Good documentation is thorough – and it does take time to produce.While this might seem like a waste of time, there are several reasons why it’s important to do (and these will probably save you time in the future!)
First of all, because documentation should be thorough it will contain a lot of information that might seem obvious. But will that same information still be obvious in a few months, years, decades, centuries… time?It’s very easy to assume that you will remember it, but it’s quite easy to forget crucial information. It also means that other people can understand what you’ve done and why. It’s important to include context (why you did your research, how it fits into other contemporary research, or follows on from previous work), as well as explaining your methods and analytical techniques. This is related to the next point…
By providing documentation, you can provide the methodology of how you generated/collected/produced your data (for example information about collection strategies, algorithms, database searches), and how you reached your conclusions from your data.This is important as it means that people can reproduce your research, either to verify your conclusions or as a starting point to developing your work further. In many research groups, this could be a student or post-doc who continues work started by a previous student. Replicating methodology can also be a useful training tool.Key points:Detailing your methods helps people understand what you did (and why)Explaining your algorithms, search methods etc makes your work reproducibleConclusions can be verified
One of the main advantages of creating documentation is that it makes data re-usable. This doesn’t have to be altruism – it can be by you at a later date. Besides, making your data available has benefits for your reputation, so documentation doesn’t have to be altruistic even if you don’t intend to re-use the data yourself.
Documentation is human readableMetadata is machine readable. This has important implications for searching for data. The structured machine-readable form of metadata means that it can make things easier to find. Think of it like tagging a photo in facebook or on flickr. The more comprehensive it is the easier it is to find things, and you can never be quite sure what other people will be looking for. But providing better metadata increases the chances of finding relevant information.
Producing good metadata means that it’s easier to find your data, as it highlights the important aspects in a machine-readable way. This makes computer-based searches, whether on your searching your own hard drive or looking for something on a database online, work better for you – they’re more likely to find relevant files and information more quickly. If you’re working on a large project you might be interested in crowd-sourcing metadata production. This works well with niche communities who are active online (such as transport, or local history). It’s easier to produce good metadata when files have also been documented!
PrePARe: Explain It
EXPLAIN ITWHY YOUR RESEARCH DESERVES GOODDOCUMENTATION AND METADATA Question Mark Sign by Colin_K on flickr: http://www.flickr.com/photos/ colinkinner/2200500024/
Why create documentation? • Creating documentation can seem like a waste of time • Good documentation will include a lot of information that might seem obviouswww.flickr.com/photos/smutjespickles/2434418686/
Make material understandable Image: http://www.flickr.com/photos/archer10/5692813531/
Make material reproducible Image by woodleywonderworks on flickr: http://www.flickr.com/photos/wwworks/4588700881/
What to include (I) • Who created it, when and why • Include: • Description of the item • Methodology • Units of measurement • References to related datadescription n.A set of characteristics by whichsomething can be recognised www.texample.net By mdxdt on flickr: www.flickr.com/ photos/dxdt22/177749386/
What to include (II)• Define jargon, acronyms and code By Gavin Llewellyn http://www.flickr.com/photos /gavinjllewellyn/6826303487/ • Provide technical information about the file (may be generated automatically)
Explain it• Create documentation to make data: – Understandable – Reproducible – Re-usable – Findable (and searchable)• Explain: – Who created it, when and why – Methodologies and analysis techniques – Jargon, acronyms and code
Open Access Teaching Materials for Digital Preservation Produced by Anna Collins (2012) for the JISC- funded PrePARe projectThis work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 2.0 UK: England & Wales License.