). (Also variants of PL/SQL and also MDX). Because of data preparation issues, the two categories overlap.
Since the mid-1980s, there has been very little fundamental research and development in the subject of data languages. The over-hyping of SQL/relational might be the most important contributing factor.
The result is: pretty serious worker efficiency problems present 25 years ago that remain unsolved today.
The four most important obstacles for the end-user doing data-related work are:
1: Usability (learning curve and readability)
2: Worker productivity
3: Flexibility
4: Reliability (in the QA/reproducibility sense)
My name is Robert Wilkins, I am a statistical programming language researcher, and I am here to solve your problems.
For the purpose of statistical table production, in the context of worker productivity, I've already designed and implemented a new language that blows the SAS programming language out of the water.
But there is also data cleaning , a more multi-faceted and difficult area of research. There are obvious things that can be done, in the relative short-term, that would greatly benefit scientific researchers, among others. It is, however, a difficult subject that requires long-term research efforts as well. I am well aware that SQL is the only open-standard well known data-handling programming language, but that fact was a mistake. SQL (or SQL alone) is not a good enough solution for handling data preparation work efficiently.
Sunday, February 26, 2012
Nothing Special
this blog is for more general comp-sci and programming language stuff than the fivetimesfaster blog.
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