Temporal Analysis of Activity Patterns of Editors in Collaborative Mapping Project of OpenStreetMap

In the recent years Wikis have become an attractive platform for social studies of the human behaviour. Containing millions records of edits across the globe, collaborative systems such as Wikipedia have allowed researchers to gain a better understanding of editors participation and their activity patterns. However, contributions made to Geo-wikis_wiki-based collaborative mapping projects_ differ from systems such as Wikipedia in a fundamental way due to spatial dimension of the content that limits the contributors to a set of those who posses local knowledge about a specific area and therefore cross-platform studies and comparisons are required to build a comprehensive image of online open collaboration phenomena. In this work, we study the temporal behavioural pattern of OpenStreetMap editors, a successful example of geo-wiki, for two European capital cities. We categorise different type of temporal patterns and report on the historical trend within a period of 7 years of the project age. We also draw a comparison with the previously observed editing activity patterns of Wikipedia.Comment: Submitte

Gender Imbalance and Spatiotemporal Patterns of Contributions to Citizen Science Projects: The Case of Zooniverse

Citizen Science is research undertaken by professional scientists and members of the public collaboratively. Despite numerous benefits of citizen science for both the advancement of science and the community of the citizen scientists, there is still no comprehensive knowledge of patterns of contributions, and the demography of contributors to citizen science projects. In this paper we provide a first overview of spatiotemporal and gender distribution of citizen science workforce by analyzing 54 million classifications contributed by more than 340 thousand citizen science volunteers from 198 countries to one of the largest online citizen science platforms, Zooniverse. First we report on the uneven geographical distribution of the citizen scientist and model the variations among countries based on the socio-economic conditions as well as the level of research investment in each country. Analyzing the temporal features of contributions, we report on high “burstiness” of participation instances as well as the leisurely nature of participation suggested by the time of the day that the citizen scientists were the most active. Finally, we discuss the gender imbalance among online citizen scientists (about 30% female) and compare it with other collaborative projects as well as the gender distribution in more formal scientific activities. Online citizen science projects need further attention from outside of the academic community, and our findings can help attract the attention of public and private stakeholders, as well as to inform the design of the platforms and science policy making processes

Technoethics and Human Rights: The Metaethical Implications of Crisismapping and the Right to Privacy in Post-Disaster, Post-Conflict Scenarios

Do invasive digital approaches to disaster response come at too high of a cost to privacy, such that we should seek alternative methods or regulations? This paper examines the tension between the right to privacy and crisismapping, a new technological advancement in emergency response. After mapping the critical international institutions and stakeholders, the paper grounds interests to effective triage and to digital privacy in international human rights law. A thought experiment is offered to show our conflicting intuitions when privacy is weighed against critical safety interests, and multiple procedures are evaluated as means to reconcile these interests and determine the extent of the right to privacy. Ultimately, the paper calls for an expanded inquiry by the United Nations Special Rapporteur on the Right to Privacy, who has the power to engage multiple stakeholders for a fair and inclusive new approach. Privacy costs are too fundamental for emergency response to proceed without proper scrutiny

BITOUR: A Business Intelligence Platform for Tourism Analysis

[EN] Integrating collaborative data in data-driven Business Intelligence (BI) system brings an opportunity to foster the decision-making process towards improving tourism competitiveness. This article presents BITOUR, a BI platform that integrates four collaborative data sources (Twitter, Openstreetmap, Tripadvisor and Airbnb). BITOUR follows a classical BI architecture and provides functionalities for data transformation, data processing, data analysis and data visualization. At the core of the data processing, BITOUR offers mechanisms to identify tourists in Twitter, assign tweets to attractions and accommodation sites from Tripadvisor and Airbnb, analyze sentiments in opinions issued by tourists, and all this using geolocation objects in Openstreetmap. With all these ingredients, BITOUR enables data analysis and visualization to answer questions like the most frequented places by tourists, the average stay length or the view of visitors of some particular destination.This work has been supported by COLCIENCIAS through a PhD scholarship. This work is supported by the Spanish MINECO project TIN2017-88476-C2-1-R.Bustamante, A.; Sebastiá Tarín, L.; Onaindia De La Rivaherrera, E. (2020). BITOUR: A Business Intelligence Platform for Tourism Analysis. ISPRS International Journal of Geo-Information. 9(11):1-23. https://doi.org/10.3390/ijgi9110671S123911Nakahira, K. T., Akahane, M., & Fukami, Y. (2012). The Difference and Limitation of Cognition for Piano Playing Skill with Difference Educational Design. Smart Innovation, Systems and Technologies, 609-617. doi:10.1007/978-3-642-29934-6_59Chua, A., Servillo, L., Marcheggiani, E., & Moere, A. V. (2016). 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Managing Data Quality in Observational Citizen Science

University of Minnesota Ph.D. dissertation.December 2017. Major: Computer Science. Advisor: Loren Terveen. 1 computer file (PDF); viii, 103 pages.Observational citizen science is an effective way to supplement the environmental datasets compiled by professional scientists. Involving volunteers in data collection has the added educational benefits of increased scientific awareness and local ownership of environmental concerns. This thesis provides an in-depth exploration of observational citizen science and the associated challenges and opportunities for HCI research. We focus on data quality as a key lens for understanding observational citizen science, and how it differs from the related domains of crowdsourcing, open collaboration, and volunteered geographic information. In order to understand data quality, we performed a qualitative analysis of data quality assurance practices in River Watch, a regional water quality monitoring program. We found that data quality in River Watch is primarily maintained through universal adherence to standard operating procedures, rather than through a computable notion of “accuracy”. We also found that rigorous data quality assurance practices appear to enhance rather than hinder the educational goals of the program participants. In order to measure data quality, we conducted a quantitative analysis of CoCoRaHS, a multinational citizen science project for observing precipitation. Given the importance of long-term participation to data consumers, we focused on volunteer retention as our primary metric for data quality. Through survival analysis, we found that participant age is a significant predictor of retention. Compared to all other age groups, participants aged 60-70 are much more likely to sign up for CoCoRaHS, and to remain active for several years. We propose that the nature of the task can profoundly influence the types of participants attracted to a project. In order to improve data quality, we derived a general workflow model for observational citizen science, drawing on our findings in River Watch, CoCoRaHS, and similar programs. We propose a data model for preserving provenance metadata that allows for ongoing data exchange between disparate technical systems and participant skill levels. We conclude with general principles that should be taken into consideration when designing systems and protocols for managing citizen science data