Archive for the ‘Versioning’ Category

Delta-flora for IntelliJ

Sunday, March 31st, 2013

Delta-flora for IntelliJ

From the webpage:

What is this?

This is a plugin for IntelliJ to analyze project source code history. It has two parts:

  • transforming VCS history into .csv format (csv because it’s easy to read and analyze afterwards)
  • analyzing history and displaying results using d3.js (requires a browser). This is currently done in a separate Groovy script.

Originally inspired by Delta Flora by Michael Feathers. It has now diverged into something a bit different.

WARNING: this is work-in-progress.

Why?

There seems to be a lot of interesting data captured in version control systems, yet we don’t tend to use it that much. This is an attempt to make looking at project history easier.

Interesting for visualization of project version control but I mention it as relevant to data versioning.

What if in addition to being in narrative prose, “facts,” such as claims about “yellow cake” uranium, were tracked by data versioning?

So that each confirmation or uncertainty is liked to a particular fact. Who confirmed? Who questioned?

There is a lot of data but limiting to to narrative structures means reduced access to track, re-structure and re-purpose that data.

A step in the right direction would be to produce both narrative and more granular forms of the same data.

Are there lessons we can draw from project source control?

Meld

Monday, December 3rd, 2012

Meld

From the webpage:

What is Meld?

Meld is a visual diff and merge tool targeted at developers. Meld helps you compare files, directories, and version controlled projects. It provides two- and three-way comparison of both files and directories, and has support for many popular version control systems.

Meld helps you review code changes and understand patches. It might even help you to figure out what is going on in that merge you keep avoiding

Features

  • Two- and three-way comparison between files and directories
  • Auto-merge mode (in development version)
  • Comparisons update as you type
  • Visualisations make it easier to compare your files
  • Actions on diff chunks make for easier merges
  • Supports Git, Bazaar, Mercurial, Subversion, etc.
  • …and more

Coming on the heels of Kevlin Henney’s Cool Code [Chess Program in 4.8 Tweets], I may have paid closer attention to this program than otherwise.

Still, source code has semantics and different ways of expressing those semantics, just like the usual topic map examples.

I first saw this in a tweet by Scientific Python.

Era of the Interest Graph

Tuesday, March 15th, 2011

Era of the Interest Graph

From the blog:

Social media is maturing as are the people embracing its most engaging tools and networks. Perhaps most notably, is the maturation of relationships and how we are expanding our horizons when it comes to connecting to one another. What started as the social graph, the network of people we knew and connected to in social networks, is now spawning new branches that resemble how we interact in real life.

This is the era of the interest graph – the expansion and contraction of social networks around common interests and events. Interest graphs represent a potential goldmine for brands seeking insight and inspiration to design more meaningful products and services as well as new marketing campaigns that better target potential stakeholders.

While many companies are learning to listen to the conversations related to their brands and competitors, many are simply documenting activity and mentions as a reporting function and in some cases, as part of conversational workflow. However, there’s more to Twitter intelligence than tracking conversations.

We’re now looking beyond the social graph as we move into focused networks that share more than just a relationship.

What struck me about this post was the sense that the graph was a non-stable construct.

Whereas most of the topic maps I have seen are not only stable, but their subjects are as well.

Which is fine for some areas of information, but not all.

A dynamic topic map seems to have different requirements than one that is a fixed editorial product, or at least it seems so to me.

Rather than versioning, for example, a dynamic topic map should have a tracking mechanism to show what information was available at any point in time.

So that say a physician relying upon a dynamic topic map for drug warning information can establish that a warning was or was not available at the time he prescribed a medication.

Oh, that’s not commonly possible even with static topic maps is it?

Hmmm, will have to give some thought to that issue.

It may just be the maps I have looked at but there is a timeless nature to them.

Much like governments, whatever is the case has always been the case. And if you remember differently, well, you are just wrong. If not subversive.