scholarly journals BIM2Modelica - An open source toolchain for generating and simulating thermal multi-zone building models by using structured data from BIM models

2019 ◽  
Author(s):  
Christoph Nytsch-Geusen ◽  
Jörg Rädler ◽  
Matthis Thorade ◽  
Carles Ribas Tugores
Keyword(s):  
Open Source ◽  
Structured Data ◽  
Building Models

scholarly journals Sherlock: an open-source data platform to store, analyze and integrate Big Data for biology

F1000Research ◽  
2021 ◽  
Vol 10 ◽  
pp. 409
Author(s):  
Balázs Bohár ◽  
David Fazekas ◽  
Matthew Madgwick ◽  
Luca Csabai ◽  
Marton Olbei ◽  
...  
Keyword(s):  
Big Data ◽  
Data Management ◽  
Open Source ◽  
Large Scale ◽  
Genomic Sequence ◽  
Large Data ◽  
Structured Data ◽  
Biological Research ◽  
Data Platform ◽  
Big Data Technologies

In the era of Big Data, data collection underpins biological research more so than ever before. In many cases this can be as time-consuming as the analysis itself, requiring downloading multiple different public databases, with different data structures, and in general, spending days before answering any biological questions. To solve this problem, we introduce an open-source, cloud-based big data platform, called Sherlock (https://earlham-sherlock.github.io/). Sherlock provides a gap-filling way for biologists to store, convert, query, share and generate biology data, while ultimately streamlining bioinformatics data management. The Sherlock platform provides a simple interface to leverage big data technologies, such as Docker and PrestoDB. Sherlock is designed to analyse, process, query and extract the information from extremely complex and large data sets. Furthermore, Sherlock is capable of handling different structured data (interaction, localization, or genomic sequence) from several sources and converting them to a common optimized storage format, for example to the Optimized Row Columnar (ORC). This format facilitates Sherlock’s ability to quickly and easily execute distributed analytical queries on extremely large data files as well as share datasets between teams. The Sherlock platform is freely available on Github, and contains specific loader scripts for structured data sources of genomics, interaction and expression databases. With these loader scripts, users are able to easily and quickly create and work with the specific file formats, such as JavaScript Object Notation (JSON) or ORC. For computational biology and large-scale bioinformatics projects, Sherlock provides an open-source platform empowering data management, data analytics, data integration and collaboration through modern big data technologies.

scholarly journals Open-Source Tool for Transforming CityGML Levels of Detail

Energies ◽  
2021 ◽  
Vol 14 (24) ◽  
pp. 8250
Author(s):  
Avichal Malhotra ◽  
Simon Raming ◽  
Jérôme Frisch ◽  
Christoph van Treeck
Keyword(s):  
Open Source ◽  
Open Data ◽  
Building Energy ◽  
Digital Form ◽  
Essential Information ◽  
Levels Of Detail ◽  
Building Models ◽  
Energy Modelling ◽  
Geometrical Information ◽  
Geometric Processing

Urban Building Energy Modelling (UBEM) requires adequate geometrical information to represent buildings in a 3D digital form. However, open data models usually lack essential information, such as building geometries, due to a lower granularity in available data. For heating demand simulations, this scarcity impacts the energy predictions and, thereby, questioning existing simulation workflows. In this paper, the authors present an open-source CityGML LoD Transformation (CityLDT) tool for upscaling or downscaling geometries of 3D spatial CityGML building models. With the current support of LoD0–2, this paper presents the adapted methodology and developed algorithms for transformations. Using the presented tool, the authors transform open CityGML datasets and conduct heating demand simulations in Modelica to validate the geometric processing of transformed building models.

scholarly journals Vega: An academic publishing system for the 21st century

2018 ◽  
Author(s):  
Cheryl E. Ball
Keyword(s):  
Open Source ◽  
Digital Publishing ◽  
Structured Data ◽  
Academic Publishing ◽  
Peer Reviews ◽  
Data Store ◽  
Open Source Data ◽  
Scholarly Communications ◽  
Interactive Experience ◽  
Reader Experience

Watch the VIDEO.Vega is a new, open-source academic publishing system, built as a collaboration between US-based library publishers and an Oslo-based design studio, Sanity (nee Bengler). Vega was built with a $1m Andrew W. Mellon Foundation grant to fill a need in academic publishing for open-source, easy-to-use editorial management system that could highlight the publication of multimedia artifacts in a born-digital publishing workflow. Vega facilitates authoring, editing, and publishing academic content as reusable structured data and facilitates innovation in indexing and presentation of this content. This short presentation will focus on the design goals underpinning Vega, specifically the goal of providing an intuitive, scholar-friendly way of editing academic documents as semantically clear, structured data while also featuring the inclusion of multimedia assets as part of the scholarly record.The Vega publishing platform incorporates collaborative digital authoring and editing platforms and a fully customizable front end for a branded reader experience. Vega is built on an open source data store and includes strong, yet flexible, editorial workflows that train editors in digital publishing best practices, especially with multimedia. For instance, the editorial dashboard features peer review options for different tracks/sections in publications, including the traditional double anonymous review process as well as collaborative reviews and fully open peer reviews, depending on each venue's and each text's needs. The UX in Vega also allows editors to see what's going on in their venues at a glance -- through a visualization that tracks each text in each stage of the editorial and production process and allows for editors to engage directly with that text with a double click regardless of where it is in the process.This presentation will highlight how Vega facilitates multiple workflows for multimodal publications (i.e. pdf, website, data, interactive experience), and how it facilitates archivability and indexability. Vega will change the scholarly communications landscape and is now available for use through free download or hosting options.

scholarly journals A ROS-Gazebo Interface for the Katana Robotic Arm Manipulation

2021 ◽  
Vol 5 (1) ◽  
pp. 26-37
Author(s):  
Rawan A. AlRashid Agha ◽  
Zhwan Hani Mahdi ◽  
Muhammed N. Sefer ◽  
Ibrahim Hamarash
Keyword(s):  
Operating System ◽  
Open Source ◽  
Robotic Systems ◽  
Robotic Arm ◽  
Code Reuse ◽  
Building Models

Nowadays, simulators are being used more and more during the development of robotic systems due to the efficiency of the development and testing processes of such applications. Undoubtedly, these simulators save time, resources and costs, as well as enable ease of demonstrations of the system. Specifically, tools like the open source Robotic Operating System (ROS) and Gazebo have gained popularity in building models of robotic systems. ROS is extensively used in robotics due to the pros of hardware abstraction and code reuse. The Gazebo platform is used for visualisation because of its high compatibility with ROS. In this paper, ROS and Gazebo have been integrated to build an interface for the visualisation of the Katana Arm manipulator.

Building your own ERMS

2015 ◽  
Vol 32 (3) ◽  
pp. 9-12 ◽  
Author(s):  
Jason C Simon
Keyword(s):  
Resource Management ◽  
Open Source ◽  
Management System ◽  
Design Methodology ◽  
Structured Data ◽  
Financial Data ◽  
Electronic Resource ◽  
Content Type ◽  
Resource Management System ◽  
Bibliographic Data

Purpose – The paper aims to demonstrate a method for creating an electronic resource management system (ERMS) from freely available open source tools. This system will help manage bibliographic data, holdings and statistical and financial data for electronic databases and periodicals. Design/methodology/approach – The paper demonstrates how to create a database and interface for managing serials and electronic resources using PHP and MySQL within a *AMP framework. Findings – By following this approach, libraries can maintain structured data regarding their electronic and print holdings with minimal expense and with flexibility that is not necessarily possible through large commercial products, while avoiding the burden of implementing a large, open source solution. Originality/value – While many products exist on the market, either commercial or large open source solutions, there is little documentation on how to create a small scalable ERMS. This paper attempts to demonstrate a method.

scholarly journals 3D CITYGML BUILDING MODELLING FROM LIDAR POINT CLOUD DATA

2018 ◽  
Vol XLII-5 ◽  
pp. 175-180 ◽  
Author(s):  
P. Jayaraj ◽  
A. M. Ramiya
Keyword(s):  
Open Source ◽  
Point Cloud ◽  
Smart Cities ◽  
Open Data ◽  
3D Models ◽  
Airborne Lidar ◽  
Model Framework ◽  
Cloud Data ◽  
Building Models ◽  
Virtual City

<p><strong>Abstract.</strong> With recent government initiatives for smart cities, 3D virtual city models are in demand for managing and monitoring the urban infrastructure. 3D building models forms an important component of 3D virtual city model. LiDAR remote sensing has revolutionized the way the third dimension can be precisely mapped and proved to be an important source of data for 3D models. The model thus generated should be in an open data format to be used across various applications. CityGML is an open data model framework that enables storage and exchange of 3D models which can be used for diversified applications. The main objective of this research is to develop a methodological workflow to create 3D building models in CityGML standard from airborne LiDAR point cloud. Initially building points were isolated from the airborne LiDAR data using point cloud processing algorithms. 3D building models with levels of detail (LoD1 and LoD2) were generated from the building points in CityGML standard using commercial (ArcGISPro) well as open source packages (3dfier, Citygml4j). Results prove that the models developed using open source packages are comparable to that provided by commercial packages.</p>

scholarly journals Brain Modeling ToolKit: An open source software suite for multiscale modeling of brain circuits

2020 ◽  
Vol 16 (11) ◽  
pp. e1008386
Author(s):  
Kael Dai ◽  
Sergey L. Gratiy ◽  
Yazan N. Billeh ◽  
Richard Xu ◽  
Binghuang Cai ◽  
...  
Keyword(s):  
Open Source ◽  
Large Scale ◽  
Experimental Studies ◽  
Software Suite ◽  
Massive Datasets ◽  
Building Models ◽  
Brain Modeling ◽  
Multiple Levels ◽  
Set Up ◽  
Modeling Toolkit

Experimental studies in neuroscience are producing data at a rapidly increasing rate, providing exciting opportunities and formidable challenges to existing theoretical and modeling approaches. To turn massive datasets into predictive quantitative frameworks, the field needs software solutions for systematic integration of data into realistic, multiscale models. Here we describe the Brain Modeling ToolKit (BMTK), a software suite for building models and performing simulations at multiple levels of resolution, from biophysically detailed multi-compartmental, to point-neuron, to population-statistical approaches. Leveraging the SONATA file format and existing software such as NEURON, NEST, and others, BMTK offers a consistent user experience across multiple levels of resolution. It permits highly sophisticated simulations to be set up with little coding required, thus lowering entry barriers to new users. We illustrate successful applications of BMTK to large-scale simulations of a cortical area. BMTK is an open-source package provided as a resource supporting modeling-based discovery in the community.

scholarly journals Brain Modeling ToolKit: an Open Source Software Suite for Multiscale Modeling of Brain Circuits

2020 ◽  
Author(s):  
Kael Dai ◽  
Sergey L. Gratiy ◽  
Yazan N. Billeh ◽  
Richard Xu ◽  
Binghuang Cai ◽  
...  
Keyword(s):  
Open Source ◽  
Large Scale ◽  
Experimental Studies ◽  
Software Suite ◽  
Massive Datasets ◽  
Building Models ◽  
Brain Modeling ◽  
Multiple Levels ◽  
Set Up ◽  
Modeling Toolkit

AbstractExperimental studies in neuroscience are producing data at a rapidly increasing rate, providing exciting opportunities and formidable challenges to existing theoretical and modeling approaches. To turn massive datasets into predictive quantitative frameworks, the field needs software solutions for systematic integration of data into realistic, multiscale models. Here we describe the Brain Modeling ToolKit (BMTK), a software suite for building models and performing simulations at multiple levels of resolution, from biophysically detailed multi-compartmental, to point-neuron, to population-statistical approaches. Leveraging the SONATA file format and existing software such as NEURON, NEST, and others, BMTK offers consistent user experience across multiple levels of resolution. It permits highly sophisticated simulations to be set up with little coding required, thus lowering entry barriers to new users. We illustrate successful applications of BMTK to large-scale simulations of a cortical area. BMTK is an open-source package provided as a resource supporting modeling-based discovery in the community.

scholarly journals Energym: A Building Model Library for Controller Benchmarking

2021 ◽  
Vol 11 (8) ◽  
pp. 3518
Author(s):  
Paul Scharnhorst ◽  
Baptiste Schubnel ◽  
Carlos Fernández Bandera ◽  
Jaume Salom ◽  
Paolo Taddeo ◽  
...  
Keyword(s):  
Open Source ◽  
Performance Indicators ◽  
Key Performance Indicators ◽  
Technical Equipment ◽  
Uncertain Variables ◽  
Building Model ◽  
Model Library ◽  
Building Models ◽  
Formal Definitions ◽  
And Control

We introduce the Python-based open-source library Energym, a building model library to test and benchmark building controllers. The incorporated building models are presented with a brief explanation of their function, location and technical equipment. Furthermore, the library structure is described, highlighting the necessary features to provide the benchmarking and control capabilities, i.e., standardized evaluation scenarios, key performance indicators (KPIs) and forecasts of uncertain variables. We go on to characterize the evaluation scenarios for each of the models and give formal definitions of the KPIs. We describe the calibration methodologies used for constructing the models and illustrate their usage through examples.

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