Skip to Content

Reading the bones: a few thoughts about the future of research information management

Printer-friendly versionPrinter-friendly version
Spring 2014

 James Brunt (LNO)

“Where the hell’s my flying car?” - Steve Earle - from 21st Century Blues“

I’m the first to admit that I’m not a great seer.   I missed the whole smartphone thing  and I still don’t understand social media.  Sure, I predicted the digital data deluge but who didn’t? I also predicted that we’d have analytical and visualization tools beyond our wildest dreams.  Whoops.  My predictions when right though have been less prophetic and more following trends out to some logical future with a judicious application of Moore’s Law.  

If I had to make just one prophetic statement it would be that site information management (IM) will get more complex.  If the trends I watch were linear, Information management should getting more automated, be focusing more on workflow process and less on site-based IT infrastructure, and be relying more on community resources.   I say this  because we are going to have cheap accessible cloud-based computing and storage infrastructure,  more community resources, like PASTA, to draw from, more tools available to help reduce the effort spent on tasks that are repetitive and common across sites, and more community standards available for adoption.  These trends all point towards increasing IM functionality and lessening site IM burdens.  So, you ask, doesn’t that mean that site IM should be getting simpler?  Not at all,  I predict  that  Glass’ Law1 will prevail and rather than simplifying IM by taking away, we make site IM  more complex.  

I offer these additional predictions based on trends (and hunches) that will lend some credibility to the statement above:

Budgets will become tighter.  Ouch, I know.  But as more of the broader  research community implements  data management plans the overall cost of data management  to the funders will go up.  Unable to sustain the introduction of data management practice where there previously was none the funding agencies will be looking for economies of scale.  This will drive the availability of community resources and centralized tools.  The initial use of these tools will be driven more by budgets than popularity.  Site management teams will have to weigh the cost and benefit of doing more centrally.

Site information management will rely more heavily on local software skills.  In the endless effort to bridge the app gap it’s still easier to tool up an application for some site-based data need than to search around for and adapt an existing tool. True or False? I believe true for the most part because of the many site specific constraints inherent in most systems.  If finding and adapting existing tools was easier this might be less true.  Look for more job announcements with an emphasis on multi-faceted programming and software integration skills.

Data quality and data assurance will become more important.  Consumers of data products are always looking for data of known quality.  Defined data quality metrics will become more common and their use will inform both producers and consumers of data.  Richness of metadata and institutionalized checks will be major factors in predicting data quality. Site information managers will continue to be the frontline defense of data quality.

Open data will pervade and prevail.  Don’t say you didn’t see this one coming.  Government, funding agencies, reviewers, colleagues, and the public will cease to tolerate obfuscation through endless registration, policy, and paywall pages between them and data.

Data products will become more important.  As a result of open data there will be a greater emphasis put on synthesized data products and reduced scrutiny of raw data publication.   As the tsunami of open data crashes upon the rocks there will be outcries and pleading for value-added products that summarize and give meaning to all the raw measurements.  Site information managers will be called upon repeatedly to contribute to and support the process of developing these products.

There will be more standards - there will be more innovation.  This may seem like a non-sequitur to the IM mind but consider my proposition that useful standards are the ultimate resting place of surviving innovation and not the death of innovation as can be the case with standards that are not empirical in design.  Good standards emerge as we use standard approaches to processes that have been originally established as innovation and have survived by popular adoption. This process makes room for more innovation and we know that ecology is a discipline that thrives on innovation. Site IM is central to both the adoption of standards and the implementation of innovation.

Inset Box 1 - What’s trending and not for the future of IM?

What’s trending?

What’s not trending?

Data quality

Website quality

Data products

Raw data

Open data


Software skills

One-size fits all

Standards ("Good")

Standards ("Bad")


1. Robert L. Glass in “Facts and Fallacies of Software Engineering”- For every 25 percent increase in functionality of a system, there is a 4X increase in the complexity of that system.