@article{KhiderEmileGeayMcKayetal.2019, author = {Khider, D. and Emile-Geay, J. and McKay, N. P. and Gil, Y. and Garijo, D. and Ratnakar, V and Alonso-Garcia, M. and Bertrand, S. and Bothe, O. and Brewer, P. and Bunn, A. and Chevalier, M. and Comas-Bru, L. and Csank, A. and Dassie, E. and DeLong, K. and Felis, T. and Francus, P. and Frappier, A. and Gray, W. and Goring, S. and Jonkers, L. and Kahle, M. and Kaufman, D. and Kehrwald, N. M. and Martrat, B. and McGregor, H. and Richey, J. and Schmittner, A. and Scroxton, N. and Sutherland, E. and Thirumalai, Kaustubh and Allen, K. and Arnaud, F. and Axford, Y. and Barrows, T. and Bazin, L. and Birch, S. E. Pilaar and Bradley, E. and Bregy, J. and Capron, E. and Cartapanis, O. and Chiang, H-W and Cobb, K. M. and Debret, M. and Dommain, R{\´e}ne and Du, J. and Dyez, K. and Emerick, S. and Erb, M. P. and Falster, G. and Finsinger, W. and Fortier, D. and Gauthier, Nicolas and George, S. and Grimm, E. and Hertzberg, J. and Hibbert, F. and Hillman, A. and Hobbs, W. and Huber, M. and Hughes, A. L. C. and Jaccard, S. and Ruan, J. and Kienast, M. and Konecky, B. and Le Roux, G. and Lyubchich, V and Novello, V. F. and Olaka, L. and Partin, J. W. and Pearce, C. and Phipps, S. J. and Pignol, C. and Piotrowska, N. and Poli, M-S and Prokopenko, A. and Schwanck, F. and Stepanek, C. and Swann, G. E. A. and Telford, R. and Thomas, E. and Thomas, Z. and Truebe, S. and von Gunten, L. and Waite, A. and Weitzel, N. and Wilhelm, B. and Williams, J. and Winstrup, M. and Zhao, N. and Zhou, Y.}, title = {PaCTS 1.0: A Crowdsourced Reporting Standard for Paleoclimate Data}, series = {Paleoceanography and paleoclimatology}, volume = {34}, journal = {Paleoceanography and paleoclimatology}, number = {10}, publisher = {American Geophysical Union}, address = {Washington}, issn = {2572-4517}, doi = {10.1029/2019PA003632}, pages = {1570 -- 1596}, year = {2019}, abstract = {The progress of science is tied to the standardization of measurements, instruments, and data. This is especially true in the Big Data age, where analyzing large data volumes critically hinges on the data being standardized. Accordingly, the lack of community-sanctioned data standards in paleoclimatology has largely precluded the benefits of Big Data advances in the field. Building upon recent efforts to standardize the format and terminology of paleoclimate data, this article describes the Paleoclimate Community reporTing Standard (PaCTS), a crowdsourced reporting standard for such data. PaCTS captures which information should be included when reporting paleoclimate data, with the goal of maximizing the reuse value of paleoclimate data sets, particularly for synthesis work and comparison to climate model simulations. Initiated by the LinkedEarth project, the process to elicit a reporting standard involved an international workshop in 2016, various forms of digital community engagement over the next few years, and grassroots working groups. Participants in this process identified important properties across paleoclimate archives, in addition to the reporting of uncertainties and chronologies; they also identified archive-specific properties and distinguished reporting standards for new versus legacy data sets. This work shows that at least 135 respondents overwhelmingly support a drastic increase in the amount of metadata accompanying paleoclimate data sets. Since such goals are at odds with present practices, we discuss a transparent path toward implementing or revising these recommendations in the near future, using both bottom-up and top-down approaches.}, language = {en} } @article{vanderAaLeopoldWeidlich2020, author = {van der Aa, Han and Leopold, Henrik and Weidlich, Matthias}, title = {Partial order resolution of event logs for process conformance checking}, series = {Decision support systems : DSS}, volume = {136}, journal = {Decision support systems : DSS}, publisher = {Elsevier}, address = {Amsterdam [u.a.]}, issn = {0167-9236}, doi = {10.1016/j.dss.2020.113347}, pages = {12}, year = {2020}, abstract = {While supporting the execution of business processes, information systems record event logs. Conformance checking relies on these logs to analyze whether the recorded behavior of a process conforms to the behavior of a normative specification. A key assumption of existing conformance checking techniques, however, is that all events are associated with timestamps that allow to infer a total order of events per process instance. Unfortunately, this assumption is often violated in practice. Due to synchronization issues, manual event recordings, or data corruption, events are only partially ordered. In this paper, we put forward the problem of partial order resolution of event logs to close this gap. It refers to the construction of a probability distribution over all possible total orders of events of an instance. To cope with the order uncertainty in real-world data, we present several estimators for this task, incorporating different notions of behavioral abstraction. Moreover, to reduce the runtime of conformance checking based on partial order resolution, we introduce an approximation method that comes with a bounded error in terms of accuracy. Our experiments with real-world and synthetic data reveal that our approach improves accuracy over the state-of-the-art considerably.}, language = {en} } @article{DinevaVermaGonzalezManriqueetal.2020, author = {Dineva, Ekaterina Ivanova and Verma, Meetu and Gonzalez Manrique, Sergio Javier and Schwartz, Pavol and Denker, Carsten}, title = {Cloud model inversions of strong chromospheric absorption lines using principal component analysis}, series = {Astronomische Nachrichten = Astronomical notes}, volume = {341}, journal = {Astronomische Nachrichten = Astronomical notes}, number = {1}, publisher = {Wiley-VCH Verl.}, address = {Berlin}, issn = {0004-6337}, doi = {10.1002/asna.202013652}, pages = {64 -- 78}, year = {2020}, abstract = {High-resolution spectroscopy of strong chromospheric absorption lines delivers nowadays several millions of spectra per observing day, when using fast scanning devices to cover large regions on the solar surface. Therefore, fast and robust inversion schemes are needed to explore the large data volume. Cloud model (CM) inversions of the chromospheric H alpha line are commonly employed to investigate various solar features including filaments, prominences, surges, jets, mottles, and (macro-) spicules. The choice of the CM was governed by its intuitive description of complex chromospheric structures as clouds suspended above the solar surface by magnetic fields. This study is based on observations of active region NOAA 11126 in H alpha, which were obtained November 18-23, 2010 with the echelle spectrograph of the vacuum tower telescope at the Observatorio del Teide, Spain. Principal component analysis reduces the dimensionality of spectra and conditions noise-stripped spectra for CM inversions. Modeled H alpha intensity and contrast profiles as well as CM parameters are collected in a database, which facilitates efficient processing of the observed spectra. Physical maps are computed representing the line-core and continuum intensity, absolute contrast, equivalent width, and Doppler velocities, among others. Noise-free spectra expedite the analysis of bisectors. The data processing is evaluated in the context of "big data," in particular with respect to automatic classification of spectra.}, language = {en} } @article{IlinPoppenhaegerAlvaradoGomez2022, author = {Ilin, Ekaterina and Poppenh{\"a}ger, Katja and Alvarado-G{\´o}mez, Juli{\´a}n David}, title = {Localizing flares to understand stellar magnetic fields and space weather in exo-systems}, series = {Astronomische Nachrichten = Astronomical notes}, volume = {343}, journal = {Astronomische Nachrichten = Astronomical notes}, number = {4}, publisher = {Berlin}, address = {Wiley-VCH}, issn = {1521-3994}, doi = {10.1002/asna.20210111}, pages = {7}, year = {2022}, abstract = {Stars are uniform spheres, but only to first order. The way in which stellar rotation and magnetism break this symmetry places important observational constraints on stellar magnetic fields, and factors in the assessment of the impact of stellar activity on exoplanet atmospheres. The spatial distribution of flares on the solar surface is well known to be nonuniform, but elusive on other stars. We briefly review the techniques available to recover the loci of stellar flares, and highlight a new method that enables systematic flare localization directly from optical light curves. We provide an estimate of the number of flares we may be able to localize with the Transiting Exoplanet Survey Satellite, and show that it is consistent with the results obtained from the first full sky scan of the mission. We suggest that nonuniform flare latitude distributions need to be taken into account in accurate assessments of exoplanet habitability.}, language = {en} }