Deeply integrating Linked Data with Geographic Information Systems

The realization that knowledge often forms a densely interconnected graph has fueled the development of graph databases, Web‐scale knowledge graphs and query languages for them, novel visualization and query paradigms, as well as new machine learning methods tailored to graphs as data structures. One such example is the densely connected and global Linked Data cloud that contains billions of statements about numerous domains, including life science and geography. While Linked Data has found its way into everyday applications such as search engines and question answering systems, there is a growing disconnect between the classical ways in which Geographic Information Systems (GIS) are still used today and the open‐ended, exploratory approaches used to retrieve and consume data from knowledge graphs such as Linked Data. In this work, we conceptualize and prototypically implement a Linked Data connector framework as a set of toolboxes for Esri's ArcGIS to close this gap and enable the retrieval, integration, and analysis of Linked Data from within GIS. We discuss how to connect to Linked Data endpoints, how to use ontologies to probe data and derive appropriate GIS representations on the fly, how to make use of reasoning, how to derive data that are ready for spatial analysis out of RDF triples, and, most importantly, how to utilize the link structure of Linked Data to enable analysis. The proposed Linked Data connector framework can also be regarded as the first step toward a guided geographic question answering system over geographic knowledge graphs.     

Computing and querying strict,approximate, and metrically refined topological relations in linked geographic data

Geographic entities and the information associated with them play a major role in Web‐scale knowledge graphs such as Linked Data. Interestingly, almost all major datasets represent places and even entire regions as point coordinates. There are two key reasons for this. First, complex geometries are difficult to store and query using the current Linked Data technology stack to a degree where many queries take minutes to return or will simply time out. Second, the absence of complex geometries confirms a common suspicion among GIScientists, namely that for many everyday queries place‐based relational knowledge is more relevant than raw geometries alone. To give an illustrative example, the statement that the White House is in Washington, DC is more important for gaining an understating of the city than the exact geometries of both entities. This does not imply that complex geometries are unimportant but that (topological) relations should also be extracted from them. As Egenhofer and Mark (1995b) put it in their landmark paper on naive geography, topology matters, metric refines. In this work we demonstrate how to compute and utilize strict, approximate, and metrically refined topological relations between several geographic feature types in DBpedia and compare our results to approaches that compute result sets for topological queries on the fly.     

Traffic transformer: Capturing the continuity and periodicity of time series for traffic forecasting

Traffic forecasting is a challenging problem due to the complexity of jointly modeling spatio‐temporal dependencies at different scales. Recently, several hybrid deep learning models have been developed to capture such dependencies. These approaches typically utilize convolutional neural networks or graph neural networks (GNNs) to model spatial dependency and leverage recurrent neural networks (RNNs) to learn temporal dependency. However, RNNs are only able to capture sequential information in the time series, while being incapable of modeling their periodicity (e.g., weekly patterns). Moreover, RNNs are difficult to parallelize, making training and prediction less efficient. In this work we propose a novel deep learning architecture called Traffic Transformer to capture the continuity and periodicity of time series and to model spatial dependency. Our work takes inspiration from Google’s Transformer framework for machine translation. We conduct extensive experiments on two real‐world traffic data sets, and the results demonstrate that our model outperforms baseline models by a substantial margin.     

Kustaanheimo–Stiefel transformation with an arbitrary defining vector

Kustaanheimo–Stiefel (KS) transformation depends on the choice of some preferred direction in the Cartesian 3D space. This choice, seldom explicitly mentioned, amounts typically to the direction of the first or the third coordinate axis in Celestial Mechanics and atomic physics, respectively. The present work develops a canonical KS transformation with an arbitrary preferred direction, indicated by what we call a defining vector. Using a mix of vector and quaternion algebra, we formulate the transformation in a reference frame independent manner. The link between the oscillator and Keplerian first integrals is given. As an example of the present formulation, the Keplerian motion in a rotating frame is re-investigated.     

SIMS Bias on Isotope Ratios in Ca‐Mg‐Fe Carbonates (Part III): δ18O and δ13C Matrix Effects Along the Magnesite–Siderite Solid‐Solution Series

This study explores the effects of cation composition on mass bias (i.e., the matrix effect), which is a major component of instrumental mass fractionation (IMF) in the microanalyses of δ¹³C and δ¹⁸O by SIMS in carbonates of the magnesite–siderite solid‐solution series (MgCO₃–FeCO₃). A suite of twelve calibration reference materials (RMs) was developed and documented (calibrated range: Fe# = 0.002–0.997, where Fe# = molar Fe/[Mg + Fe]), along with empirical expressions for regressing calibration data (affording residuals < 0.5‰ relative to certified reference material NIST‐19). The calibration curves of both isotope systems are non‐linear and have, over a 2‐year period, fallen into one of two distinct but largely self‐consistent shape categories (data from ten measurement sessions), despite adherence to well‐established analytical protocols for carbonate δ¹³C and δ¹⁸O analyses at WiscSIMS (CAMECA IMS 1280). Mass bias was consistently most sensitive to changes in composition near the magnesite end‐member (Fe# 0–0.2), deviating by up to 4.5‰ (δ¹³C) and 14‰ (δ¹⁸O) with increasing Fe content. The cause of variability in calibration curve shapes is not well understood at present and demonstrates the importance of having available a sufficient number of well‐characterised RMs so that potential complexities of curvature can be adequately delineated and accounted for on a session‐by‐session basis.     

Earliest mordellid-like beetles from the Jurassic of Kazakhstan and China (Coleoptera: Tenebrionoidea)

Within this study the subfamily Praemordellinae is reviewed and the holotype of Praemordella martynovi Scegoleva-Barovskaja, 1929 is re-described. The genera Cretanaspis Huang and Yang, 1999, Mirimordella Liu et al., 2007, Bellimordella Liu et al., 2008 and Wuhua Wang and Zhang, 2011 is attributed to Praemordellinae. One new species, Wuhua peregrina sp. nov., is erected based on two well-preserved specimens from the Middle Jurassic Daohugou Biota (Inner Mongolia, China). The morphological characters of Praemordellinae are given and a key to genera of Praemordellinae is presented. Praemordellinae is closely related to extant Mordellidae in having humpbacked body, strongly deflexed head, filiform antennae and pectinate tarsal claws, but it is differing in that the pygidium absent and hind femora not well developed. It is also similar to Ripiphoridae in having a convex body and simple tarsi, but differs Ripiphoridae in having filiform antennae. Praemordellinae is probably a stem group including the ancestor of Mordellidae and Ripiphoridae. Also, within this paper, the fossil record of Mordellidae is summarized.     

Origin and evolution of volatiles in the Central Europe late Variscan granitoids,using the example of the Strzegom-Sobótka Massif,SW Poland

Mineralogy and Petrology - The results of the new Electron Microprobe Analysis of apatite, hornblende and biotite crystals of the hornblende-biotite variety of the Strzegom-Sobótka granite...     

Georadar studies on St. Benedict’s Church on Lasota Hill,Kraków,Poland

Georadar methodology has a considerable potential as a tool for verification of archeological hypotheses. I applied it in the present study to resolve a discussion on the importance of a Proto-Romanesque structure located on Lasota Hill. It is one of the oldest structures on the right bank of Vistula River in Kraków in Poland and some archeologists believe that it was the first seat of the rulers of Lesser Poland in the 9th century. After few decades, the prince’s castle was built on Wawel Hill, where subsequently the royal castle was constructed. On the place of the abandoned Proto-Romanesque edifice, a small St. Benedict’s Church was raised, but the importance of its predecessor was discussed. Archeological excavations suggested that it served as the prince’s residence, but this view would be much strengthened if traces of a prince’s building — palatium — could be found. With this in mind, I undertook a search for traces of palatium, employing georadar methodology. I carried out the measurements using Georadar PROEX produced by MALA Geoscience with a set of shielded antennas of frequencies 500 and 800 MHz. They permitted to construct echogram profiles, whose interpretation suggested the existence of palatium. Thus, the georadar data supported the archeological hypothesis about the important role of the Proto-Romanesque structures on Lasota Hill in the early medieval era in Poland, and at the same time demonstrated the usefulness of introducing geophysical methods to archaeology.     

Influence of a method of evaluation of the curvature of flexible vegetation elements on vertical distributions of flow velocities

Methods of computing the deflections of flexible vegetation elements under the dynamic pressure of water were presented in the paper. Two methods, based on Euler-Bernoulli beam theory, were discussed, one designed for small deflections and the other, generalized one, also for larger deflections. The choice of the method for computations of deflections was discussed from the perspective of the computation of flow velocities above flexible vegetation. Computational results were compared with laboratory experiments and it was found that the simplified, computationally less expensive method may be used in many practical situations without deterioration of the results.