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Author: Fiebig, Markus × DDC: 500 ×

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    Curating Scientific Information in Knowledge Infrastructures
    (Paris : CODATA, 2018) Stocker, Markus; Paasonen, Pauli; Fiebig, Markus; Zaidan, Martha A.; Hardisty, Alex
    Interpreting observational data is a fundamental task in the sciences, specifically in earth and environmental science where observational data are increasingly acquired, curated, and published systematically by environmental research infrastructures. Typically subject to substantial processing, observational data are used by research communities, their research groups and individual scientists, who interpret such primary data for their meaning in the context of research investigations. The result of interpretation is information—meaningful secondary or derived data—about the observed environment. Research infrastructures and research communities are thus essential to evolving uninterpreted observational data to information. In digital form, the classical bearer of information are the commonly known “(elaborated) data products,” for instance maps. In such form, meaning is generally implicit e.g., in map colour coding, and thus largely inaccessible to machines. The systematic acquisition, curation, possible publishing and further processing of information gained in observational data interpretation—as machine readable data and their machine readable meaning—is not common practice among environmental research infrastructures. For a use case in aerosol science, we elucidate these problems and present a Jupyter based prototype infrastructure that exploits a machine learning approach to interpretation and could support a research community in interpreting observational data and, more importantly, in curating and further using resulting information about a studied natural phenomenon.
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    Collocated observations of cloud condensation nuclei, particle size distributions, and chemical composition
    (London : Nature Publ. Group, 2017) Schmale, Julia; Henning, Silvia; Henzing, Bas; Keskinen, Helmi; Sellegri, Karine; Ovadnevaite, Jurgita; Bougiatioti, Aikaterini; Kalivitis, Nikos; Stavroulas, Iasonas; Jefferson, Anne; Park, Minsu; Schlag, Patrick; Kristensson, Adam; Iwamoto, Yoko; Pringle, Kirsty; Reddington, Carly; Aalto, Pasi; Äijälä, Mikko; Baltensperger, Urs; Bialek, Jakub; Birmili, Wolfram; Bukowiecki, Nicolas; Ehn, Mikael; Fjæraa, Ann Mari; Fiebig, Markus; Frank, Göran; Fröhlich, Roman; Frumau, Arnoud; Furuya, Masaki; Hammer, Emanuel; Heikkinen, Liine; Herrmann, Erik; Holzinger, Rupert; Hyono, Hiroyuki; Kanakidou, Maria; Kiendler-Scharr, Astrid; Kinouchi, Kento; Kos, Gerard; Kulmala, Markku; Mihalopoulos, Nikolaos; Motos, Ghislain; Nenes, Athanasios; O’Dowd, Colin; Paramonov, Mikhail; Petäjä, Tuukka; Picard, David; Poulain, Laurent; Prévôt, André Stephan Henry; Slowik, Jay; Sonntag, Andre; Swietlicki, Erik; Svenningsson, Birgitta; Tsurumaru, Hiroshi; Wiedensohler, Alfred; Wittbom, Cerina; Ogren, John A.; Matsuki, Atsushi; Yum, Seong Soo; Myhre, Cathrine Lund; Carslaw, Ken; Stratmann, Frank; Gysel, Martin
    Cloud condensation nuclei (CCN) number concentrations alongside with submicrometer particle number size distributions and particle chemical composition have been measured at atmospheric observatories of the Aerosols, Clouds, and Trace gases Research InfraStructure (ACTRIS) as well as other international sites over multiple years. Here, harmonized data records from 11 observatories are summarized, spanning 98,677 instrument hours for CCN data, 157,880 for particle number size distributions, and 70,817 for chemical composition data. The observatories represent nine different environments, e.g., Arctic, Atlantic, Pacific and Mediterranean maritime, boreal forest, or high alpine atmospheric conditions. This is a unique collection of aerosol particle properties most relevant for studying aerosol-cloud interactions which constitute the largest uncertainty in anthropogenic radiative forcing of the climate. The dataset is appropriate for comprehensive aerosol characterization (e.g., closure studies of CCN), model-measurement intercomparison and satellite retrieval method evaluation, among others. Data have been acquired and processed following international recommendations for quality assurance and have undergone multiple stages of quality assessment.