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Naked data: curating Wikidata as an artistic medium to interpret prehistoric figurines

INTERNATIONAL JOURNAL OF PERFORMANCE ARTS AND DIGITAL MEDIA 2023年第3期19卷 445-462页

作者： Sant, Toni Tabone, Enrique Univ Salford Sch Arts Media & Creat Technol Salford England Univ Salford Digital Curat Salford England Univ Salford Salford England

In 2019, Digital Curation Lab Director Toni Sant and the artist Enrique Tabone started collaborating on a research project exploring the visualization of specific data sets through Wikidata for artistic practice. An art installation called Naked data was developed from this collaboration and exhibited at the Stanley Picker Gallery in Kingson, London, during the DRHA 2022 conference. Through data analysis, employing Wikidata tools, this creative work employs a data set depicting prehistoric female figurines held by Heritage Malta. The artistic research aims to develop a creative workflow model for processing essential information about art collections, museum policies, and ways to engage with cultural heritage through data. This article outlines the key elements involved in this practice-based research work and shares the artistic process involving the visualizing of the scientific data with special attention to the aesthetic qualities afforded by this technological engagement.

关键词： data visualization data art data feminism Wikidata Prehistoric figurines Digital curation

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Programming Representations: Uncovering the Process of Constructing data visualizations in a Block-based Programming Environment 23

Programming Representations: Uncovering the Process of Const...

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2023 Symposium on Learning, Design and Technology, LDT 2023

作者： Fernandez, Cassia De Deus Lopes, Roseli Blikstein, Paulo Brazil Teachers College Columbia University United States

ISBN: (纸本)9798400707360

In this paper, we analyze how middle schoolers engaged in data visualization activities using Playdata, an educational tool designed to create representations for data by taking advantage of the flexibility and low entry point of block-based programming environments. Drawing on the analysis of artifacts and videos collected during a three-day workshop, we explore the types of visualizations created by participants and the process they engaged with to produce visualizations. Although the representational forms chosen by students were mainly traditional, our findings indicate that they were engaged in authentic data visualization practices throughout their programming process. These practices included translating ideas into programs, selecting parameters (such as color scheme and space between data points), inspecting the output, and adding annotations to provide context and better communicate the desired information. Moreover, our analysis pointed out opportunities for improving Playdata, mainly by the addition of new primitives for automating labeling and performing data transformations. © 2023 Copyright held by the owner/author(s). Publication rights licensed to ACM.

关键词： data visualization

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Exploiting Sentinel-5P for Spatio-Temporal analysis of SO2 Volcanic Ash Activity in 2019-2022 at Indonesia Using Earth Engine Platform

Exploiting Sentinel-5P for Spatio-Temporal Analysis of SO2 V...

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IEEE International conference on Aerospace Electronics and Remote Sensing Technology (ICARES)

作者： Sukojo, Bangun Muljo Fadhilah, Nur Aini Qolbi Sanjaya, Hartanto Inst Teknol Sepuluh Nopember Geomat Engn Surabaya Indonesia Natl Res & Innovat Agcy Tangerang Selatan Indonesia

ISBN: (纸本)9798350344004

Based on data from website MAGMA PVMBG, the Geological Agency of the Ministry of Energy and Mineral Resources, from 2019 until 2022, about 10 volcanoes in Indonesia have erupted, some more than twice. In addition, there are 10% of Indonesian people who live around disaster-prone areas, so they have great potential to be exposed SO2 (Sulfur Dioxide) pollutants due to volcanic ash. Therefore, a spatiotemporal analysis was carried out on SO2 concentrations due to volcanic eruptions in Indonesia for the 2019-2022 period using Sentinel-5P imagery data with a cloud-based application, Google Earth Engine. The analysis was carried out during pre-eruption, eruption, and post-eruption to find out the differences and distribution of concentrations. The processed data and other supporting information will be presented in the form of visualization maps, diagrams, tables, and Google Earth Engine Apps. The research method is carried out by classification and sampling with the object of research focused on 5 volcanoes spread across the national scope, namely Mount Agung, Mount Semeru, Mount Ibu, Mount Anak Krakatau, and Mount Sinabung. The image used is Sentinel-5P with the advantage of temporal resolution, which can acquire daily data. The concentration values of SO2 in volcanic eruption areas ranged from -0.0009 to 0.002 mol/m2 with varying value in each affected area. Correlation tests for the processed results showed that BMKG (The Meteorology, Climatology, and Geophysics Agency) parameters (wind speed, temperature, humidity, and rainfall) influence the distribution of SO2 in the five studied volcano areas.

关键词： volcanic eruption SO2 concentration Sentinel-5P Google Earth Engine correlation test

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DeFraudify4ALL: Prototyping and Validation of a System for Fraud Detection with Big data and Cloud Technology 30

DeFraudify4ALL: Prototyping and Validation of a System for F...

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30th IEEE International Symposium for Design and Technology in Electronic Packaging, SIITME 2024

作者： Popovici, Eduard-Cristian Stalidi, Cosmina Teodoras, Dan-Alexandru Suciu, George Cosma, Ioan POLITEHNICA University of Bucharest ETTI Faculty Telecommunication Department Bucharest Romania Beia Consult International R and D Department Bucharest Romania

ISBN: (纸本)9798331539511

This paper presents the prototyping and validation of a Financial data Management and analysis System designed to enhance fraud detection using advanced Big data and Cloud technologies. The system incorporates a Java-based worker for data retrieval and analysis from various sources, including external APIs. The processed data is efficiently stored in a data Lake utilizing Dremio, Apache Arrow, and Apache Parquet technologies. By leveraging cloud platforms such as AWS, the system ensures scalability, security, and flexibility. Additionally, the integration of sophisticated data visualization tools and AI algorithms, particularly Random Forest, enhances the system's ability to detect fraudulent activities. © 2024 IEEE.

关键词： Cloud platforms

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GIS-Based visualization of Lightning Activities in Peninsular Malaysia and Its Correlation With Monsoon Seasons 37

GIS-Based Visualization of Lightning Activities in Peninsula...

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37th International conference on Lightning Protection, ICLP 2024

作者： Ahmad, Nur Azliza Kadir, Mohd Zainal Abidin Ab Ya, Nik Norasma Che Amirulddin, Ungku Anisa Ungku Roslan, Nurzanariah Malaysia Malaysia Malaysia Malaysia

ISBN: (纸本)9783800764174

The paper presents a method for visualizing lightning occurrence maps using three years of data in Peninsular Malaysia from 2017 to 2019. The lightning occurrence maps were made to understand lightning distribution patterns and determine the high-activity regions. This was accomplished using advanced Geographic Information System (GIS) software combined with an in-depth base map of Peninsular Malaysia with lightning stroke data from Vaisala GLD360. This study has shown the extent to which the lightning occurrence mapping technique works for classifying lightning distribution and determining hotspot locations during monsoon season. The largest total distribution of lightning strikes occurred in May, with 5,157,797 counts (16.5%). The Inter-Monsoon season has the highest average of lightning strokes, occurring in April, May, October, and November with 51.85% within three years. The longest lightning stroke duration occurs between 8 AM and 9 AM with the total amount of average are 293,113 (33.9%). The lightning strokes were evenly scattered throughout the visualization analysis to correspond with the monsoon season's variations these results are important for utility and protection engineers because they may significantly improve the reliability of electrical networks by reducing power outages caused by lightning strokes. © 2024 IEEE, © VDE VERLAG GMBH ∙ Berlin ∙ Offenbach.

关键词： visualization

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Research on the Construction of Library Digital Resources Based on Computer Big data Technology

Research on the Construction of Library Digital Resources Ba...

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IEEE International conference on Electrical Engineering, Big data and Algorithms (EEBDA)

作者： Sha, Zhengyu Wuhan Univ Technol Lib Wuhan Univ Technol Wuhan Peoples R China

ISBN: (纸本)9781665416061

Featured resources are a valuable asset of a library, and are the embodiment of its distinctiveness and individualization. These resources depend on the existence of a variety of different media. As an effective method of resource display and disclosure, visualization technology can make it easier for users to understand and use the various media characteristic resources of the library. This article comprehensively uses social network visualization and knowledge measurement methods to construct a visualization model for the knowledge aggregation of digital library resources from knowledge unit mining, knowledge domain development, knowledge network construction, knowledge graph presentation and knowledge visualization applications, with a view to building a digital library The fine-grained aggregate object mining of resources, the disclosure of multidimensional knowledge structure, the visual display of static and dynamic interactive knowledge, and the application of precise knowledge analysis provide reference for reference.

关键词： computer big data library digital resource construction text segmentation

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scikit-fda: Computational Tools for Machine Learning with Functional data 34

scikit-fda: Computational Tools for Machine Learning with Fu...

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34th IEEE International conference on Tools with Artificial Intelligence (ICTAI)

作者： Ramos-Carreno, Carlos Luis Torrecilla, Jose Hong, Yujian Suarez, Alberto Univ Autonoma Madrid Dept Comp Sci Madrid Spain Univ Autonoma Madrid Dept Math Madrid Spain

ISBN: (纸本)9798350397444

Machine learning from functional data poses particular challenges that require specific computational tools that take into account their structure. In this work, we present scikitfda, a Python library for functional data analysis, visualization, preprocessing, and machine learning. The library is designed for smooth integration in the Python scientific ecosystem. In particular, it complements and can be used in combination with scikitlearn, the reference Python library for machine learning. The functionality of scikit-fda is illustrated in clustering, regression, and classification problems from different areas of application.

关键词： functional data analysis data visualization machine learning Python toolbox

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Pre-processing SARS-CoV-2 Sequence data for Application of Machine Learning Techniques for visualization and Clustering of Virus Characteristics

Pre-processing SARS-CoV-2 Sequence Data for Application of M...

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14th Annual Summit and conference of the Asia-Pacific-Signal-and-Information-Processing-Association (APSIPA ASC)

作者： Kim, Juhyeon Ahn, Insung Korea Inst Sci & Technol Informat Daejeon South Korea

ISBN: (数字)9786165904773

ISBN: (纸本)9786165904773

SARS-CoV-2, first known as unknown pneumonia on December 31, 2019, has been around the world for more than two years. As the virus has spread for a long time, various types of mutant viruses have occurred, and the sequence data of the virus has been accumulated considerably. Therefore, studies are being conducted on the types of mutations that are divided by analyzing sequence data and what features are found in which variants. Traditionally, this kinds of sequence analysis has been dominated by analysis and visualization using phylogenetic trees. analysis with these phylogenetic trees can be useful if there is not much data. However, analysis and visualization are not easy when there are hundreds of thousands or millions of data. Thus, in this study, we propose a method to pre-process virus sequence data so that several machine learning techniques can be applied to better analyze and visualize data. In this study, SARS-CoV-2 sequence data is pre-processed by suggesting method and machine learning models such as Auto Encoder and DBSCAN are applied to extract important features and clustering the data. According to the experimental results, important features were extracted by reducing the dimension of the data, and it was confirmed that a numerous amount of viruses were well visualized on 3-dimensional graphs depending on the characteristics of the data, and that they were well clustered according to the virus variation.

关键词： South America Computer viruses Urban areas Asia data visualization Machine learning Feature extraction

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AWS solutions for new energy wind solar farm management 3

AWS solutions for new energy wind solar farm management

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3rd EAGE Digitalization conference and Exhibition 2023

作者： Ma, N. AWS United States

ISBN: (纸本)9789462824720

Amazon is committed to building a sustainable business for our customers and the planet. In September 2019, Amazon co-funded The Climate Pledge – a commitment to be net zero carbon across our business by 2040, 10 years ahead of the Paris Agreement. As part of this pledge, Amazon has made ambitious commitments toward reaching this goal. Amazon is the world’s largest corporate purchaser of renewable energy and is on a path to powering operations with 100% renewable energy by 2025. Amazon Web Services (AWS) is known as a cloud innovator. The AWS energy transition wind solar farm data management and operational dashboard allows for the efficient and effective management of data and operations for wind and solar farms by adopting AWS cloud native services. The dashboard allows users to monitor and track energy production, manage maintenance and repairs, and optimize performance through data analysis and visualization. AWS is sharing solutions developed internally and is enabling our customers and partners to build solutions on top of what we believe are the broadest and deepest set of cloud services available to accelerate customer’s energy transition. © 2023 3rd EAGE Digitalization conference and Exhibition. All Rights Reserved.

关键词： data visualization

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visualization of the dynamic changes of Zhaling Lake in the past 45 Years

Visualization of the dynamic changes of Zhaling Lake in the ...

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2022 International conference on Artificial Intelligence, Virtual Reality, and visualization, AIVRV 2022

作者： Li, Lujia Geng, Shengling Zhou, Mingquan Song, Suxin College of Computer Qinghai Normal University Xining810008 China Academy of Plateau Science and Sustainability Xining810008 China

ISBN: (纸本)9781510662988

Zhaling Lake is the first lake at the source of the Yellow River. The morphology of Zhaling Lake has changed frequently in recent decades. We conducted a visual analysis of Landsat remote sensing images and weather station observations in Maduo County from 1976-2021. We derived the space-time evolution of Zhaling Lake shoreline and area change trends. This paper obtained the basic characteristics such as the area and shoreline of Zhaling Lake by using water index and visual interpretation. Based on these basic characteristics, we calculated other shoreline characteristics. We analyze the morphological, meteorological, and other data characteristics of Zhaling Lake by visualization method. Research results show that the area of Zhaling Lake is highly variable. Its overall change shows a cyclic trend of recession-expansionrecession. A significant shrinkage of Zhaling Lake occurred from 1976 to 1986, from 544.177 km2 to 537.32 km2. Between 1986 and 1993, Zhaling Lake gradually expanded, adding 9.541 km2. During 1993-2019, the area of Zhaling Lake showed a continuous trend of increase. In 2019, Zhaling Lake reached the largest area of 555.368 km2 in nearly 45 years. During 2019-2021, Zhaling Lake begins to shrink slightly again. In 2021, Zhaling Lake's area shrinks to 549.41km2. © 2023 SPIE. All rights reserved.

关键词： Landsat

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