Article
Computer Science, Information Systems
Petar Milic, Natasa Veljkovic, Leonid Stoimenov
Summary: Metadata plays a crucial role in e-government open data platforms, providing a structured environment for data consumption and enabling unique interpretations of data. Research indicates that more attention should be paid to metadata to uncover relationships between datasets.
IEEE TRANSACTIONS ON EMERGING TOPICS IN COMPUTING
(2021)
Article
Computer Science, Interdisciplinary Applications
O. Mryglod, S. Nazarovets, S. Kozmenko
Summary: This study provides a multidimensional and longitudinal disciplinary analysis of Ukrainian economic research at the national level based on Crossref data. It explores general tendencies and characteristics of Ukrainian economic research output, highlighting the importance of enriching open scholarly metadata. The study found a tendency towards more collaborative output in Ukrainian economic research and discusses the specific and universal features of the field.
Article
Chemistry, Multidisciplinary
Ingrid Hasenkopf, Robert Mills-Goodlet, Litty Johnson, Ian Rouse, Mark Geppert, Albert Duschl, Dieter Maier, Vladimir Lobaskin, Iseult Lynch, Martin Himly
Summary: Extensive investigation and characterisation of nanoparticle-protein conjugates are important for assessing potential hazards and predicting biological effects. The development of in silico modelling tools can provide alternative approaches and accelerate risk assessment. This study validates emerging in silico protein corona models and provides recommendations for improvement.
Article
Computer Science, Artificial Intelligence
Bernardo Breve, Loredana Caruccio, Stefano Cirillo, Vincenzo Deufemia, Giuseppe Polese
Summary: This paper introduces a tool for visualizing RFDS discovered from a data stream, which allows exploration of results for different types of RFDS and uses quantitative measures to monitor the evolution of discovery results. The tool enables comparison of RFDS discovered across multiple executions and provides visual manipulation operators for dynamically composing and filtering results.
Article
Construction & Building Technology
David Waterworth, Subbu Sethuvenkatraman, Quan Z. Sheng
Summary: The introduction of smart building technology brings benefits and enables smart grid integration. However, mapping the building sensor metadata to the requirements of smart building applications is a significant barrier. This paper studies weakly supervised machine learning as a promising approach to accelerate the metadata mapping process. A pattern-based workflow is developed, validated using three commercial office buildings, and shown to reduce annotation time by a factor of 4 compared to manual methods.
ENERGY AND BUILDINGS
(2023)
Article
Environmental Sciences
Ming Chen, Tongsheng Yao, Ke Wang
Summary: This study characterizes the literature on the economic impact of climate change using bibliometric methods. The findings show that the USA is the most productive country, while China has become the second most productive country in recent years. Adaptation, vulnerability, uncertainty, economic growth, climate policy, ecosystem service, energy consumption, renewable energy, food security, and land use are the representative keywords. The research hotspots include potential benefits, fat-tailed risk, social cost, international migration, and sustainable intensification. The research trends focus on methodological innovation, the effect of adaptive measures on agriculture, the interaction between technological change and carbon tax, and the effect on the labor market caused by climate change.
ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH
(2023)
Article
Multidisciplinary Sciences
Rachel H. Toczydlowski, Libby Liggins, Michelle R. Gaither, Tanner J. Anderson, Randi L. Barton, Justin T. Berg, Sofia G. Beskid, Beth Davis, Alonso Delgado, Emily Farrell, Maryam Ghoojaei, Nan Himmelsbach, Ann E. Holmes, Samantha R. Queeno, Thienthanh Trinh, Courtney A. Weyand, Gideon S. Bradburd, Cynthia Riginos, Robert J. Toonen, Eric D. Crandall
Summary: Genomic data are being generated and archived rapidly, but a lack of spatiotemporal metadata poses challenges for genetic diversity monitoring. Only a small fraction of genomic datasets contain geographic coordinates and collection years, highlighting the need for streamlined data processes and updated policies to address the growing metadata gap.
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
(2021)
Article
Engineering, Industrial
Fuqiang Yang, Yujie Huang, Jing Tao, Genserik Reniers, Chao Chen
Summary: This paper conducts a bibliometric data mining to systematically review the research domain of safety climate (SC), analyzing the development trend, authors, journals, countries, and institutions related to SC. Network analysis and text mining are used to understand the relationship among different countries/regions, authors, and keywords, and identify the main topics and hotspots in SC research. The limitations of past research on SC and the differences between SC and safety culture are analyzed, and recommendations for future research on SC are given.
Article
Green & Sustainable Science & Technology
H. Gardian, J. -p. Beck, M. Koch, R. Kunze, C. Muschner, L. Huelk, M. Bucksteeg
Summary: A variety of models have emerged in the field of energy system analysis to address sustainability in the energy sector. Model experiments are important for decision-makers to understand the range of models available and make meaningful choices. Harmonising data is crucial for comparing and selecting models, ensuring high comparability.
RENEWABLE & SUSTAINABLE ENERGY REVIEWS
(2022)
Article
Agronomy
Boon Teck Tan, Pei Shan Fam, R. B. Radin Firdaus, Mou Leong Tan, Mahinda Senevi Gunaratne
Summary: Climate change affects rice yields in Malaysia, with higher temperatures impacting the off-season and lower temperatures positively affecting both cropping seasons. Future projections show varying effects on rice yield, highlighting the importance of adaptation at the farm level to address potential negative impacts.
Article
Environmental Sciences
Martin Bachmann, Kevin Alonso, Emiliano Carmona, Birgit Gerasch, Martin Habermeyer, Stefanie Holzwarth, Harald Krawczyk, Maximilian Langheinrich, David Marshall, Miguel Pato, Nicole Pinnel, Raquel de losReyes, Mathias Schneider, Peter Schwind, Tobias Storch
Summary: Ground segments of Landsat and Sentinel missions provide well-calibrated datasets which are orthorectified and corrected for atmospheric effects. Initiatives like CEOS ARD propose guidelines for easily using such datasets and ensuring interoperability. The increasing availability of hyperspectral sensor data from EnMAP, DESIS, PRISMA, and upcoming missions like CHIME and SBG make analysis ready hyperspectral data more valuable.
Article
Engineering, Electrical & Electronic
Sung Joon Maeng, Ozgur Ozdemir, Ismail Guvenc, Mihail L. Sichitiu, Magreth Mushi, Rudra Dutta
Summary: This article highlights the importance of using cellular networks for remote control and communication of UAVs, and the potential applications of machine learning techniques in improving UAV communication and navigation. It presents raw data sets obtained from field experiments and provides examples of potential uses for other researchers.
IEEE COMMUNICATIONS MAGAZINE
(2023)
Article
Biochemical Research Methods
Tao Sun, Mengci Li, Xiangtian Yu, Dandan Liang, Guoxiang Xie, Chao Sang, Wei Jia, Tianlu Chen
Summary: In this study, we designed and developed a comprehensive platform, 3MCor, for the correlation analysis of metabolome and microbiome. The platform integrates multiple correlation analysis methods and provides three different pipelines for inter-correlation analysis. The network analysis function facilitates the rapid identification of clusters and key nodes in complex correlation networks. The platform is easy to use and provides numerical results and figures as outputs.
Article
Biochemical Research Methods
Rick Gelhausen, Sarah L. Svensson, Kathrin Froschauer, Florian Heyl, Lydia Hadjeras, Cynthia M. Sharma, Florian Eggenhofer, Rolf Backofen
Summary: HRIBO is a workflow designed for reproducible and high-throughput analysis of bacterial Ribo-seq data, facilitating the rapid and high-confidence discovery of novel ORFs and their prioritization for functional characterization.
Article
Meteorology & Atmospheric Sciences
Filippo Giorgi, Erika Coppola, Daniela Jacob, Claas Teichmann, Sabina Abba Omar, Moetasim Ashfaq, Nikolina Ban, Katharina Buelow, Melissa Bukovsky, Lars Buntemeyer, Tereza Cavazos, James Ciarlo, Rosmeri Porfirio da Rocha, Sushant Das, Fabio di Sante, Jason P. Evans, Xuejie Gao, Graziano Giuliani, Russell H. Glazer, Peter Hoffmann, Eun-Soon Im, Gaby Langendijk, Ludwig Lierhammer, Marta Llopart, Sebastial Mueller, Rosa Luna-Nino, Rita Nogherotto, Emanuela Pichelli, Francesca Raffaele, Michelle Reboita, Diana Rechid, Armelle Remedio, Thomas Remke, Windmanagda Sawadogo, Kevin Sieck, Jose Abraham Torres-Alavez, Torsten Weber
Summary: This article describes the first effort of the Coordinated Regional Climate Downscaling Experiment (CORDEX)-CORE EXP-I, which involves using regional climate models (RCMs) to downscale global climate model (GCM) simulations from the CMIP5 program. The results cover a wide range of topics, including extreme indices, storms, monsoons, and more. The CORDEX-CORE EXP-I ensemble provides unprecedented downscaled information to improve understanding of regional climate change and impacts.
BULLETIN OF THE AMERICAN METEOROLOGICAL SOCIETY
(2022)
Article
Computer Science, Software Engineering
Marius Hografer, Magnus Heitzler, Hans-Jorg Schulz
COMPUTER GRAPHICS FORUM
(2020)
Article
Engineering, Civil
Juan Lam, Juergen Hackl, Magnus Heitzler, Bryan T. Adey, Lorenz Hurni
JOURNAL OF INFRASTRUCTURE SYSTEMS
(2020)
Review
Geography
Chenjing Jiao, Magnus Heitzler, Lorenz Hurni
Summary: This article provides a comprehensive overview of methods for extracting road features from raster maps, categorizing them based on techniques, user intervention, data requirements, and produced results. It also reviews recent road extraction methods from overhead imagery and evaluation methods that may benefit road extraction from raster maps. The evolution of this research field over the past 35 years is analyzed, and the limitations of current techniques, as well as possible future directions, are discussed.
TRANSACTIONS IN GIS
(2021)
Article
Geography, Physical
Sidi Wu, Magnus Heitzler, Lorenz Hurni
Summary: This study utilizes Bayesian deep learning for uncertainty estimation in historical maps to improve the semantic segmentation of hydrological features. By integrating multi-scale contextual information, the algorithm achieves significant performance improvement and outputs interpretable uncertainty maps, which can be used for refining segmentation results and selecting reliable features in future GIS analyses.
GISCIENCE & REMOTE SENSING
(2022)
Article
Computer Science, Artificial Intelligence
Marius Hografer, Marco Angelini, Giuseppe Santucci, Hans-Jorg Schulz
Summary: Progressive visual analytics allows users to interact with early, partial results of long-running computations on large datasets. We present a novel interactive steering approach called steering-by-example, which prioritizes data subspaces for progression without additional index structures.
ACM TRANSACTIONS ON INTELLIGENT SYSTEMS AND TECHNOLOGY
(2022)
Article
Computer Science, Information Systems
Marianna Farmakis-Serebryakova, Magnus Heitzler, Lorenz Hurni
Summary: In this study, a U-Net model was adapted to recognize and segment different landforms on the terrain. The algorithm performed well for block mountains, Prealps, valleys, and hills, but faced challenges in segmenting plateaus and folded mountains. Mountains formed by erosion processes were the least recognized landform. The overall accuracy of the model was relatively high.
ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION
(2022)
Article
Computer Science, Software Engineering
Wenkai Han, Hans-Jorg Schulz
Summary: This study proposes a generic method for guiding visual analytics by framing the problem as a decision problem and applying decision making theory and models. The method involves three stages: identifying decision points, deriving and evaluating alternatives, and visualizing the resulting alternatives for user comparison and choice. The method is illustrated using a use case of providing guidance among different clustering methods. Finally, the method is compared to existing guidance frameworks to understand their respective goals and contributions.
INFORMATION VISUALIZATION
(2023)
Review
Food Science & Technology
Soren Drud-Heydary Nielsen, Ningjian Liang, Harith Rathish, Bum Jin Kim, Jiraporn Lueangsakulthai, Jeewon Koh, Yunyao Qu, Hans-Jorg Schulz, David C. Dallas
Summary: Partial digestion of milk proteins produces various bioactive peptides. Our research team constructed the milk bioactive peptide database (MBPDB) by thoroughly reviewing existing literature on milk bioactive peptides across species. This article provides a comprehensive update to the data in the MBPDB, and reviews the current state of research for each functional category, including ACE-inhibitory, antimicrobial, antioxidant, DPP-IV inhibitory, opioid, anti-inflammatory, immunomodulatory, calcium absorption and bone health, and anticancer activity. This information will contribute to future research on the bioactivities of milk peptides.
CRITICAL REVIEWS IN FOOD SCIENCE AND NUTRITION
(2023)
Article
Computer Science, Information Systems
Raimund Schnuerer, A. Cengiz Oztireli, Magnus Heitzler, Rene Sieber, Lorenz Hurni
Summary: This study explores the application of CNN techniques to artificially created images, successfully identifying human figures using Mask R-CNN and UNet++. The results show potential for use in animation and historical map analysis.
INTERNATIONAL JOURNAL OF CARTOGRAPHY
(2022)
Proceedings Paper
Computer Science, Artificial Intelligence
Steffen Strunge Mathiesen, Hans-Jorg Schulz
Summary: This paper introduces a novel approach to improving the layout of stacked area charts by reordering the time series in the stack and using a new algorithm to optimize the aesthetic properties. The algorithm can increase layout quality by 25%-50% over the state-of-the-art approach but at the expense of longer runtimes.
DIAGRAMMATIC REPRESENTATION AND INFERENCE, DIAGRAMS 2021
(2021)
Proceedings Paper
Computer Science, Artificial Intelligence
Lars Nonnemann, Heidrun Schumann, Bodo Urban, Mario Aehnelt, Hans-Jorg Schulz
2020 24TH INTERNATIONAL CONFERENCE INFORMATION VISUALISATION (IV 2020)
(2020)
Proceedings Paper
Computer Science, Artificial Intelligence
Wenkai Han, Hans-Jorg Schulz
2020 IEEE WORKSHOP ON TRUST AND EXPERTISE IN VISUAL ANALYTICS (TREX 2020)
(2020)
Proceedings Paper
Computer Science, Artificial Intelligence
Hans-Joerg Schulz, Martin Roehlig, Lars Nonnemann, Marius Hograefer, Mario Aehnelt, Bodo Urban, Heidrun Schumann
COMPUTER VISION, IMAGING AND COMPUTER GRAPHICS THEORY AND APPLICATIONS (VISIGRAPP 2019)
(2020)
Article
Engineering, Civil
Juan Carlos Lam, Magnus Heitzler, Juergen Hackl, Bryan T. Adey, Lorenz Hurni
SUSTAINABLE AND RESILIENT INFRASTRUCTURE
(2020)