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文件名称：Developing Quality Metadata
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更新时间：2014-04-06 16:24:44
Developing Quality Metadata
Data and metadata drives the TV production and broadcast scheduling systems. Metadata
helps to manage content and when you examine a broadcast infrastructure, a lot of what
is happening is to do with the manipulation of nonvideo data formats. Interactive TV and
digital text services also require data in large quantities. Managing it, cleaning it, routing it
to the correct place at the right time and in the right format are all issues that are familiar
to data management professionals inside and outside the media industry.
While I wrote this book, I spent a little time working with some developers who build
investment-banking systems. Interestingly they face identical problems to my colleagues
in broadcasting. I suspected this was the case all along because I have frequently deployed
solutions in broadcasting that I learned from projects in nonbroadcast industries. Spend
some ‘sabbatical’ time in another kind of industry. It will teach you some useful insights.
Workflow in an organization of any size will be composed of many discrete steps.
Whether you work on your own or in a large enterprise, the processes are very similar.
The scale of the organization just dictates the quantity. The quality needs to be maintained
at the highest level in both cases. The Data and Metadata Workflow Tools you choose and
use are critical to your success.
The key word here is Tools. With good tools, you can “Push the Envelope” and raise
your product quality.
There has been much discussion about metadata systems and data warehouses.
Systems used as data repositories are useful but if you don’t put good quality data in there
you are just wasting your time. We need to focus on making sure the data is as good as
possible—and stays that way.
Raw data is often in somewhat of a mess. There are a series of steps required to clean
the data so it can be used. Sometimes even the individual fields need to be broken down
so that the meaning can be extracted. This book is not so much about storage systems but
more about what gets stored in them.
There are defensive coding techniques you can use as avoidance strategies. There are
also implications when designing database schemas. Data entry introduces problems at
the outset and needs to be as high quality as possible or the entire process is compromised.
The book describes risk factors and illuminates them with real-world case examples and
how they were neutralized. Planning your systems well and fixing problems before they
happen is far cheaper than clearing up the mess afterwards.
This book is designed to be practical. If nontechnical staff read it, they will understand
why some of the architectural designs for their systems are hard to implement. For
people in the implementation area, they will find insights that help solve some of the
issues that confront them. A lot of the advice is in the form of case studies based on genuine
experience of building workflows. Some explanation is given about the background to
the problem and why it needs to be solved.
The material is divided into two parts. Part 1 deals with theory while Part 2 provides
many practical examples in the form of tutorials.
We lay a foundation for further projects that look inside the media files and examine
audio/video storage and the various tools that you can build for manipulating them.
Before embarking on that, we need to manage a variety of data and metadata components
and get that right first.