Characterizing Novelty as a Motivator in Online Citizen Science

Citizen science projects rely on the voluntary contribution of nonscientists to take part in scientific research projects. Projects taking place exclusively over the Internet face significant challenges, chief among them is the attracting and keeping the critical mass of volunteers needed to conduct the work outlined by the science team. The extent to which platforms can design experiences that positively influence volunteers’ motivation can help address the contribution challenges. Consequently, project organizers need to develop strategies to attract new participants and keep existing ones. One strategy to encourage participation is implementing features, which re-enforce motives known to change people’s attitudes towards contributing positively. The literature in psychology noted that novelty is an attribute of objects and environments that occasion curiosity in humans leading to exploratory behaviors, e.g., prolonged engagement with the object or environment. This dissertation described the design, implementation, and evaluation of an experiment conducted in three online citizen science projects. Volunteers received novelty cues when they classified data objects that no other volunteer had previously seen. The hypothesis was that exposure to novelty cues while classifying data positively influences motivational attitudes leading to increased engagement in the classification task and increased retention. The experiments resulted in mixed results. In some projects, novelty cues were universally salient, and in other projects, novelty cues had no significant impact on volunteers’ contribution behaviors. The results, while mixed, are promising since differences in the observed behaviors arise because of individual personality differences and the unique attributes found in each project setting. This research contributes to empirically grounded studies on motivation in citizen science with analyses that produce new insights and questions into the functioning of novelty and its impact on volunteers’ behaviors

Building an Apparatus: Refractive, Reflective, and Diffractive Readings of Trace Data

We propose a set of methodological principles and strategies for the use of trace data, i.e., data capturing performances carried out on or via information systems, often at a fine level of detail. Trace data comes with a number of methodological and theoretical challenges associated with the inseparable nature of the social and material. Drawing on Haraway and Barad’s distinctions among refraction, reflection, and diffraction, we compare three approaches to trace data analysis. We argue that a diffractive methodology allows us to explore how trace data are not given but created through the construction of a research apparatus to study trace data. By focusing on the diffractive ways in which traces ripple through an apparatus, it is possible to explore some of the taken-for-granted, invisible dynamics of sociomateriality. Equally important, this approach allows us to describe what distinctions emerge and when, within entwined phenomena in the research process. Empirically, we illustrate the guiding methodological principles and strategies by analyzing trace data from Gravity Spy, a crowdsourced citizen science project on Zooniverse.org. We conclude by suggesting that a diffractive methodology helps us draw together quantitative and qualitative research practices in new and productive ways that allow us to study and design for the entwined and dynamic sociomaterial practices found in contemporary organizations

Event Based Analysis of a Citizen Science Community: Are New and Non-sustained Users Included?

High turnover rates in online communities suggest the need for measures that move non-sustained community members towards sustained participation. Non-sustained members actively seek inclusion opportunities, but are often disappointed by the lack of access to existing members. One method of inclusion can be contact with existing members through dialogue on discussion boards. Understanding the structure of interactions between sustained and non-sustained members and can inform new strategies to address the high turnover rate and ensure community longevity. In this poster, we analyze the network structure of newcomer and existing member interaction through discussion posts. Through analysis of a citizen science community we ask: Are non-sustained and sustained participants engaged in conversations? The researcher analyzes the topological features of an affiliation network and centrality measures to determine the extent of interactions between these two groups. Finally, the researcher presents strategies to engage non-sustained participants in online.publishedye

The Genie in the Bottle: Different Stakeholders, Different Interpretations of Machine Learning

We explore how people developing or using a system with a machine-learning (ML) component come to understand the capabilities and challenges of ML. We draw on the social construction of technology (SCOT) tradition to frame our analysis of interviews and discussion board posts involving designers and users of a ML-supported citizen-science crowdsourcing project named Gravity Spy. We extend SCOT by anchoring our investigation in the different uses of the technology. We find that the type of understandings achieved by groups having less interaction with the technology is shaped more by outside influences and less by the specifics of the system and its role in the project. This initial understanding of how different participants understand and engage with ML points to challenges that need to be overcome to help users of a system deal with the opaque position that ML often holds in a work system

The Application of Modern Optimization Packages in Multisensor Data Assimilation

PyDDA is an expandable framework that integrates data from weather radars and forecasting models using SciPys optimization package to create meteorological fields

PyDDA: A New Pythonic Wind Retrieval Package

PyDDA (Pythonic Direct Data Assimilation) is a new community framework aimed at wind retrievals that depends only upon utilities in the SciPy ecosystem such as scipy, numpy, and dask. It can support retrievals of winds using information from weather radar networks constrained by high resolution forecast models over grids that cover thousands of kilometers at kilometer-scale resolution. Unlike past wind retrieval packages, this package can be installed using anaconda for easy installation and, with a focus on ease of use can retrieve winds from gridded radar and model data with just a few lines of code. The package is currently available for download at https://github.com/openradar/PyDDA

Reconciling Semiclassical and Bohmian Mechanics: II. Scattering states for discontinuous potentials

In a previous paper [J. Chem. Phys. 121 4501 (2004)] a unique bipolar decomposition, Psi = Psi1 + Psi2 was presented for stationary bound states Psi of the one-dimensional Schroedinger equation, such that the components Psi1 and Psi2 approach their semiclassical WKB analogs in the large action limit. Moreover, by applying the Madelung-Bohm ansatz to the components rather than to Psi itself, the resultant bipolar Bohmian mechanical formulation satisfies the correspondence principle. As a result, the bipolar quantum trajectories are classical-like and well-behaved, even when Psi has many nodes, or is wildly oscillatory. In this paper, the previous decomposition scheme is modified in order to achieve the same desirable properties for stationary scattering states. Discontinuous potential systems are considered (hard wall, step, square barrier/well), for which the bipolar quantum potential is found to be zero everywhere, except at the discontinuities. This approach leads to an exact numerical method for computing stationary scattering states of any desired boundary conditions, and reflection and transmission probabilities. The continuous potential case will be considered in a future publication.Comment: 18 pages, 8 figure

Analysis of nuclear transport signals in the human apurinic/apyrimidinic endonuclease (APE1/Ref1)

The mammalian abasic-endonuclease1/redox-factor1 (APE1/Ref1) is an essential protein whose subcellular distribution depends on the cellular physiological status. However, its nuclear localization signals have not been studied in detail. We examined nuclear translocation of APE1, by monitoring enhanced green fluorescent protein (EGFP) fused to APE1. APE1's nuclear localization was significantly decreased by deleting 20 amino acid residues from its N-terminus. Fusion of APE1's N-terminal 20 residues directed nuclear localization of EGFP. An APE1 mutant lacking the seven N-terminal residues (ND7 APE1) showed nearly normal nuclear localization, which was drastically reduced when the deletion was combined with the E12A/D13A double mutation. On the other hand, nearly normal nuclear localization of the full-length E12A/D13A mutant suggests that the first 7 residues and residues 8–13 can independently promote nuclear import. Both far-western analyses and immuno-pull-down assays indicate interaction of APE1 with karyopherin alpha 1 and 2, which requires the 20 N-terminal residues and implicates nuclear importins in APE1's nuclear translocation. Nuclear accumulation of the ND7 APE1(E12A/D13A) mutant after treatment with the nuclear export inhibitor leptomycin B suggests the presence of a previously unidentified nuclear export signal, and the subcellular distribution of APE1 may be regulated by both nuclear import and export