Tips to manage a spatial data library.
In private organizations, the CDO, or Chief Digital Officer, is a job that didn't exist just a few years ago and is still evolving. They help companies adopt technology, manage digital resources, and get the biggest bang for buck out of the online economy, among other things. Spatial data management in particular is so important to the success of organizations these days, in the European Union, the INSPIRE directive was created to standardize the approach for the benefit of public policy makers across the entire European community, with full implementation expected by 2019.
If you're in the position to set up a modern spatial data department for your company, large or small, here's a few underlying basic principles to keep in mind:
The general steps you'll go through:
Determine what you've got, what condition and format its in, how it's stored and what your future needs might be.
Define the specific goals and requirements, design a structure and strategy to bring everything together. Make sure it will be accessible to those who need it and easy to keep up to date.
Set up the basic infrastructure for your plan and test it to make sure it's going to do what you want. Make adjustments to the plan before going further.
Go ahead and migrate your data over, then deprecate the old system.
Schedule the life cycle of data and automate the process wherever possible.
Five simple steps. Easy! A few considerations to watch out for along the way:
Old habits die hard. Old digital formats, even paper maps will need to be updated, converted to common formats, reprojected, documented etc. Expect the guy who looked after it for the last 30 years and just remembers where it all came from to retire some day, so record the oral history now before its lost.
The current trend is towards incorporating spatial data into every aspect of day to day business. By the time you finish reading this article, however, that may have changed.
The Human Element
The data is for people, and some of them are stubborn. If it's too hard to learn or access the new system, it won't get used. Plan for training to ease the transition for some users who might be averse to change, and design it in the first place around the idiosyncrasies of the average human.
If you do your job well, plan for exponential growth in the amount of data you need to support, even if you carefully edit your data requirements. If you store data in the cloud or in the basement, the physical space available wherever your data is hosted can get eaten up quickly.
Signal to Noise
Too much data can be as unhelpful as no data at all since you'll waste time hunting for a needle in a haystack to pull out any insights. Your plan should include focusing on what's relevant now and in the future rather than amassing the world's biggest data pile. The better your metadata infrastructure is, the more discoverable the stuff you want most will be.
Batch process whatever you can. Any opportunity you see to handle routine tasks like assigning metadata to a file automatically, take it.
Is it really useful after a few years? Definitely back up all your work, but having deprecated data sets still available can be confusing for the users and can encourage human error. Decide if all data really needs to be hosted indefinitely or if it has a limited useful lifespan.
Expect users to try to circumvent your carefully laid out plan. You should develop policies in advance for how data can be accessed, used, and shared, depending on intellectual property rights, privacy expectations and security concerns for your particular data. Don't forget the tools to monitor and enforce the policies you put in place.