Tradeoffs and tools for data quality, privacy, transparency, and trust in citizen science

Anhalt‐Depies, Christine; Stenglein, Jennifer L.; Zuckerberg, Benjamin; Townsend, Philip A.; Rissman, Adena R.

doi:10.1016/j.biocon.2019.108195

Cited by 56 publications

(41 citation statements)

References 33 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Visualization‐based interfaces can play a key role in helping data owners, subjects, custodians, and consumers dynamically evaluate the disclosure risks of shared data. For data owners or custodians, visual interfaces [GHK*16, CRVFS15] can help communicate privacy risks by suggesting non‐obvious, probabilistic linkages [HWL*19], let them dynamically evaluate the trade‐offs among data utility and privacy risks [ADSZ*19] by visualizing privacy outcomes from new and evolving metrics [JSH*17], and make more confident decisions regarding data sharing [BVM*17].…”

Section: Gaps and Research Opportunitiesmentioning

confidence: 99%

Privacy‐Preserving Data Visualization: Reflections on the State of the Art and Research Opportunities

Bhattacharjee

Chen

Dasgupta

2020

Computer Graphics Forum

View full text Add to dashboard Cite

Preservation of data privacy and protection of sensitive information from potential adversaries constitute a key socio‐technical challenge in the modern era of ubiquitous digital transformation. Addressing this challenge needs analysis of multiple factors: algorithmic choices for balancing privacy and loss of utility, potential attack scenarios that can be undertaken by adversaries, implications for data owners, data subjects, and data sharing policies, and access control mechanisms that need to be built into interactive data interfaces. Visualization has a key role to play as part of the solution space, both as a medium of privacy‐aware information communication and also as a tool for understanding the link between privacy parameters and data sharing policies. The field of privacy‐preserving data visualization has witnessed progress along many of these dimensions. In this state‐of‐the‐art report, our goal is to provide a systematic analysis of the approaches, methods, and techniques used for handling data privacy in visualization. We also reflect on the road‐map ahead by analyzing the gaps and research opportunities for solving some of the pressing socio‐technical challenges involving data privacy with the help of visualization.

show abstract

Section: Gaps and Research Opportunitiesmentioning

confidence: 99%

Privacy‐Preserving Data Visualization: Reflections on the State of the Art and Research Opportunities

Bhattacharjee

Chen

Dasgupta

2020

Computer Graphics Forum

View full text Add to dashboard Cite

show abstract

“…Scientific research must gather valid information, and while traditional citizen science uses trained volunteers to ensure data accuracy, it has participant limitations and requires more money and effort (Gardiner et al 2012). If they are untrained, the data from citizens can be problematic, and furthermore, it takes time for researchers to verify the information with each reporter (Goffredo et al 2010;Bird et al 2014;Anhalt-Depies et al 2019).…”

Section: Discussionmentioning

confidence: 99%

Community‐based population monitoring for large baleen whales: the case study of Bryde's whale in Beibu Gulf of China

Zhang

Chen

et al. 2021

Integr. Zool.

View full text Add to dashboard Cite

Citizen science is a popular method for the long-term monitoring of the distribution of wild animals. The application of these methods in different species and environments still poses challenges, especially for aquatic animals. In this study, we investigated the distribution of the Bryde's whale (Balaenoptera edeni) in the Beibu Gulf of China by using scientific boat-based surveys and citizen science approaches using 2 different methods of data collection. First, we built our mobile app (Whale Guard) and installed it on fishermen's phones. Second, we used a popular instant messaging app (WeChat) to create an online fisherman community. We found that the mobile phone app collected far fewer reports (5 reports) than the online community group (42 reports, P < 0.01). By using a variety of incentives, we maintained the fisherman's community's activity without significant user loss (P < 0.01). We also found that the locations collected by social media applications in this study were consistent with observations from scientific boat-based transect surveys. The sightings distribution of Bryde's whales differed from those in previous surveys in that they were present across larger areas. Social media apps reported that 69% of reports was confirmed by more than one person, whereas Whale Guard reports were much lower (0, P <0.001). Community-based citizen science can greatly contribute to the long-term monitoring of Bryde's whales, and it has successfully overcome the challenges of data accessibility, accuracy, and fragmentation. Our study shows how to appropriately use citizen science in different community groups and community-based approaches make them useful for large baleen whale surveys.

show abstract

“…Providing simple language that enables users to understand their intellectual property rights for using CSD facilitates their use as open data. Ideally, such language should describe permissive intellectual property rights that eliminate restrictions on the use of the data and the documentation (Anhalt-Depies et al, 2019).…”

Section: Transparency In Information About Qa/qc Practices During the Data Production Processmentioning

confidence: 99%

“…Especially given the increased opportunity to supplement traditional scientific data with CSD, it is essential that the CSD be as trustworthy and of known quality as other scientific data (Swanson et al, 2016;Aceves-Bueno et al, 2017;Budde et al, 2017;Burgess et al, 2017;Kallimanis et al, 2017;Steger et al, 2017;Sandahl and Tøttrup, 2020). Information about the quality of CSD builds trust, provides opportunities for potential users to discover CSD that are appropriate for their purposes, and enables users to determine whether and how the data can be used to meet their objectives (Alabri and Hunter, 2010;Hunter et al, 2013;Freitag et al, 2016;Lukyanenko et al, 2016;Stevenson, 2018;Anhalt-Depies et al, 2019). The quality of CSD also can influence the analysis and interpretation of the data (Kelling et al, 2015;Clare et al, 2019).…”

Section: Introductionmentioning

confidence: 99%

Perspectives on Citizen Science Data Quality

et al. 2021

View full text Add to dashboard Cite

Information about data quality helps potential data users to determine whether and how data can be used and enables the analysis and interpretation of such data. Providing data quality information improves opportunities for data reuse by increasing the trustworthiness of the data. Recognizing the need for improving the quality of citizen science data, we describe quality assessment and quality control (QA/QC) issues for these data and offer perspectives on aspects of improving or ensuring citizen science data quality and for conducting research on related issues.

show abstract

Tradeoffs and tools for data quality, privacy, transparency, and trust in citizen science

Cited by 56 publications

References 33 publications

Privacy‐Preserving Data Visualization: Reflections on the State of the Art and Research Opportunities

Privacy‐Preserving Data Visualization: Reflections on the State of the Art and Research Opportunities

Community‐based population monitoring for large baleen whales: the case study of Bryde's whale in Beibu Gulf of China

Perspectives on Citizen Science Data Quality

Contact Info

Product

Resources

About