jepson biofresh_bih2013

Paul Jepson, Aaike De Wever & Astrid Schmidt-Kloiber

Data mobilisation from the BioFresh perspective: past, present & future visions

Co. 226874

Freshwater biodiversity status, trends pressure and conservation priorities

BIH2013 – September 2013 – Rome, Italy Contract No. 226874

BioFresh in the Network of EU F7 Biodiversity Research

•  Green = BioFresh partners

•  BioFresh close to dense centre, but on the periphery of the centre.

•  Network maps may identify potential for collaboration


Freshwaters cover less than 1% of the Earth’s surface yet are home to over 10% of all animal species Dudgeon et al. 2006

They possess immense natural capital in terms of the range and significance of ecosystem services

Freshwater Biodiversity needs attention

But, freshwater biodiversity is declining at an alarming rate


Water resource scarcity is considered a major threat to the security of social and economic systems A water-energy-food nexus is gaining influence as a framework for conceptualizing policies to guide transitions towards green economies. Biodiversity is not yet in this frame in any meaningful way

Water Lives: but not yet in policy


A real and pressing challenge is how to simultaneously manage freshwaters as a resource for humanity and as medium for life."

Going with the flow

Our ability to answer broad scale scientific questions on the status and trends in freshwater biodiversity is hampered by the limited and fragmented data"

Freshwater biodiversity and sound policy needs biodiversity informatics!!


The BioFresh project commenced in April 2010 to respond to this need

18 partners 9 Work-packages www.freshwaterbiodiversity.eu


Long tail, great potential

Plot of the citations in Web of Science and Scopus for the contributing data sets to BioFresh's data-portal (2012)"

Like many informatics project we have encountered the long tail of ‘dark data’"


What freshwater biodiversity data are out there?

•  We only have a vague idea but know that large amounts are currently unavailable.

•  Case study: GBIF has mobilised 3% of natural history collections data. Of 1200 possible data sets only 17 data sets predominantly freshwater specific. - must be more out there.

•  Additional data we ‘know’ exists, but is hard to get our hands on is data collected by environmental agencies, under the WFD monitoring and in EIA reports. This is because there is no directory and/or its stored in government departments.

In our view such facts underline the need for a freshwater biodiversity focused data mobilisation effort


Data mobilisation: what are we at?

We have been actively reaching out to data holders and other networks

•  Meta-databases for freshwater databases : 162 entries (54 under quality control), 100 more currently being integrated (mostly collected during WISER)

•  Links to relevant data (e.g. GBIF) al •  Supporting 26 digitisation &

mobilisation projects (contingency fund)

•  Assisting data holders to prepare their data for on-line publication

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BioFresh"related"datasets"

external"datasets" con;ngency"fund"datasets"

GBIF"freshwater"datasets"


Around 20 datasets have been commissioned through the BioFresh con7ngency fund Example 1: distribu7on data of European caddisflies

•  66 contributors adding 580,000 occurrences (addi5onal to GBIF data) – 420,000 from adults

• Significance: Group is key environmental indicator previously unavailable. Will form the basis of a Red List of Caddis Flies Example 2: Fish distribu7on data

•  9 con5ngency fund datasets, covering 13 countries , adding 250,000 species occurrences

•  Significance: Comple5ng spa5al gaps – European wide analysis of scien5fic ques5on rela5ng to fish now possible

Example 3: FADA con7ngency fund

•  Extension of taxonomic backbone with around 30,000 names of macro-‐invertebrate species

•  Significance: enables linking to and harves5ng of other sources

New data sets digitized & mobilized


Some nice applied science outputs now emerging

Identification of Key Biodiversity Areas for Africa a major output


Mobilising data has proved difficult

•  Convincing data holders to contribute data is often not straightforward

•  Tedious process to obtain metadata, involving a lot of contacting work, even for project partners’ datasets

•  Filling out information ourselves improved response rates, but is obviously time-consuming

•  Especially difficult was integrating datasets e.g. water framework directive (inter-calibration challenges)

•  Processing datasets further involves frequent email exchange with data holders, esp. when we prepare the data (for publication using GBIF’s Integrated Publishing Toolkit)


Barriers to contributing to the BioFresh Portal: a survey of data owners

•  Funding provision: funding unavailable for data curation, so no one is tasked with maintaining or making the data public."

•  Incompatible technology: data stored in defunct, or difficult to integrate formats. Or, in a known format, but the scientist who put it together is no longer available (retired/RIP!) so data meaning lost."

•  Early career researchers: Not keen on sharing data, as it has been painstakingly collected during their PhD, and they want to publish it and get as publications as possible from it, before it is shared with others."

•  Time: scientists are increasingly busy and under resourced, as such they don't have time to clean and categorize data (applying metadata) for a mass audience. "

•  Reward structures of science: not calibrated to support data sharing and re-use"

•  Commercial imperatives: data part funded by water companies, pharmaceutical companies etc. Open data is not their paradigm and data ownership is often at a company rather than an individual level"

Cf. Tenopir, C. et al. (2012) Data Sharing by Scientists: Practices and Perceptions. PlosONE 6: 1-21


Biodiversity informatics is an interdisciplinary science

Mobilizing data and constructing data networks is not simply a technological and resourcing challenge "

"It has complex science sociology !

and culture dimensions!!

This aspect is largely over-looked in" Hardisty & Roberts Decadal View "


“Science Friction”: a metaphor and conceptual framework for embracing the social in informatics

•  ‘Science friction’ : ‘the difficulties encountered when two scientific disciplines (or data holders) try to interoperate.’

•  ‘Data friction’: ‘Every movement of data across an interface comes at some cost in time, energy, and human attention... In social systems, data friction consumes energy and produces turbulence and heat - that is, conflicts, disagreements, and inexact, unruly processes.’

•  ‘Lubrication’: the practices through which people overcome friction without precise solutions or the need to modify components

•  ‘Precision’: making it possible to join one part (dataset) more perfectly to another one (data standards)

Edwards, P et al. (2011) Science friction: Data, metadata, and collaboration. Social Studies of Science 41:667-690


Our effort at ‘lubrication’ hasn’t yet been a great success!

In short, encouragement is not enough! (cf:

We envisage a special issue on contingency fund projects in a data journal (e.g. Pensoft’s Biodiversity Data Journal)


So what about this cultural shift?

•  Is a cultural shift towards scientists embracing the principles of data access, sharing and reuse really taking hold?

•  Is this a generational shift or could be it be accelerated?

•  What’s the strategy – our theory of change?


Some options in our minds

•  Data publishing gets similar status to other forms of publishing (??) •  Actively learn from our fund-raising and NGO campaign lobbying

colleagues – i.e. techniques of relationship building, profiling and coalition building Tip: email last. Be a person, be prepared to roam and smooch to capture data.

•  Actively learn from industry associations. E.g. Could National Science Academies produce best-practice standards for research institutions in same was as IMCO does for mining corporations

•  Normalise data sharing principles in post-graduate training. EU (and UK in particular is a global centre and leader in Biodiversity PGT


The H2020 scientist & policy professional

Disciplinary knowledge

Professional friends

Core specialism

Interdisciplinary breadth


Thinking ahead… and ambitiously!

To what extent is biodiversity informatics conceptualized and enacted in 4th wave internet computing?"

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How do we conceptualize biodiversity informatics in terms of 5th wave mobile computing and responding to the technological forces of ‘mobile’ ‘cloud’, ‘social’ and ‘big data’?"

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Might a shift in focus from mobilizing legacy data towards generating contemporary data face less ‘science friction’ and improve data density more rapidly?"

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Might adding a focus on citizen science and automated sensing support simultaneous developments in science-policy-management interfaces?"


Biodiversity Informatics - extended vision Bigger science : better policy : effective governance

Crowd-identification

Engagement media

NGO data Individual’s data

Gov data

Museum data Res.Inst. data

Super computer muscle

Cloud utility computing

Smartphone

Citizen interpreters

Citizen data collectors

App 2.0

App Supersize

Policy 3.0

Device Re-mastered

Teaching Resources

Research Resources

Decision support tools

Real Science online

Decision support visualisations

Citizen recording

Platform

Portal Portal

Mobile device

Sensing 2.0

Automation, Minaturisation, networks DIY


Technologies for sensing biodiversity are under-going a step-change

Research Drones Micro-sensors

Sensor networks

Our challenge is thinking creatively and strategically on how to embrace and integrate these


App-phones as rich sensors, mobile computers and a

technological appendage of the human body and mind

Supersize Apps vs.

Apps 2.0

Smartphones as efficient, low cost and trendy delivery or

collection media

Earl. J. & Kimport, K (2011) Digitally enabled social change: Activism in the internet age. Cambridge. MA. MIT Press

Citizen science is expanding but needs research investment to undergo a step-change


Jepson & Ladle in prep Conservation in the App-age Scrape of Google play = 7400 apps.

•  Scrape of Google play = ca. 7400 apps

•  Probably <120 data mobilisation apps

•  Probably <10 App 2.0

•  Automatically identifies cicada plus 6 grasshopper species

•  Walk, ride and sense •  Alert if senses a target species

New Forest Cicada Hunt

Survey of Nature & Conservation Apps


Mobilisizing citizen science for freshwater science

Opportunity Many and varied communities of practice engage with

freshwaters – government environmental agencies – anglers – wild swimmers

Challenge Much of what we want to record is under the surface! Sources of inspiration Examples of innovative partnerships with Information

Engineering (e.g. Zooniverse) & computer scientists (e.g. New Forest cicada hunt)

Developments in App-phone hardware add-ons (e.g. water quality sensors)


Biodiversity Informatics - extended vision Bigger science : better policy : effective governance

Crowd-identification

Engagement media

NGO data Individual’s data

Gov data

Museum data Res.Inst. data

Super computer muscle

Cloud utility computing

Smartphone

Citizen interpreters

Citizen data collectors

App 3.0

App Supersize

Policy 3.0

Device Re-mastered

Teaching Resources

Research Resources

Decision support tools

Real Science online

Decision support visualisations

Citizen recording

Platform

Portal Portal

Mobile device

Sensing 3.0

Automation, Minaturisation, networks DIY


BioFresh platform: Towards intelligent openness:

Royal Society principles • Accessible • Assessable • Intelligible • Useable + Science – policy context Decision support tools Research information Analysis tools Training resources


Decision support tool: IUCN/ESRI Freshwater biodiversity browser & Arc GIS App

Supports environmental impact assessments, conservation planning etc. By making IUCN data on African fish, mollusc, dragonfly, crabs and freshwater plants at sub-catchment level See www.biofreshblog.com


•  Currently ~50 maps in various stages of implementation •  Dynamic currated atlas – anyone can contribute their nice

map

Decision support visualization: BioFresh Atlas of Freshwater Biodiversity

Decision support visualization: BioFresh Atlas of Freshwater Biodiversity


•  Freshwater is a major area of policy. Investments in freshwater biodiversity informatics are needed to develop a science capable of meeting policy needs

•  Mobilizing freshwater data sets has proved difficult. •  We need add and adopt a cultural approach •  Need to further invest and reinforce the building of a

freshwater biodiversity data network •  Looking forward we need to explore and respond to the

potential associated with the transformations in science and society resulting from new technological forces

•  We need to simultaneously conceptualize the design of open-access, on-line science-policy-management platforms

Summary

jepson biofresh_bih2013

Education