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1. Open Data and Open Source GIS

   https://doi.org/10.1016/B978-0-12-409548-9.09592-0  

   Ye, Xinyue (January 2018, Comprehensive Geographic Information Systems)
2. Enhanced Open-Circuit Voltage in Perovskite Solar Cells with Open-Cage [60]Fullerene Derivatives as Electron-Transporting Materials

   https://doi.org/10.3390/ma12081314  

   Castro, Edison; Artigas, Albert; Pla-Quintana, Anna; Roglans, Anna; Liu, Fang; Perez, Frank; Lledó, Agustí; Zhu, X.-Y.; Echegoyen, Luis (April 2019, Materials)

   The synthesis, characterization, and incorporation of open-cage [60]fullerene derivatives as electron-transporting materials (ETMs) in perovskite solar cells (PSCs) with an inverted planar (p-i-n) structure is reported. Following optical and electrochemical characterization of the open-cage fullerenes 2a–c, p-i-n PSCs with a indium tin oxide (ITO)/poly(3,4-ethylenedioxythiophene)-polystyrene sulfonate (PEDOT:PSS)/perovskite/fullerene/Ag structure were prepared. The devices obtained from 2a–b exhibit competitive power conversion efficiencies (PCEs) and improved open-circuit voltage (Voc) values (>1.0 V) in comparison to a reference cell based on phenyl-C61-butyric-acid methyl-ester (PC61BM). These results are rationalized in terms of a) the higher passivation ability of the open-cage fullerenes with respect to the other fullerenes, and b) a good overlap between the highest occupied molecular orbital/lowest unoccupied molecular orbital (HOMO/LUMO) levels of 2a–b and the conduction band of the perovskite. 

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3. Open data and digital morphology

   https://doi.org/10.1098/rspb.2017.0194  

   Davies, Thomas G.; Rahman, Imran A.; Lautenschlager, Stephan; Cunningham, John A.; Asher, Robert J.; Barrett, Paul M.; Bates, Karl T.; Bengtson, Stefan; Benson, Roger B.; Boyer, Doug M.; et al (April 2017, Proceedings of the Royal Society B: Biological Sciences)
4. Uncertain risk: assessing open data signals

   https://doi.org/10.1108/TG-09-2019-0086  

   Washington, Anne L. (June 2020, Transforming Government: People, Process and Policy)

   Purpose Open data resources contain few signals for assessing their suitability for data analytics. The purpose of this paper is to characterize the uncertainty experienced by open data consumers with a framework based on economic theory. Design/methodology/approach Drawing on information asymmetry theory about market exchanges, this paper investigates the practical challenges faced by data consumers seeking to reuse open data. An inductive qualitative analysis of over 2,900 questions asked between 2013 and 2018 on an internet forum identified how a community of 15,000 open data consumers expressed uncertainty about data sources. Findings Open data consumers asked direct questions that expressed uncertainty about the availability, interoperability and interpretation of data resources. Questions focused on future value and some requests were devoted to seeking data that matched known sources. The study proposes a data signal framework that explains uncertainty about open data within the context of control and visibility. Originality/value The proposed framework bridges digital government practice to information signaling theory. The empirical evidence substantiates market aspects of open data portals. This paper provided a needed case study of how data consumers experience uncertainty. The study integrates established theories about risk to improve the reuse of open data. 

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5. Approximate Query Answering over Open Data

   https://doi.org/10.1145/3597465.3605227  

   Zhang, Mengqi; Mundra, Pranay; Chikweze, Chukwubuikem; Nargesian, Fatemeh; Weikum, Gerhard (June 2023, HILDA'23: The SIGMOD 2023 Workshop on Human-in-the-Loop Data Analytics)

   Open knowledge, including open data and publicly available knowledge bases, offers a rich opportunity for data scientists for analysis and query answering, but comes with big obstacles due to the diverse, noisy, and incomplete nature of its data eco-system. This paper proposes a vision for enabling approximate QUery answering over Open Knowledge (Quok), with a focus on supporting analytic tasks that involve identifying relevant data and computing aggregations. We define the problem, outline a system architecture, and discuss challenges and approaches to taming the uncertainty and incompleteness of open knowledge. 

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