1. Standardizing Citizen Science
Dr. Anne Bowser
Woodrow Wilson International Center for Scholars
Presentation Prepared for GEO Week 2017
Good morning and thank you for the introduction! I’m incredibly excited to be here. This is my first time at TDWG 2017 and I am not a biodiversity informatician.

2. Citizen science is structure and scale.
I started working with CS in 2010, when I was getting my Masters at UMD. A senior researcher was testing the boundaries of social network analysis software, which was just being used to answer research questions through platforms like Twitter. He gave me a data set that showed the network of different biodiversity data repositories sharing records with the Encyclopedia of life. I analyzed this data in a number of ways, and learned about the role of citizen science in so many of these nodes. This project helped shape my perspective that citizen science is important because it provides structure and scale. Through the structure of projects, individual volunteers can share information in a way that counts towards a specific goal. And the network of citizen science projects together helps further scale these initial observations so that data collected to solve one local problem can have a truly global impact.

3. Global Mosquito Alert: History
2014-present: CS Mosquito monitoring begins (everywhere)
2015: (ECSA) Conference in Barcelona
2016: ECSA Policy Working Group charters a Mosquito Task Force
2017: UNEP host a workshop in Geneva
“The Global Mosquito Alert will be an open, common set of protocols, platform, and toolkit that is augmented with modular components created to meet both global and local research and management needs.”
2017: NASA DEVELOP
To do a roof of concept data

4. Global Mosquito Alert: 4 ProtocolsX 1 3 Y Z
Real time vector monitoring
Habitat mapping and breeding grounds
Bites/ nuisance
Specimen sampling/ eDNA 2 4

5. Global Mosquito Alert: Partners
Mosquito Alert, Spain/ Catalonia
Aedes albopictus (Zika) and Aedes aegypti (yellow fever)
App + visualization platform for species presence via photo and breeding site
9,301 reports (3,473 validated)

6. Global Mosquito Alert: Partners
Muggenradar, Netherlands
Any and all species for forecasting
3593 samples (all)
5236 citizen scientists
193 pictures (all)

7. Global Mosquito Alert: Partners
Zanzamapp, Italy
10,457 observations
Aedes albopictus – Culex pipiens
General public
Insecticide sprayings

8. Global Mosquito Alert Early Findings with MODIS and SRTM (++)
Not all data are “good,” “open,” or “obvious.”
Value to integration ...no issues beyond other scientific research.

9. Lessons for Citizen Science Standards
Transdisciplinary data and metadata formats, including information about projects and observations.
Methods and processes for collaboration.
Tools for data collection.
Protocols for data collection.
Information including alignment with standards.
Common and flexible and maybe a little bit generic.
Processes and documentation of repeatable workflows.

10. Public Participation in Scientific Research (PPSR)-Core
A Common Data Model (CDM) with three main schemas
That essentially seeks to cobble together and benefit from a lot of what came before- but can still, hopefully, make a contribution.

11. PPSR-Core A Common Data Model (CDM) with three main schemas
2. Data Set (DDM)
Descriptive & contextual information about a collection of data records using a common method and data schema.
(ie. Metadata about a published collection of data)
A Common Data Model
(CDM) with three main
schemas
0 : n
will have
may have
1. Project (PDM)
1 : n
3. Data (ODM)
A coordinated cluster of citizen science activities and data. Information describes the context and purpose for activities.
Key components of the PPSR-Core PDM schema are used to share data between SciStarter, ALA, CitSci.org, and the Federal Catalog.
Slide by AB.
Feel strongly that a data set is published, and ideally has a DOI or other persistent identifier attached. It has “complete” metadata. In addition we have data and other forms of information that may not be finalized. Still, CS projects need to be thinking about standardizing “Data” before they think about documenting their “data set” in a consistent way.
Question: What is 0: n, 1:n, etc.??
PB comments:
I accept that “container” is probably not a term that can be easily related to, but I think that using “coordinator” in this context is wrong and distorts the meaning/intent of what the project entity is about. Coordinator implies that this entity is all about a person and that is definitely not the case, it should be focused on the what and why. It is about providing the who/what/when/where/how/etc. context for the activities and data. Suggest rewording again.
AB: Addressed.
Data records using a common method and data schema.
(eg. Physical/chemical water quality records collected over a series of data collection events at one or more sites)

12. PPSR-Core: History 2010-2012 2013-2014 2015 2016 +
Why: Understand and document citizen science
Why: Develop Project Metadata standards to share records between 4 databases
Why: Build a 5th database that is compatible with the other 4
Why: Create and document parallel processes for knowledge generation and use

13. PPSR-Core: Next Steps 2 3 1 3’ 0. Common (CDM) High-level skeleton
1. Project (PDM)
2. Data Set (DDM)
3. Data (ODM)
Ongoing
Crosswalks
New (fitness for purpose)
Crosswalks
Data integrations 1 3’
Ecology/
Environment
Biology
Health
Astronomy
Agriculture
Energy
Humanities
source:

14. Thank You Stay in touch anne.bowser@wilsoncenter.org