Seven Predictions

In a tradition as old as blogs, I’m summarizing here what someone else wrote up and put on the internet. In my defense, it is pretty good stuff that certainly didn’t get enough attention from what I can tell. Hopefully this post will remedy the situation.

gadget graffiti

Only in New York: Go-Go-Gadget Graffiti! From Flickr by sabeth718

The piece I’m reporting on comes from the JISC organization. JISC (formerly the Joint Information Systems Committee) is an organization in the UK whose role is to provide leadership in “Information and Communications Technology” for higher education institutions. They put out all kinds of great information on their website, including an online publication called JISC Inform.

In the most recent issue of JISC Inform, there is a piece on seven predictions for the future of research, fueled by the minds of Sarah Porter and Torsten Reimer. In my opinion, they are spot on in their predictions.  Researchers, librarians, funders, and journals alike would benefit from perusing their (now my) list:

1. Researchers will go mobile. These days, all data that is collected must either be born digital or converted to digital; why not make as much of it born digital as possible? That means taking mobile devices, like phones, tablets, and laptops, out into the field and using them to directly collect data. Go-Go-Gadget Scientist!

2. Lines between professionals, amateurs, and the public will blur. Citizen science (or PPSR) is on the rise, due to increased global connectivity and better quality control and assurance methods for data that the public collects. A great success story is the eBird: amateur birders have contributed important data to help answer research questions about topics like migration and range spread.  Crowd-sourcing some of the data collection or analysis is also becoming commonplace: check out Galaxy Zoo for a great example.

3. Researchers will fully embrace social media. Those that don’t are not likely to be as successful as their counterparts (take note, oceanographers). Blogs and other forms of rapid scientific communication are now ubiquitous, and the pace of academic publishing is speeding up.  Altmetrics will serve to quantify the effects of this participation so researchers can understand their impact.

4. Data-driven research will be embraced by all disciplines. Of course, there is plenty of data-driven research in fields like chemistry, astronomy, and ecology; this trend is alluding to a move in the humanities towards data-driven research. Ever heard of digital humanities? If not, you will soon.

5. Automation. With the deluge of data comes a need for better analytical tools.  Text analysis, cloud-based applications, and mining for data will become more automated and tools for researchers will continually improve to meet their increasing needs.

6. Increasing visualization and infographics. Humans are inherently visual; processing information in the form of a chart or graph typically is much easier than in a table or list.  The rise of visual websites such as Flowing Data, Information is Beautiful, and Daily Infographic, are all evidence of the shift. Want to start creating pretty things? Play around with visual.ly.

7. Researchers as data managers. That’s right: data management made the list (I swear I didn’t add it to synchronize with my drum beat about better data management). The authors says that data is at the heart of activities for researchers; they will need to be more involved in how these data are documented, collected, managed, and preserved. Mandates for data sharing are inevitable, and researchers would do themselves a favor by practicing good data stewardship now.

Read the full article from JISC here.

A Potpourri of DC Meetings

I’ve been in our nation’s capital since Sunday for three meetings, all while battling a particularly tenacious cold.  I’m using this post as a debrief, as well as to tell you about a few nifty projects.

First, the University of North Texas folks put on a symposium about the DataRes Project.  UNT librarians are quite the players in the data curation landscape these days – check out their website Data Management @UNT for more information. The DataRes Project is funded by the IMLS and “investigates how the library and information science (LIS) profession can best respond to emerging needs of research data management in universities.” Although I’ve only been involved with libraries since 2011, I’m pretty darn excited about the role that libraries are poised to play in data management.  Sounds like UNT agrees!

The second meeting was the Coalition for Networked Information 2012 Fall Members Meeting.  The Coalition for Networked information (CNI) is an institutional membership organization, with members that include universities, publishers, libraries, IT companies, governmental folks, and others.  These groups have a common interest in figuring out ways to facilitate communication, collaboration, and innovation in information management. I presented on the DMPTool, which was greeted with excitement by members of the audience. I also attended quite a few “project briefings” (i.e., sessions), wherein I heard about other interesting goings on in the world of information.

The briefing I enjoyed most was about FORCE11. It’s all caps because it’s an acronym: the Future of Research Communications and e-Scholarship. The “11” is because the group was founded in 2011.  FORCE11 is a “virtual community working to transform scholarly communications toward improved knowledge creation and sharing. ” I plan to join up with this group for their meeting Beyond the PDF 2 in March. Stay tuned for more on that group – I think they have the potential to really shape the future of scholarly communication.

The third and final meeting this week is still going on – the E-Science Institute. I blogged about E-Science last week, so I won’t go into detail on that aspect of the meeting.  But the basic idea is that libraries attend this meeting to think about ways to shape their “Strategic Agenda” for supporting science in this age of digital, big, complicated data and analyses. You can see how this might fit in with the DataRes project.  I like the idea of empowering libraries to take on all things data!

LOC reading room

I could get some serious studying done here. The Library of Congress Reading Room, From Flickr by shoupiest

A brief thought: What is E-Science?

I’m not sure when I first heard the term “E-Science”, but it wasn’t that long ago. My first impression was that it sounds like one of those words that should be unsucked (i.e., jargon). Now that I know more about it, I’m inclined to think that jargon is in the ear of the beholder. Here’s why:

The most commonly used definition for E-Science is that it is type of scientific research that uses large-scale computing infrastructure to process very large datasets (i.e., “Big Science“, which generates “Big Data“).  However many (most?) often I hear E-Science used as an umbrella term that describes any size of science that involves digital data and/or analysis.  These days, that pretty much covers all science.  I therefore contend that E-Science as a phrase is redundant – it was describing what used to be a subset of science, but is now more correctly describing all science. So why is there an “E” at all?

There are journals, websites, and meetings focused on E-Science (I blogged about attending the Microsoft eScience Workshop just a few months ago). In fact, I’m currently participating in an E-Science Institute, sponsodred by the Association of Research Libraries, the Digital Library Federation, and  DuraSpace.  The goal of the Institute is to provide opportunities for “academic and research libraries to  boost institutional support of e-research and the management and preservation of our scientific and scholarly record.” Libraries are facing the new digital frontier head-on: they are interested in providing services that meet researchers’ needs, and these services have changed dramatically in the last few decades.

The argument for keeping the “E”: Although science researchers have no need for the distinction between Science and E-Science, it is a helpful distinction for groups that provide services to academia at large. Not all disciplines are as digital as the sciences: think about art history, studies of ancient texts, or observations of other cultures. Those groups that provide services or assistance for the broader academic community should, therefore, continue to consider E-Science.

banksy

Perhaps one day emails will just be mails… And Banksy will return them. From Flickr by Bruno Girin (More on Banksy: http://en.wikipedia.org/wiki/Banksy)

Some readings, recommended by the E-Science Institute organizers (and me!):

  • Jim Gray on e-Science, A Transformed Scientific Method. from The Fourth Paradigm: Data-Intensive Scientific Discovery, Tony Hey et al. Microsoft Research, 2009 .  Link
  • E-Science and the Life Cycle of Research, Charles Humphrey.  June, 2008.  Link
  • Special Online Collection: Dealing with Data, Science Magazine, AAAS.  February 11, 2011.  Link (free registration available)