On Feb 15, 2013, at 12:27 PM, Kyle Banerjee wrote:
> On Fri, Feb 15, 2013 at 6:45 AM, Diane Hillmann <[log in to unmask]>wrote:
>> I'm all for people learning to code if they want to and think it will help
>> them. But it isn't
>> the only thing library people need to know, and in fact, the other
>> key skill needed is far rarer: knowledge of library data...
>> ...More useful, I think, is for each side of that skills divide to value
>> the skills
>> of other other, and learn to work together....
> Well put. No amount of technical skill substitutes for understanding what
> people are actually doing -- it's very easy to write apps that nail any set
> of specifications and then some but are still totally useless.
> Even if you never intend to do any programming, it's still useful to know
> how to code because it will help you know what is feasible, what questions
> to ask, what is feasible, and how to interpret responses.
> That doesn't mean you need to know any particular language. It does mean
> you need to grok the fundamental methodologies and constraints.

And the vocabulary (which Alison also mentioned, but for those who read
Stranger in a Strange Land know that 'grok' was also associated with
understanding the language to be able to explain what something was.)

I've had *way* too many incidents where the problem was simply
mis-communication because one group was using a term that
had a specific meaning to the other group with some other intended
meaning.  I even gave a talk last year on the problem:

And one of the presenters earlier that night touched on the issue,
for scientists talking to politicians and the public:

It takes more than just people skills to coordinate between the 
customers & the software people.*  Being able to translate between
the problem domain's jargon and the programmers (possibly via some
requirements language, like UML), or even just normalizing metadata
between the sub-communities is probably 25-50% of my work.

As a quick example, there's 'data' ... it means something completely
different if you're dealing with scientists, programmers, or
information scientists.  For the scientists, metadata vs. data is
a legitimate distinction as not all of what programmers would
consider 'data' is considered to be 'scientific data'.