@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} } @proceedings {wang2024reelframer, title = {ReelFramer: Human-AI Co-Creation for News-to-Video Translation}, year = {2024}, address = {Honolulu, Hawai{\textquoteright}i}, abstract = {

Short videos on social media are the dominant way young people consume content. News outlets aim to reach audiences through news reels -- short videos conveying news -- but struggle to translate traditional journalistic formats into short, entertaining videos. To translate news into social media reels, we support journalists in reframing the narrative. In literature, narrative framing is a high-level structure that shapes the overall presentation of a story. We identified three narrative framings for reels that adapt social media norms but preserve news value, each with a different balance of information and entertainment. We introduce ReelFramer, a human-AI co-creative system that helps journalists translate print articles into scripts and storyboards. ReelFramer supports exploring multiple narrative framings to find one appropriate to the story. AI suggests foundational narrative details, including characters, plot, setting, and key information. ReelFramer also supports visual framing; AI suggests character and visual detail designs before generating a full storyboard. Our studies show that narrative framing introduces the necessary diversity to translate various articles into reels, and establishing foundational details helps generate scripts that are more relevant and coherent. We also discuss the benefits of using narrative framing and foundational details in content retargeting.

}, url = {https://arxiv.org/abs/2304.09653}, author = {Sitong Wang and Samia Menon and Tao Long and Keren Henderson and Dingzeyu Li and Kevin Crowston and Mark Hansen and Jeffrey V. Nickerson and Lydia B. Chilton} } @proceedings {petridis2023anglekindling, title = {AngleKindling: Supporting Journalistic Angle Ideation with Large Language Models}, year = {2023}, doi = {10.1145/3544548.3580907}, url = {https://savvaspetridis.github.io/papers/anglekindling.pdf}, author = {Petridis, Savvas and Diakopoulos, Nicholas and Crowston, Kevin and Hansen, Mark and Henderson, Keren and Jastrzebski, Stan and Nickerson, Jefrey V and Chilton, Lydia B} } @article {wang2023reelframer, title = {Video for ReelFramer: Co-creating News Reels on Social Media with Generative AI}, year = {2023}, type = {Video}, url = {https://youtu.be/WQZcbdp5yJQ}, author = {Sitong Wang and Samia Menon and Tao Long and Keren Henderson and Dingzeyu Li and Kevin Crowston and Mark Hansen and Jeffrey V. Nickerson and Lydia B. Chilton} } @article {soni2021discovering, title = {Discovering features in gravitational-wave data through detector characterization, citizen science and machine learning}, journal = {Classical and Quantum Gravity}, volume = {38}, year = {2021}, doi = {10.1088/1361-6382/ac1ccb}, author = {S Soni and C P L Berry and S B Coughlin and M Harandi and C B Jackson and K Crowston and C {\O}sterlund and O Patane and A K Katsaggelos and L Trouille and V-G Baranowski and W F Domainko and K Kaminski and M A Lobato Rodriguez and U Marciniak and P Nauta and G Niklasch and R R Rote and B T{\'e}gl{\'a}s and C Unsworth and C Zhang} } @article {9998, title = {Examining Open Innovation in Science (OIS): What Open Innovation can and cannot offer the science of science}, journal = {Innovation: Organization \& Management}, year = {2021}, abstract = {

Scholars across disciplines increasingly hear calls for more open and collaborative approaches to scientific research. The concept of Open Innovation in Science (OIS) provides a framework that integrates dispersed research efforts aiming to understand the antecedents, contingencies, and consequences of applying open and collaborative research practices. While the OIS framework has already been taken up by science of science scholars, its conceptual underpinnings require further specification. In this essay, we critically examine the OIS concept and bring to light two key aspects: 1) how OIS builds upon Open Innovation (OI) research by adopting its attention to boundary-crossing knowledge flows and by adapting other concepts developed and researched in OI to the science context as exemplified by two OIS cases in the area of research funding; 2) how OIS conceptualises knowledge flows across boundaries. While OI typically focuses on well-defined organizational boundaries, we argue that blurry and even invisible boundaries between communities of practice may more strongly constrain flows of knowledge related to openness and collaboration in science. Given the uptake of this concept, this essay brings needed clarity to the meaning of OIS, which has no particular normative orientation toward a close coupling between science and industry. We end by outlining the essay{\textquoteright}s contributions to OI and the science of science, as well as to science practitioners.

}, doi = {10.1080/14479338.2021.1999248}, author = {Susanne Beck and Marcel LaFlamme and Carsten Bergenholtz and Marcel Bogers and Tiare-Maria Brasseur and Marie-Louise Conradsen and Kevin Crowston and Diletta Di Marco and Agnes Effert and Despoina Filiou and Lars Frederiksen and Thomas Gillier and Marc Gruber and Carolin Haeussler and Karin Hoisl and Olga Kokshagina and Maria-Theresa Norn and Marion Poetz and Gernot Pruschak and Laia Pujol Priego and Agnieszka Radziwon and Alexander Ruser and Henry Sauermann and Sonali Shah and Julia Suess-Reyes and Christopher L. Tucci and Philipp Tuertscher and Jane Bj{\o}rn Vedel and Roberto Verganti and Jonathan Wareham and Sunny Mosangzi Xu} } @article {2019, title = {Classifying the unknown: Discovering novel gravitational-wave detector glitches using similarity learning}, journal = {Physical Review D}, volume = {99}, year = {2019}, pages = {082002}, abstract = {

The observation of gravitational waves from compact binary coalescences by LIGO and Virgo has begun a new era in astronomy. A critical challenge in making detections is determining whether loud transient features in the data are caused by gravitational waves or by instrumental or environmental sources. The citizen-science project Gravity Spy has been demonstrated as an efficient infrastructure for classifying known types of noise transients (glitches) through a combination of data analysis performed by both citizen volunteers and machine learning. We present the next iteration of this project, using similarity indices to empower citizen scientists to create large data sets of unknown transients, which can then be used to facilitate supervised machine-learning characterization. This new evolution aims to alleviate a persistent challenge that plagues both citizen-science and instrumental detector work: the ability to build large samples of relatively rare events. Using two families of transient noise that appeared unexpectedly during LIGO{\textquoteright}s second observing run, we demonstrate the impact that the similarity indices could have had on finding these new glitch types in the Gravity Spy program.

}, issn = {2470-0010}, doi = {10.1103/PhysRevD.99.082002}, author = {Scott Coughlin and Sara Bahaadini and Neda Rohani and Michael Zevin and Patane, Oli and Mahboobeh Harandi and Corey Brian Jackson and Noroozi, V. and Sarah Allen and Areeda, J. and Coughlin, M. and Ruiz, P. and Berry, C. P. L. and Kevin Crowston and Aggelos Katsaggelos and Andrew Lundgren and Carsten {\O}sterlund and Joshua Smith and Laura Trouille and Vicky Kalogera} } @article {2016, title = {Manifesto on Engineering Academic Software (Dagstuhl Perspectives Workshop 16252)}, volume = {6}, year = {2016}, month = {12/2106}, institution = {Schloss Dagstuhl {\textendash} Leibniz Center for Informatics}, address = {Wadern, Germany}, abstract = {Software is often a critical component of scientific research. It can be a component of the academic research methods used to produce research results, or it may itself be an academic research result. Software, however, has rarely been considered to be a citable artifact in its own right. With the advent of open-source software, artifact evaluation committees of conferences, and journals that include source code and running systems as part of the published artifacts, we foresee that software will increasingly be recognized as part of the academic process. The quality and sustainability of this software must be accounted for, both a priori and a posteriori. The Dagstuhl Perspectives Workshop on {\textquotedblleft}Engineering Academic Software{\textquotedblright} has examined the strengths, weaknesses, risks, and opportunities of academic software engineering. A key outcome of the workshop is this Dagstuhl Manifesto, serving as a roadmap towards future professional software engineering for software-based research instruments and other software produced and used in an academic context. The manifesto is expressed in terms of a series of actionable {\textquotedblleft}pledges{\textquotedblright} that users and developers of academic research software can take as concrete steps towards improving the environment in which that software is produced.}, author = {Alice Allen and Cecilia Aragon and Christoph Becker and Jeffrey Carver and Andrei Chi{\c s} and Benoit Combemale and Mike Croucher and Kevin Crowston and Daniel Garijo and Ashish Gehani and Carole Goble and Robert Haines and Robert Hirschfeld and James Howison and Kathryn Huff and Caroline Jay and Daniel S. Katz and Claude Kirchner and Katie Kuksenok and Ralf L{\"a}mmel and Oscar Nierstrasz and Matt Turk and van Nieuwpoort, Rob and Matthew Vaughn and Jurgen Vinju} } @article {9998, title = {Assessing IS research impact}, journal = {Communications of the Association for Information Systems}, volume = {36}, year = {2015}, chapter = {Article 7}, abstract = {

Based on the International Conference on Information Systems{\textquoteright} (ICIS) 2013 senior scholars{\textquoteright} forum, this paper shares insights on IS research impact assessment. We define research impact as conducting research that makes a difference to individuals, businesses, industries and societies. While assessment groups like AACSB (the Association to Advance Collegiate Schools of Business) want scholars to make an impact, sometimes they operationalize impact in ways that may encourage scholars to pursue research goals tangential to making a difference. The purpose of this paper is to stimulate thinking in the IS community on creating research assessment techniques that encourage our scholars to make a difference.

}, doi = {10.17705/1CAIS.03607}, author = {Niederman, Fred and Kevin Crowston and Koch, Hope and Krcmar, Helmut and Powell, Philip and E. Burton Swanson} } @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 {2011, title = {Mechanisms for Data Quality and Validation in Citizen Science}, booktitle = {"Computing for Citizen Science" workshop at the IEEE eScience Conference}, year = {2011}, month = {12/2011}, address = {Stockholm, Sweden}, abstract = {Data quality is a primary concern for researchers employing public participation in scientific research, or {\textquotedblleft}citizen science,{\textquotedblright} to accomplish data collection and analysis tasks. This mode of scientific collaboration relies on contributions from a large, often unknown population of volunteers with widely variable expertise. In this paper, we review the commonly employed mechanisms for ensuring data quality. We also discuss results of a survey of citizen science projects that reports on the use of some of these mechanisms, noting that it is most common for projects to employ multiple mechanisms to ensure data quality and appropriate levels of validation.}, keywords = {Citizen Science, data quality, data validation}, url = {http://itee.uq.edu.au/~eresearch/workshops/compcitsci2011/index.html}, attachments = {https://crowston.syr.edu./sites/crowston.syr.edu/files/PID2090593.pdf}, author = {Wiggins, Andrea and Newman, Greg and Stevenson, Robert D. and Kevin Crowston} } @proceedings {Roussinov:2001a, title = {Genre based navigation on the Web}, year = {2001}, publisher = {IEEE}, address = {Maui, HI, January}, abstract = {We report on our ongoing study of using the genre of Web pages to facilitate information exploration. By genre, we mean socially recognized regularities of form and purpose in documents (e.g., a letter, a memo, a research paper). Our study had three phases. First, through a user study, we identified genres which most/least frequently meet searchers{\textquoteright} information needs. We found that certain genres are better suited for certain types of needs. We identified five (5) major groups of document genres that might be used in an interactive search tool that would allow genrebased navigation. We tried to balance the following dual objectives: 1) each group should be recognizable by a computer algorithm as easily as possible 2) each group has a better chance of satisfying particular types of information needs. Finally, we developed a novel user interface for a web searching that allows genre-based navigation through three major functionalities: 1) limiting search to specified genres 2) visualizing the hierarchy of genres discovered in the search results and 3) accepting user feedback on the relevancy of the specified genres.}, isbn = {0-7695-0981-9 }, doi = {10.1109/HICSS.2001.926478}, attachments = {https://crowston.syr.edu./sites/crowston.syr.edu/files/09814013.pdf}, author = {Roussinov, Dmitri and Kevin Crowston and Nilan, Michael and Kwa{\'s}nik, Barbara H. and Xiaozhong Liu and Cai, J.} } @article {Kwasnik:2000, title = {Identifying document genre to improve web search effectiveness}, volume = {27}, number = {2}, year = {2001}, pages = {23{\textendash}26}, issn = {0095-4403}, doi = {10.1002/bult.194}, url = {http://www.asis.org/Bulletin/Dec-01/kwasnikartic.html}, author = {Kwa{\'s}nik, Barbara H. and Kevin Crowston and Nilan, Michael and Roussinov, Dmitri} }