This document discusses research data management. It addresses what constitutes research data, including structured, unstructured, multi-modal, and multimedia data. It also discusses the life cycles of data and issues like how long to keep data, who should have access, and data ownership. The document proposes that cloud-based research data management can provide storage, software, and services to help with organizing, protecting, analyzing, archiving and sharing research data.
What could I tell you about Reearch Data? What kind of research does a company like Palomino know about?
Well, for one we manage research data for our clients. Clients rely on the tools we provide to gather, store, process and protect their data. So, we see Research Data Management as a set of REQUIREMENTS posed against our systems, giving researchers – as our end users – a tool to get their work done.
That’s how we know about Research Data Management.
So what is Research Data?
First of, RD has so many forms. Big Data, small data. Structured data warehouses, unstructured collections of office documents. Data with different life cycles and validity periods. One thing tht is for sure is that research data has ever-changing structure. Much different from business process data, which has a structure that does not change much unless the business changes.
So when we talk to a client about their data, the first thing we ask is – what do you do with your data? Do you change it? How often? Who gets it? Here just a few activities that typically are associated with RD.
Let’s just take a look at the obvious ones. Before we can do anything else with Data, we need to KEEP it somewhere. Preserve its existence. Protect it from oblivion. Send it to Archive.
Or, store it somewhere. This is what Scholars have done for centuries. Fill huge public rooms with shelves and shelves of DATA. Of course, such open display also makes our data accessible – to the public. Also, As we all know, knowledge is power, and displaying knowledge is, well, a display of power.
This is at least what the architects of the Staatsbibliothek in Austria had in mind when this library was built in the 19th century. Unfortunately, this building was a prime example of the problems with such public display of knowledge.
It burned down in 1848
And again in 1992.
So what is a solution to this problem of exposed, vulnerable Data Storage?
We bury the data to protect it. We limit access.
We keep it so far out of reach, sometimes we forget that we have it altogether.
Laughing? This is today’s equivalent. Who recognizes this? Servers, full of research data, tucked underneath am RA’s desk. Who has access to this?
Or to this? Is buried data truly there? Can we work with it? Or is it lost?
From my point of view – that of a business owner with a penchant for management of future risk – I see THIS as LOST DATA. That stick is practically already lost in someone’s jeans pocket right now. Where will it end up? In the laundry machine of course.
Some other thoghts are on how long we are required to keep data.
Retention is important to satisfy funders requirements for preservation of knowledge in Ontario and Canada.
Survey subjects have the right to request their responses for a period of time.
Your Team members benefit from accessing research data from archive.
THIS IS the value of the Cloud!
Losing and protecting data is not the only issue.
Using the Cloud to Keep RD is only the start.
To really turn data into knowledge, we need shared access.
We need shared access to discuss, collaborate, present, publish and validate.
What das sharing access mean? This is where it gets complicated.
For example, who should have access?
The TEAM of course!
Who should NOT have access?
This Person definitely not.
But also not this random grandmother.
Or Justin Bieber.
While we may choose to replace the library with the cloud, we still need a librarian.
Librarians help us to preside over data ownership, which is so important in research.
Possession is king, as they say.