Launching the VASCO citizen science project (2009.10813v4)

Abstract: The Vanishing & Appearing Sources during a Century of Observations (VASCO) project investigates astronomical surveys spanning a time interval of 70 years, searching for unusual and exotic transients. We present herein the VASCO Citizen Science Project, which can identify unusual candidates driven by three different approaches: hypothesis, exploratory, and machine learning, which is particularly useful for SETI searches. To address the big data challenge, VASCO combines three methods: the Virtual Observatory, user-aided machine learning, and visual inspection through citizen science. Here we demonstrate the citizen science project and its improved candidate selection process, and we give a progress report. We also present the VASCO citizen science network led by amateur astronomy associations mainly located in Algeria, Cameroon, and Nigeria. At the moment of writing, the citizen science project has carefully examined 15,593 candidate image pairs in the data (ca. 10% of the candidates), and has so far identified 798 objects classified as "vanished". The most interesting candidates will be followed up with optical and infrared imaging, together with the observations by the most potent radio telescopes.

• The paper introduces a novel citizen science framework that integrates historical astronomical data with AI and volunteer input to identify rare and vanishing celestial objects.
• The project employs virtual observatory tools, user-aided machine learning, and global visual inspections to analyze over 15,500 candidate image pairs, identifying 798 tentative vanishings.
• The initiative demonstrates how combining human insight with advanced computational methods can revolutionize astronomical research and scale to big data challenges.

Essay on "Launching the VASCO Citizen Science Project"

The paper "Launching the VASCO Citizen Science Project" introduces an initiative aimed at uncovering unusual astronomical phenomena by leveraging the potential of both citizen science and advanced computational methods. This project is part of the broader Vanishing and Appearing Sources during a Century of Observations (VASCO) program, which ambitiously investigates data from astronomical surveys conducted over a 70-year span. The primary aim is to identify celestial objects that have appeared or vanished over this duration, focusing particularly on phenomena that are either rare or have been overlooked by traditional transient sky surveys.

Methodological Framework

The VASCO Citizen Science Project adopts a multifaceted approach to tackle the extensive data analysis required. The paper details the project's reliance on three core methodologies:

1. Virtual Observatory Tools: This approach facilitates access to and management of the vast databases of historical astronomical data, ensuring efficient cross-matching and comparison across different epochs.
2. User-Aided Machine Learning: Volunteers interact with an AI system designed to learn and improve through user inputs, thereby enhancing candidate selection procedures for potential anomalous objects.
3. Visual Inspection via Citizen Science: Engaging amateur astronomers and enthusiasts around the globe, this method fosters a cooperative framework where human insight aids in identifying anomalies that may elude algorithmic detection.

Progress and Results

As reported, approximately 15,593 candidate image pairs have undergone examination, resulting in 798 objects being tentatively classified as "vanished." The paper emphasizes the human factor in these discoveries, as traditional machine learning algorithms alone cannot replicate the nuanced pattern recognition capabilities innate to human cognition. The most promising candidates will undergo further scrutiny through advanced optical and infrared imaging, in conjunction with observation by formidable radio telescopes to determine their nature and characteristics.

Implications and Future Prospects

This initiative not only underscores the critical role of citizen science in modern astronomy but also explores its potential within fields like SETI (Search for Extraterrestrial Intelligence). The project’s foundation on historical data sets it apart by focusing beyond transient phenomena, expanding the potential discovery landscape to include chronologically extreme or infrequent occurrences which often escape notice in contemporary transient-focused surveys.

Moreover, with the introduction of advanced AI frameworks intertwined with human analysis, this project could set a precedent for future astronomical studies involving massive multi-decade datasets. The development and deployment of AI models that continually learn from user inputs present a paradigm shift in how citizen science can significantly contribute to scientific discovery beyond manual curation and analysis.

Conclusion

The VASCO Citizen Science Project exemplifies a harmonious integration of technology, public involvement, and scientific inquiry, paving a pathway for novel discoveries that challenge current astrophysical models. As astronomical datasets continue to grow exponentially, the need for innovative methodologies that combine human intellect with computational prowess becomes increasingly apparent. This project not only could elucidate hidden secrets of the cosmos but also represents an evolving frontier for citizen science in the era of big data, offering a scalable model for research in other scientific disciplines where similar challenges persist.