Combining Data Sources to Understand the Fine- Scale Distribution and Encounter Rates of Common Dolphins Delphius delphis in one of the busiest waterways in the world, the Istanbul Strait

Data collection and machine learning are changing the world. Whether it is medicine, sports or education, companies and institutions are investing a lot of time and money in systems that gather, process and analyse data. Likewise, to improve competitiveness, a lot of countries are making changes to their educational policy by supporting STEM disciplines. Therefore, it’s important to put effort into using various data sources to help students succeed in STEM. In this paper, we present a platform that can analyse student’s activity on various contest and e-learning systems, combine and process the data, and then present it in various ways that are easy to understand. This in turn enables teachers and organizers to recognize talented and hardworking students, identify issues, and/or motivate students to practice and work on areas where they’re weaker.

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Groundwater storage in Africa

10.29104/wins.l.0171.2018 ◽

2017 ◽

Author(s):

Gabin Archambault

Keyword(s):

High Resolution ◽

Effective Porosity ◽

Data Sources ◽

Groundwater Storage ◽

British Geological Survey ◽

Full List ◽

The World ◽

Storage Type ◽

Porosity Range ◽

Aquifer Flow

This 5 km resolution grid presents groundwater storage in Africa (in mm). This parameter was estimated by combining the saturated aquifer thickness and effective porosity of aquifers across Africa. For each aquifer flow/storage type an effective porosity range was assigned based on a series of studies across Africa and surrogates in other parts of the world. Groundwater storage is given in millimeters. Detailed description of the methodology, and a full list of data sources used to develop the layer can be found in the peer-reviewed paper available here: http://iopscience.iop.org/article/10.1088/1748-9326/7/2/024009/pdf The raster and a high resolution PDF file are available for download on the website of British Geological Survey (BGS): http://www.bgs.ac.uk/research/groundwater/international/africanGroundwater/mapsDownload.html Groundwater Storage

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Collaboration platforms in water management

Water Practice & Technology ◽

10.2166/wpt.2011.062 ◽

2011 ◽

Vol 6 (3) ◽

Author(s):

C. E. Hidaka ◽

H. R. Kolar ◽

R. P. Williams ◽

P. G. Hartswick ◽

S. B. Foong

Keyword(s):

Water Management ◽

Information Technology ◽

Water Resources ◽

Data Sources ◽

Effective Management ◽

Holistic View ◽

The World ◽

Technical Architecture ◽

Multiple Levels ◽

Collaboration Platforms

In many parts of the world, management of water resources and infrastructures is fragmented between agencies at multiple levels – state, provincial, and local – and sometimes between functions within individual agencies. Consequently it is often impossible to take a holistic view of the issues at hand to enable effective management of the resource or infrastructure – either because of the overhead of managing the coordination required, and/or because of politics between the different stakeholders. In their work for IBM, the authors created a concept of an information technology (IT)-enabled “collaboration platform” that integrates different water data sources with IT tools to enable multiple entities to maintain and share a “common operating picture.” This greatly assists with coordination and reduces politics to manageable levels. In this paper, the authors describe the collaboration platform and its benefits by reference to examples of such platforms in use, and propose a reference technical architecture for creating collaboration platforms.

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A Large-Scale COVID-19 Twitter Chatter Dataset for Open Scientific Research—An International Collaboration

Epidemiologia ◽

10.3390/epidemiologia2030024 ◽

2021 ◽

Vol 2 (3) ◽

pp. 315-324

Author(s):

Juan M. Banda ◽

Ramya Tekumalla ◽

Guanyu Wang ◽

Jingyuan Yu ◽

Tuo Liu ◽

...

Keyword(s):

Large Scale ◽

Social Dynamics ◽

Additional Data ◽

Open Data ◽

Data Sources ◽

Research Projects ◽

Research Groups ◽

The World ◽

Data Source

As the COVID-19 pandemic continues to spread worldwide, an unprecedented amount of open data is being generated for medical, genetics, and epidemiological research. The unparalleled rate at which many research groups around the world are releasing data and publications on the ongoing pandemic is allowing other scientists to learn from local experiences and data generated on the front lines of the COVID-19 pandemic. However, there is a need to integrate additional data sources that map and measure the role of social dynamics of such a unique worldwide event in biomedical, biological, and epidemiological analyses. For this purpose, we present a large-scale curated dataset of over 1.12 billion tweets, growing daily, related to COVID-19 chatter generated from 1 January 2020 to 27 June 2021 at the time of writing. This data source provides a freely available additional data source for researchers worldwide to conduct a wide and diverse number of research projects, such as epidemiological analyses, emotional and mental responses to social distancing measures, the identification of sources of misinformation, stratified measurement of sentiment towards the pandemic in near real time, among many others.

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Comparative Analysis of Geolocation Information through Mobile-Devices under Different COVID-19 Mobility Restriction Patterns in Spain

ISPRS International Journal of Geo-Information ◽

10.3390/ijgi10020073 ◽

2021 ◽

Vol 10 (2) ◽

pp. 73

Author(s):

Raquel Pérez-Arnal ◽

David Conesa ◽

Sergio Alvarez-Napagao ◽

Toyotaro Suzumura ◽

Martí Català ◽

...

Keyword(s):

Mobile Phones ◽

Human Mobility ◽

The Other ◽

Data Sources ◽

Experimental Setting ◽

Mobile Data ◽

Restriction Patterns ◽

Mobility Data ◽

The World ◽

Proper Interpretation

The COVID-19 pandemic is changing the world in unprecedented and unpredictable ways. Human mobility, being the greatest facilitator for the spread of the virus, is at the epicenter of this change. In order to study mobility under COVID-19, to evaluate the efficiency of mobility restriction policies, and to facilitate a better response to future crisis, we need to understand all possible mobility data sources at our disposal. Our work studies private mobility sources, gathered from mobile-phones and released by large technological companies. These data are of special interest because, unlike most public sources, it is focused on individuals rather than on transportation means. Furthermore, the sample of society they cover is large and representative. On the other hand, these data are not directly accessible for anonymity reasons. Thus, properly interpreting its patterns demands caution. Aware of that, we explore the behavior and inter-relations of private sources of mobility data in the context of Spain. This country represents a good experimental setting due to both its large and fast pandemic peak and its implementation of a sustained, generalized lockdown. Our work illustrates how a direct and naive comparison between sources can be misleading, as certain days (e.g., Sundays) exhibit a directly adverse behavior. After understanding their particularities, we find them to be partially correlated and, what is more important, complementary under a proper interpretation. Finally, we confirm that mobile-data can be used to evaluate the efficiency of implemented policies, detect changes in mobility trends, and provide insights into what new normality means in Spain.

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A dataset on affiliation of venture capitalists in China between 2000 and 2016

Scientific Data ◽

10.1038/s41597-021-00993-w ◽

2021 ◽

Vol 8 (1) ◽

Author(s):

Jin Chen ◽

Tianyuan Chen ◽

Yifei Song ◽

Bin Hao ◽

Ling Ma

Keyword(s):

Data Sources ◽

Venture Capitalists ◽

High Quality ◽

Public Agency ◽

Multiple Data Sources ◽

Multiple Data ◽

Multi Stage ◽

The World ◽

Prior Literature ◽

Innovation And Entrepreneurship

AbstractPrior literature emphasizes the distinct roles of differently affiliated venture capitalists (VCs) in nurturing innovation and entrepreneurship. Although China has become the second largest VC market in the world, the unavailability of high-quality datasets on VC affiliation in China’s market hinders such research efforts. To fill up this important gap, we compiled a new panel dataset of VC affiliation in China’s market from multiple data sources. Specifically, we drew on a list of 6,553 VCs that have invested in China between 2000 and 2016 from CVSource database, collected VC’s shareholder information from public sources, and developed a multi-stage procedure to label each VC as the following types: GVC (public agency-affiliated, state-owned enterprise-affiliated), CVC (corporate VC), IVC (independent VC), BVC (bank-affiliated VC), FVC (financial/non-bank-affiliated VC), UVC (university endowment/spin-out unit), and PenVC (pension-affiliated VC). We also denoted whether a VC has foreign background. This dataset helps researchers conduct more nuanced investigations into the investment behaviors of different VCs and their distinct impacts on innovation and entrepreneurship in China’s context.

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Combining data from existing company data sources: architecture and experiences

Proceedings of the 33rd Annual Hawaii International Conference on System Sciences ◽

10.1109/hicss.2000.926901 ◽

2005 ◽

Cited By ~ 1

Author(s):

J. Vanhanen ◽

K. Risku ◽

P. Kilponen

Keyword(s):

Data Sources ◽

Combining Data

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A computationally tractable birth-death model that combines phylogenetic and epidemiological data

10.1101/2020.10.21.349068 ◽

2020 ◽

Author(s):

Alexander E. Zarebski ◽

Louis du Plessis ◽

Kris V. Parag ◽

Oliver G. Pybus

Keyword(s):

Transmission Rate ◽

Epidemiological Data ◽

Heterogeneous Data ◽

Pathogen Transmission ◽

Data Sources ◽

Primary Data ◽

Analytic Approximation ◽

Data Set ◽

Combining Data ◽

Birth Death

Inferring the dynamics of pathogen transmission during an outbreak is an important problem in both infectious disease epidemiology and phylodynamics. In mathematical epidemiology, estimates are often informed by time-series of infected cases while in phylodynamics genetic sequences sampled through time are the primary data source. Each data type provides different, and potentially complementary, insights into transmission. However inference methods are typically highly specialised and field-specific. Recent studies have recognised the benefits of combining data sources, which include improved estimates of the transmission rate and number of infected individuals. However, the methods they employ are either computationally prohibitive or require intensive simulation, limiting their real-time utility. We present a novel birth-death phylogenetic model, called TimTam which can be informed by both phylogenetic and epidemiological data. Moreover, we derive a tractable analytic approximation of the TimTam likelihood, the computational complexity of which is linear in the size of the data set. Using the TimTam we show how key parameters of transmission dynamics and the number of unreported infections can be estimated accurately using these heterogeneous data sources. The approximate likelihood facilitates inference on large data sets, an important consideration as such data become increasingly common due to improving sequencing capability.

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URBAN SCENE CLASSIFICATION USING FEATURES EXTRACTED FROM PHOTOGRAMMETRIC POINT CLOUDS ACQUIRED BY UAV

ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences ◽

10.5194/isprs-archives-xlii-2-w13-511-2019 ◽

2019 ◽

Vol XLII-2/W13 ◽

pp. 511-518 ◽

Cited By ~ 1

Author(s):

G. G. Pessoa ◽

R. C. Santos ◽

A. C. Carrilho ◽

M. Galo ◽

A. Amorim

Keyword(s):

Point Clouds ◽

Bare Soil ◽

Urban Environments ◽

Data Sources ◽

Classification Error ◽

Error Matrix ◽

Urban Scenes ◽

Optical Images ◽

Combining Data ◽

Quantitative Analyses

<p><strong>Abstract.</strong> Images and LiDAR point clouds are the two major data sources used by the photogrammetry and remote sensing community. Although different, the synergy between these two data sources has motivated exploration of the potential for combining data in various applications, especially for classification and extraction of information in urban environments. Despite the efforts of the scientific community, integrating LiDAR data and images remains a challenging task. For this reason, the development of Unmanned Aerial Vehicles (UAVs) along with the integration and synchronization of positioning receivers, inertial systems and off-the-shelf imaging sensors has enabled the exploitation of the high-density photogrammetric point cloud (PPC) as an alternative, obviating the need to integrate LiDAR and optical images. This study therefore aims to compare the results of PPC classification in urban scenes considering radiometric-only, geometric-only and combined radiometric and geometric data applied to the Random Forest algorithm. For this study the following classes were considered: buildings, asphalt, trees, grass, bare soil, sidewalks and power lines, which encompass the most common objects in urban scenes. The classification procedure was performed considering radiometric features (Green band, Red band, NIR band, NDVI and Saturation) and geometric features (Height – nDSM, Linearity, Planarity, Scatter, Anisotropy, Omnivariance and Eigenentropy). The quantitative analyses were performed by means of the classification error matrix using the following metrics: overall accuracy, recall and precision. The quantitative analyses present overall accuracy of 0.80, 0.74 and 0.98 for classification considering radiometric, geometric and both data combined, respectively.</p>

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Sanksi Pidana terhadap Guru yang Melakukan Tindak Penganiayaan kepada Murid saat Proses Pembelajaran

Jurnal Konstruksi Hukum ◽

10.22225/jkh.1.1.2127.44-50 ◽

2020 ◽

Vol 1 (1) ◽

pp. 44-50

Author(s):

Anak Agung Ngurah Adhi Wibisana ◽

I Made Sepud ◽

I Made Minggu Widyantara

Keyword(s):

Learning Process ◽

Teaching Methods ◽

Criminal Code ◽

The Body ◽

Data Sources ◽

Criminal Sanctions ◽

The World ◽

Pros And Cons ◽

The Right ◽

Laws And Regulations

Indonesia has a law on education, namely Law No. 14 of 2005 on Teachers and Lecturers. In its implementation, there is a case that causes pros and cons to the statement of every article of the Teacher and Lecturer Law, especially in relation to the right to defend oneself in criminal acts of persecution. The purpose of this research is to know the arrangement of teaching methods for students during the learning process and to know the criminal sanctions against teachers who abuse students during the learning process. This study uses a normative method with the main data sources namely laws and regulations. The results showed that the element of an act, and / or the result of an act, pain in the body, and injuries to the body contained in Article 351 paragraph (1) of the Criminal Code refers to the Teacher and Lecturer Law, namely in Article 77 paragraph (6). This article defines the basis of persecution, namely actions that cause pain to a person. The criminal act of persecution in the world of education, at least, must be considered with the intention of disciplining and educating the nation's life.

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