Still in Need of Norms: The State of the Data in Citizen Science
This article offers an assessment of current data practices in the citizen science, community science, and crowdsourcing communities. We begin by reviewing current trends in scientific data relevant to citizen science before presenting the results of our qualitative research. Following a purposive s...
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2020-09-01
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doaj-68fe4578187a4a6094c220934cb444682020-11-25T01:53:33ZengUbiquity PressCitizen Science: Theory and Practice2057-49912020-09-015110.5334/cstp.30397Still in Need of Norms: The State of the Data in Citizen ScienceAnne Bowser0Caren Cooper1Alex de Sherbinin2Andrea Wiggins3Peter Brenton4Tyng-Ruey Chuang5Elaine Faustman6Mordechai (Muki) Haklay7Metis Meloche8Woodrow Wilson International Center for ScholarsNorth Carolina (NC) State UniversityCenter for International Earth Science Information Network (CIESIN), The Earth Institute, Columbia UniversityUniversity of Nebraska OmahaAtlas of Living Australia; CSIROInstitute of Information Science, Academia-SinicaInstitute for Risk Analysis and Risk Communication (IRARC), School of Public Health, University of Washington, Seattle, WAExtreme Citizen Science (ExCiteS), Department of Geography, UCLWoodrow Wilson International Center for ScholarsThis article offers an assessment of current data practices in the citizen science, community science, and crowdsourcing communities. We begin by reviewing current trends in scientific data relevant to citizen science before presenting the results of our qualitative research. Following a purposive sampling scheme designed to capture data management practices from a wide range of initiatives through a landscape sampling methodology (Bos et al. 2007), we sampled 36 projects from English-speaking countries. The authors used a semi-structured protocol to interview project proponents (either scientific leads or data managers) to better understand how projects are addressing key aspects of the data lifecycle, reporting results through descriptive statistics and other analyses. Findings suggest that citizen science projects are doing well in terms of data quality assessment and governance, but are sometimes lacking in providing open access to data outputs, documenting data, ensuring interoperability through data standards, or building robust and sustainable infrastructure. Based on this assessment, the paper presents a number of recommendations for the citizen science community related to data quality, data infrastructure, data governance, data documentation, and data access.https://theoryandpractice.citizenscienceassociation.org/articles/303citizen sciencecrowdsourcingdatadata managementfairdata quality |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Anne Bowser Caren Cooper Alex de Sherbinin Andrea Wiggins Peter Brenton Tyng-Ruey Chuang Elaine Faustman Mordechai (Muki) Haklay Metis Meloche |
spellingShingle |
Anne Bowser Caren Cooper Alex de Sherbinin Andrea Wiggins Peter Brenton Tyng-Ruey Chuang Elaine Faustman Mordechai (Muki) Haklay Metis Meloche Still in Need of Norms: The State of the Data in Citizen Science Citizen Science: Theory and Practice citizen science crowdsourcing data data management fair data quality |
author_facet |
Anne Bowser Caren Cooper Alex de Sherbinin Andrea Wiggins Peter Brenton Tyng-Ruey Chuang Elaine Faustman Mordechai (Muki) Haklay Metis Meloche |
author_sort |
Anne Bowser |
title |
Still in Need of Norms: The State of the Data in Citizen Science |
title_short |
Still in Need of Norms: The State of the Data in Citizen Science |
title_full |
Still in Need of Norms: The State of the Data in Citizen Science |
title_fullStr |
Still in Need of Norms: The State of the Data in Citizen Science |
title_full_unstemmed |
Still in Need of Norms: The State of the Data in Citizen Science |
title_sort |
still in need of norms: the state of the data in citizen science |
publisher |
Ubiquity Press |
series |
Citizen Science: Theory and Practice |
issn |
2057-4991 |
publishDate |
2020-09-01 |
description |
This article offers an assessment of current data practices in the citizen science, community science, and crowdsourcing communities. We begin by reviewing current trends in scientific data relevant to citizen science before presenting the results of our qualitative research. Following a purposive sampling scheme designed to capture data management practices from a wide range of initiatives through a landscape sampling methodology (Bos et al. 2007), we sampled 36 projects from English-speaking countries. The authors used a semi-structured protocol to interview project proponents (either scientific leads or data managers) to better understand how projects are addressing key aspects of the data lifecycle, reporting results through descriptive statistics and other analyses. Findings suggest that citizen science projects are doing well in terms of data quality assessment and governance, but are sometimes lacking in providing open access to data outputs, documenting data, ensuring interoperability through data standards, or building robust and sustainable infrastructure. Based on this assessment, the paper presents a number of recommendations for the citizen science community related to data quality, data infrastructure, data governance, data documentation, and data access. |
topic |
citizen science crowdsourcing data data management fair data quality |
url |
https://theoryandpractice.citizenscienceassociation.org/articles/303 |
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