@article {zevin2023gravity, title = {Gravity Spy: Lessons Learned and a Path Forward}, journal = {European Physical Journal Plus}, volume = {139}, year = {2024}, month = {01/2024}, pages = {Article 100}, abstract = {

The Gravity Spy project aims to uncover the origins of glitches, transient bursts of noise that hamper analysis of gravitational-wave data. By using both the work of citizen-science volunteers and machine-learning algorithms, the Gravity Spy project enables reliable classification of glitches. Citizen science and machine learning are intrinsically coupled within the Gravity Spy framework, with machine-learning classifications providing a rapid first-pass classification of the dataset and enabling tiered volunteer training, and volunteer-based classifications verifying the machine classifications, bolstering the machine-learning training set and identifying new morphological classes of glitches. These classifications are now routinely used in studies characterizing the performance of the LIGO gravitational-wave detectors. Providing the volunteers with a training framework that teaches them to classify a wide range of glitches, as well as additional tools to aid their investigations of interesting glitches, empowers them to make discoveries of new classes of glitches. This demonstrates that, when giving suitable support, volunteers can go beyond simple classification tasks to identify new features in data at a level comparable to domain experts. The Gravity Spy project is now providing volunteers with more complicated data that includes auxiliary monitors of the detector to identify the root cause of glitches.

}, doi = {10.1140/epjp/s13360-023-04795-4}, author = {Michael Zevin and Corey B. Jackson and Zoheyr Doctor and Yunan Wu and Carsten {\O}sterlund and L. Clifton Johnson and Christopher P. L. Berry and Kevin Crowston and Scott B. Coughlin and Vicky Kalogera and Sharan Banagiri and Derek Davis and Jane Glanzer and Renzhi Hao and Aggelos K. Katsaggelos and Oli Patane and Jennifer Sanchez and Joshua Smith and Siddharth Soni and Laura Trouille and Marissa Walker and Irina Aerith and Wilfried Domainko and Victor-Georges Baranowski and Gerhard Niklasch and Barbara T{\'e}gl{\'a}s} } @article {9998, title = {Data quality up to the third observing run of Advanced LIGO: Gravity Spy glitch classifications}, journal = {Classical and Quantum Gravity}, volume = {40}, year = {2023}, keywords = {FOS: Physical sciences, General Relativity and Quantum Cosmology (gr-qc), Instrumentation and Methods for Astrophysics (astro-ph.IM)}, doi = {10.1088/1361-6382/acb633}, author = {Glanzer, J and Banagiri, S and Coughlin, S B and Soni, S and Zevin, M and Berry, C P L and Patane, O and Bahaadini, S and Rohani, N and Crowston, K and {\O}sterlund, C} } @inbook {9999, title = {Levels of trace data for social and behavioural science research}, booktitle = {Big Data Factories: Collaborative~Approaches}, year = {2017}, publisher = {Springer Nature}, organization = {Springer Nature}, abstract = {

The explosion of data available from online systems such as social media is creating a wealth of trace data, that is, data that record evidence of human activity. The volume of data available offers great potential to advance social and behavioural science research. However, the data are of a very different kind than more conventional social and behavioural science data, posing challenges to use. This paper adopts a data framework from Earth Observation science and applies it to trace data to identify possible issues in analyzing trace data. Application of the framework also reveals issues for sharing and reusing data.

}, isbn = {978-3-319-59186-5}, doi = {10.1007/978-3-319-59186-5_4}, attachments = {https://citsci.syr.edu/sites/crowston.syr.edu/files/160529\%20levels\%20book\%20chapter_0.pdf}, author = {Kevin Crowston}, editor = {Sorin Matei and Sean Goggins and Nicolas Jullien} } @article {2012, title = {The future of citizen science: emerging technologies and shifting paradigms}, journal = {Frontiers in Ecology and the Environment}, volume = {10}, year = {2012}, month = {08/2012}, pages = {298{\textendash}304}, abstract = {

Citizen science creates a nexus between science and education that, when coupled with emerging technologies, expands the frontiers of ecological research and public engagement. Using representative technologies and other examples, we examine the future of citizen science in terms of its research processes, program and participant cultures, and scientific communities. Future citizen-science projects will likely be influenced by sociocultural issues related to new technologies and will continue to face practical programmatic challenges. We foresee networked, open science and the use of online computer/video gaming as important tools to engage non-traditional audiences, and offer recommendations to help prepare project managers for impending challenges. A more formalized citizen-science enterprise, complete with networked organizations, associations, journals, and cyberinfrastructure, will advance scientific research, including ecology, and further public education.

}, issn = {1540-9295}, doi = {10.1890/110294}, url = {http://www.esajournals.org/doi/pdf/10.1890/110294}, author = {Newman, Greg and Wiggins, Andrea and Crall, Alycia and Graham, Eric and Newman, Sarah and Kevin Crowston} } @conference {2009, title = {Designing Virtual Organizations for Citizen Science}, booktitle = {IFIP Working Group 8.2 OASIS workshop 2009}, year = {2009}, month = {12/2009}, address = {Phoenix, AZ}, url = {http://sprouts.aisnet.org/9-56/}, attachments = {https://citsci.syr.edu/sites/crowston.syr.edu/files/WigginsOASIS2009.pdf , https://citsci.syr.edu/sites/crowston.syr.edu/files/awigginsOASIS2009.ppt}, author = {Wiggins, Andrea and Kevin Crowston}, editor = {Uri Gal} }