Motivating and Sustaining Participation in VGI

Volunteers are the key component in the collection of Volunteered Geographic Information (VGI), so what motivates their participation, what strategies work in recruitment and how sustainability of participation can be achieved are key questions that need to be answered to inform VGI system design and implementation. This chapter reviews studies that have examined these questions and presents the main motivational factors that drive volunteer participation, as determined from empirical research. Some best practices from broader citizen science applications are also presented that may have relevance for VGI initiatives. Finally, a set of case studies from our experiences are used to illustrate how volunteers have been motivated to collect VGI through mapping parties, gamification and working with schools

Increased luminescence efficiency by synergistic exploitation of lipo/hydrophilic co-solvency and supramolecular design

We use steady-state and time-resolved photoluminescence (PL) spectroscopy to investigate the luminescent properties of a sulfonated poly(diphenylenevinylene) lithium salt (PDV.Li) in water/propanol solutions at different concentrations, with a view to assessing its aggregation behavior. In particular, we compare results from uninsulated PDV.Li and cyclodextrin-threaded PDV.Li polyrotaxane (PDV.Li⊂β-CD). We find that addition of 1-propanol (≥20 weight%) leads to a significant blue-shift (of ∼0.20 eV) of the PL spectra, that we assign to suppressed interchain aggregation in PDV.Li solutions, with a concomitant fourfold increase in the fluorescence quantum efficiency (i.e. from 14 to 60%). Surprisingly, a moderate concentration of propanol increases further the luminescence efficiency even for PDV.Li⊂β-CD, whose supramolecular encapsulation already provides a shield against aggregation. Indeed, addition of propanol reduces the solvent polarity, and therefore helps solubilizing these materials that are still largely aromatic in nature. Interestingly, however, both uninsulated PDV.Li and polyrotaxane solutions exhibit signs of aggregation at high propanol fraction (>70%) with a distinctively weaker coupling than that of interchain states in PDV.Li at high water concentration and in pure water in particular. While we ascribe such behavior to a poor solvation of the polar moieties, we also report a different strength of aggregation for PDV.Li and PDV.Li⊂β-CD that can be attributed to the presence of the cyclodextrin rings. In PDV.Li⊂β-CD hydrogen bonding between the cyclodextrin rings may lead to closer packing between the polymer chains. We therefore suggest that a content of propanol between 30 and 70% provides a good balance of hydrophobic and hydrophilic interactions both for PDV.Li and PDV.Li⊂β-CD

Rhythmic dynamics and synchronization via dimensionality reduction : application to human gait

Reliable characterization of locomotor dynamics of human walking is vital to understanding the neuromuscular control of human locomotion and disease diagnosis. However, the inherent oscillation and ubiquity of noise in such non-strictly periodic signals pose great challenges to current methodologies. To this end, we exploit the state-of-the-art technology in pattern recognition and, specifically, dimensionality reduction techniques, and propose to reconstruct and characterize the dynamics accurately on the cycle scale of the signal. This is achieved by deriving a low-dimensional representation of the cycles through global optimization, which effectively preserves the topology of the cycles that are embedded in a high-dimensional Euclidian space. Our approach demonstrates a clear advantage in capturing the intrinsic dynamics and probing the subtle synchronization patterns from uni/bivariate oscillatory signals over traditional methods. Application to human gait data for healthy subjects and diabetics reveals a significant difference in the dynamics of ankle movements and ankle-knee coordination, but not in knee movements. These results indicate that the impaired sensory feedback from the feet due to diabetes does not influence the knee movement in general, and that normal human walking is not critically dependent on the feedback from the peripheral nervous system

Development of a Voice Virtual Assistant for the Geospatial Data Visualization Application on the Web

Voice assistants can elevate interaction in geospatial data web platforms. This research introduces a voice assistant in the BStreams platform and focuses on understanding user commands in the geospatial domain. We developed a specialised geospatial discourse framework through structured prototyping. A survey with 66 participants revealed prevalent English geospatial terminologies. Using ChatGPT, we found the term suggestions aligned with survey results, with a notable correlation (r = 0.81, p < 0.01) between the NPL model’s probability scores and term prevalence in survey data. Our study also incorporated usability tests on the application, which uses tools like Web Speech API, Leaflet, and Mapbox geocoding. Results from these tests reaffirm the potential of voice assistants in enhancing geospatial data visualisation, though challenges persist in areas like language understanding and domain knowledge. The paper advocates for further research to refine the integration of voice technology in this domain

BIG GEO DATA MANAGEMENT: AN EXPLORATION WITH SOCIAL MEDIA AND TELECOMMUNICATIONS OPEN DATA

The term Big Data has been recently used to define big, highly varied, complex data sets, which are created and updated at a high speed and require faster processing, namely, a reduced time to filter and analyse relevant data. These data is also increasingly becoming Open Data (data that can be freely distributed) made public by the government, agencies, private enterprises and among others. There are at least two issues that can obstruct the availability and use of Open Big Datasets: Firstly, the gathering and geoprocessing of these datasets are very computationally intensive; hence, it is necessary to integrate high-performance solutions, preferably internet based, to achieve the goals. Secondly, the problems of heterogeneity and inconsistency in geospatial data are well known and affect the data integration process, but is particularly problematic for Big Geo Data. Therefore, Big Geo Data integration will be one of the most challenging issues to solve. With these applications, we demonstrate that is possible to provide processed Big Geo Data to common users, using open geospatial standards and technologies. NoSQL databases like MongoDB and frameworks like RASDAMAN could offer different functionalities that facilitate working with larger volumes and more heterogeneous geospatial data sources

Sample-Averaged Biexciton Quantum Yield Measured by Solution-Phase Photon Correlation

The brightness of nanoscale optical materials such as semiconductor nanocrystals is currently limited in high excitation flux applications by inefficient multiexciton fluorescence. We have devised a solution-phase photon correlation measurement that can conveniently and reliably measure the average biexciton-to-exciton quantum yield ratio of an entire sample without user selection bias. This technique can be used to investigate the multiexciton recombination dynamics of a broad scope of synthetically underdeveloped materials, including those with low exciton quantum yields and poor fluorescence stability. Here, we have applied this method to measure weak biexciton fluorescence in samples of visible-emitting InP/ZnS and InAs/ZnS core/shell nanocrystals, and to demonstrate that a rapid CdS shell growth procedure can markedly increase the biexciton fluorescence of CdSe nanocrystals.United States. Dept. of Energy. Office of Basic Energy Sciences (DE-FG02-07ER46454)United States. Dept. of Energy. Office of Basic Energy Sciences (DE-SC0001088)National Institutes of Health (U.S.) (9P41EB015871-26A1

Crystal Phase Transitions in the Shell of PbS CdS Core Shell Nanocrystals Influences Photoluminescence Intensity

ABSTRACT We reveal the existence of two different crystalline phases, i.e., the metastable rock salt and the equilibrium zinc blende phase within the CdS shell of PbS CdS core shell nanocrystals formed by cationic exchange. The chemical composition profile of the core shell nanocrystals with different dimensions is determined by means of anomalous small angle X ray scattering with subnanometer resolution and is compared to X ray diffraction analysis. We demonstrate that the photoluminescence emission of PbS nanocrystals can be drastically enhanced by the formation of a CdS shell. Especially, the ratio of the two crystalline phases in the shell significantly influences the photoluminescence enhancement. The highest emission was achieved for chemically pure CdS shells below 1 nm thickness with a dominant metastable rock salt phase fraction matching the crystal structure of the PbS core. The metastable phase fraction decreases with increasing shell thickness and increasing Exchange times. The photoluminescence intensity depicts a constant decrease with decreasing metastable rock salt phase fraction but Shows an abrupt drop for shells above 1.3 nm thickness. We relate this effect to two different transition mechanisms for changing from the metastable rock salt phase to the equilibrium zinc blende phase depending on the shell thicknes

Capacity Building for GIS-based SDG Indicator Analysis with Global High-resolution Land Cover Datasets

The support of geospatial data and technologies for the United Nations Sustainable Development Goals (SDG) framework is critical for assessing and monitoring key indicators, revealing the planet’s trajectory towards sustainability. The availability of global open geospatial datasets, especially high-resolution land cover datasets, provides significant opportunities for computing and comparing indicators across different regions and scales. However, barriers to their proficient use remain due to a lack of data awareness, management and processing capacities using geographic information systems software. To address this, the”Capacity Building for GIS-based SDG Indicator Analysis with Global High-resolution Land Cover Datasets” project created open training material on discovering, accessing, and manipulating global geospatial datasets for computing SDG indicators. The material focuses on water and terrestrial ecosystems, urban environments, and climate, by leveraging world-class global geospatial datasets and using the Free and Open Source Software QGIS. The training material is released under a Creative Commons Attribution 4.0 License, ensuring broad accessibility and facilitating continuous improvement