Jennifer Couch: Well, while we’re getting our technical
issues work out, I want to thank -- join Dave and Charlisse, and the rest of the NIH Citizen
Science Working Group, on thanking you for joining us this morning, those of you here
in the room with us today, and also those of you out in the virtual space of the Twitterverse
and beyond.
I’m very happy to have you join us.
Now that you’re all tanked up on your exciting bread-and-water breakfast, and your brisk
walk in the Washington weather here this morning, should be a really productive day of discussion.
Let’s see.
So, I just want to give you a little bit of background on citizen science here at NIH,
and what we’ve been thinking, and what we’ve done here over the past couple of years, and
-- by way of intro to this particular workshop.
So, I want to start with just a little bit of a definition here, just because we’re
often asked to define citizen science, and we’re often asked to delineate it from these
other terms, here on the slide.
So, for us -- you already saw this on Charlisse’s slide, but citizen science is, just at its
essence, an approach to research that involves the public directly in the research process.
So, not just as subjects of the research or advisors to the research, but direct partners
and collaborators in all aspects of the research process, everything from data collection and
donation or sharing of data, all the way through the analysis of that data, and, ultimately,
in priority-setting and analyzing results.
The other terms that I’ve shown on here, community-based participatory research, and
crowdsourcing, you know, we can haggle over the exact boundaries of this Venn Diagram.
It’s a moving space.
I couldn’t quite -- I’m not artistically talented enough to make a moving Venn Diagram
here, but it’s a rapidly-evolving space, and these terms are sort of changing meaning
over time.
And I think, really, they’re converging, because they’re converging on this idea
of a more active role of the public in the research process itself.
And all three of those terms sort of share some methodologies and some tools, some data
science needs.
There’s an increasing reliance, in all of them, on things like the use of challenges,
and games, and we’ll talk more about that in just a sec.
So, back in 2013, which seems like eons ago now in this field which changes so quickly,
we had our first workshop on citizen science here at NIH.
The idea was that we had seen a lot of success in other fields, ecology and astronomy, notably,
for citizen science.
And we hadn’t seen a lot of activity in the biomedical space, and we knew we weren’t
supporting very much in the biomedical space, we NIH.
So we reached out to the folks in the biomedical sphere that we could see were actively doing
biomedical citizen science back in 2013, and they’re shown here by their logos on the
slide.
That’s who was at the meeting.
That workshop was chaired by Sharon Terry and Stephen Friend.
And it was a really good meeting.
It kind of gave us the lay of the land at the time, what was going on, and what the
potential was for citizen science in the biomedical sphere, and specifically, what the potential
was for NIH-supported research in citizen science in the biomedical sphere.
So what came out of that first workshop were some revelations, and recommendations, here.
The idea that biomedical research really can benefit from the creativity and problem-solving
skills of the public, and also from citizen-collected data, and insights that aren’t obtainable
through conventional approaches.
So, we don’t think of these approaches as displacing any of our current methods.
Nothing’s going to replace double-blind clinical trials, for example.
But all of these new approaches that are emerging in the citizen science space really have the
potential to enable research that isn’t doable in other ways.
But biomedical research poses really some unique challenges for citizen science that
isn’t as important in things like astronomy, where stars don’t really care if you share
their personal information, and that sort of thing.
There’s also some technical issues, you know, that arise in the scientific world,
and we think about using data collected by the public, for example, in terms of, sort
of, accuracy of the data, and that sort of thing, and analysis.
What we saw in 2013 was that the early efforts that were out there showed some promise, but
that biomedical research really -- and this was the thinking of the group that was here
two years ago -- that biomedical research, biomedical citizen science, really would benefit
from a more rigorous scientific assessment, and that these new methods have the potential
to complement, rather than replace, existing research approaches.
And then, obviously, the key recommendation at the bottom here, that we needed to -- before
we really did too much else, we needed to really think more, investigate more, understand
more, the ethical, legal, social implications of citizen science in the biomedical space.
Thus, all of you here today.
So the challenges that were raised by that group, you know, the challenges and the opportunities
kind of intersect here, so, but the idea was that these methods are still relatively new
in biomedical research.
It’s not totally clear what can be adapted to the biomedical space and what can’t,
what’s going to work under what conditions.
Our current policies, regulations and practices, really weren’t designed for citizen science,
and in particular, IRBs, for example, don’t really know what to do when investigators
come to them and want to use citizen science approaches.
We talked about the creation of flexible infrastructure and governance models that enable multiple
levels of participation, while maintaining data security, integrity, and scientific rigor.
So this is the idea of really putting the person, the public, in the driver’s seat
here, of deciding what to share, when, how to collaborate, that sort of thing, while
maintaining a level of scientific rigor in the research.
They said that methods needed to be developed and adapted, and rigorously tested, so that
we know what works and what doesn’t.
There’s a whole lot of methodologies out there, and it’s sort of -- some of this
is beginning to happen, but it’s still unclear which of those methods work best for which
kinds of research questions.
And they said that dissemination of tools, best practices, and training resources would
be critical.
This is something that we’ve taken to heart here at NIH.
We’re thinking about how to make some of these methods, these resources, more broadly
available.
I know that’s also going on out in the rest of the community.
Various other organizations are thinking about, you know, platforms and web resources, to
make some of these methods.
There are new journals out there.
So we’re beginning to sort of accumulate all of this information in a way that people
can access.
And the group also showed the need for evaluation of citizen science approaches to research.
So, you know, we don’t really know how to evaluate and review these kind of approaches.
But the opportunities are big, here.
For the most part, what came out of that think tank, and what we’ve seen more generally,
is that the public is eager and able to solve problems, if presented with the right tools,
and the right opportunities, under the right conditions.
A lot of caveats there, but you get it.
Patients and healthy individuals are generally motivated to collect and share personal health
data.
Obviously, this varies by group, it varies by person, it varies under different conditions,
it varies depending on what the disease or the condition is, and it varies by the sort
of background of the individuals, and thus, the sort of flexible governance models enabling
multiple levels of participation.
All of this sort of needs to be taken into consideration when we think about how to set
these studies up.
But initial applications of these methods in biomedical science have shown some utility,
and, applied effectively, there’s general agreement that there’s an opportunity here
to accomplish research that we really can’t accomplish using more traditional methods.
So -- whoops [spelled phonetically], well, all right.
So, following up on the recommendations of the think tank, we’ve been doing a few things
here.
And NIH sometimes moves slowly, but we move carefully.
We have been following up on the recommendation to learn more from other communities, to begin
to leverage what else is out there.
And that means other fields, things besides biomedical research, but also the community-based
participatory research area that we have long supported.
There’s a lot of lessons to be learned there.
We’ve become active participants in the Federal Community of Practice for crowdsourcing
and citizen science.
Some of those folks from other agencies are here in the room with us today.
We’ve learned a lot from them about how to support this kind of research in the federal
space, and they are likewise wanting to hear what you all have to say here today, because
the ethical, legal, social implications are big in biomedical research, but they cut across
some other fields as well.
We’re going to be presenting a panel with some of the experts here in the room, and
again, out there in the space beyond, at the upcoming Citizen Science Association meeting.
That’s the meeting happening here in February.
We have a panel, we’ll show that all to you guys here in a little bit.
And there are additional panels on biomedical research, I think, going to happen at that
meeting.
There’s one on environmental science, also, and some of the folks here in the room are
participating in that one.
We’ve done some additional investigation into some of the areas that the original think
tank recommended as sort of immediate opportunities, and one of the early sort of immediate opportunities
is this idea of engaging the game developer community in developing more biomedical research
games, really leveraging the wealth of expertise and technical resources that are out there
in the game developer world, to bring those to bear on biomedical research in creative
ways.
At the time, we saw things like Folded and Cell Slider, and since then, there’s been
the development of additional games.
Back in December, well, last month, we brought together 10 of those game developers and 10
biomedical researchers, and had a very, very active and exciting discussion with them about
how to bring those two communities together, how to form more partnerships, and begin to
develop more of these games.
A report from that will be coming out soon.
We did that workshop in conjunction with the NIH Big Data to Knowledge program, so the
report will be put on their website.
And then obviously, our next step here is the meeting at hand here, with following up
on the ethical, legal, social implications.
So there are also additional workshops and things being held by the different institutes.
You know, NIH has 27 different institutes and centers focused on diseases in organ sites,
and development in aging, and whatnot.
Several of them are following up on citizen science topics specific to their missions.
So, just, really quickly, last slide, because I think I’m getting the wave here, is, you
know, I wanted to just leave you with the idea of where we think citizen science can
have an impact in NIH-sponsored research space.
So, NIH supports research across a wide range of topic areas, and I think you saw that in
Charlisse’s slide earlier.
And we can imagine citizen science, you know -- spoiler alert, here -- the answer is, I
think citizen science can have an impact in almost every aspect of NIH-supported research
space.
Certainly, we’ve seen crowdsourcing and challenges, and things work very well in technology
development, computational methods, and software.
We can imagine better understanding the underlying biology of health and disease easily, through
things like games but one can imagine other methods in citizen science being applied there
as well.
We can see potential for impact in translational research, and therapeutic development, screening
and risk assessment.
Certainly areas like environmental factors have been very active in community-based participatory
research, and more and more in the citizen science arena, with the crossover with the
ecology field there.
And all aspects of epidemiology, certainly things like wearable technologies, sensors,
mHealth, nutrition and lifestyle, that kind of data is incredibly difficult to collect
under, sort of, traditional research conditions, but you can imagine that citizen science approaches
lend themselves really readily to collecting, utilizing, and analyzing that kind of data.
So anywhere that we can see the creativity and capabilities, and the unique insights
from the public, coming into bear in creative ways, we can imagine citizen science approaches
being useful for biomedical research.
So, I’m just going to leave it there for any quick questions that you might have.
Otherwise, I’m going to turn it back over to Dave and Charlisse to bring it back around
to the ethical, legal, and social implications of all of this.
Okay.
Everybody’s so starved on their bread-and-water diet here.
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