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Data, Volume 3, Issue 1 (March 2018)

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Open AccessData Descriptor A Data Set of Portuguese Traditional Recipes Based on Published Cookery Books
Received: 27 December 2017 / Revised: 1 March 2018 / Accepted: 5 March 2018 / Published: 8 March 2018
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Abstract
This paper presents a data set resulting from the abstraction of books of traditional recipes for Portuguese cuisine. Only starters, main courses, side dishes, and soups were considered. Desserts, cakes, sweets, puddings, and pastries were not included. Recipes were characterized by the province
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This paper presents a data set resulting from the abstraction of books of traditional recipes for Portuguese cuisine. Only starters, main courses, side dishes, and soups were considered. Desserts, cakes, sweets, puddings, and pastries were not included. Recipes were characterized by the province and ingredients regardless of quantities or preparation. An exploratory characterization of recipes and ingredients is presented. Results show that Portuguese traditional recipes organize differently among the eleven provinces considered, setting up the basis for more detailed analyses of the 1382 recipes and 421 ingredients inventoried. Full article
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Open AccessData Descriptor RAE: The Rainforest Automation Energy Dataset for Smart Grid Meter Data Analysis
Received: 31 December 2017 / Revised: 8 February 2018 / Accepted: 9 February 2018 / Published: 12 February 2018
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Abstract
Datasets are important for researchers to build models and test how well their machine learning algorithms perform. This paper presents the Rainforest Automation Energy (RAE) dataset to help smart grid researchers test their algorithms that make use of smart meter data. This initial
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Datasets are important for researchers to build models and test how well their machine learning algorithms perform. This paper presents the Rainforest Automation Energy (RAE) dataset to help smart grid researchers test their algorithms that make use of smart meter data. This initial release of RAE contains 1 Hz data (mains and sub-meters) from two residential houses. In addition to power data, environmental and sensor data from the house’s thermostat is included. Sub-meter data from one of the houses includes heat pump and rental suite captures, which is of interest to power utilities. We also show an energy breakdown of each house and show (by example) how RAE can be used to test non-intrusive load monitoring (NILM) algorithms. Full article
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Open AccessArticle Uttarakhand Medicinal Plants Database (UMPDB): A Platform for Exploring Genomic, Chemical, and Traditional Knowledge
Received: 12 December 2017 / Revised: 11 January 2018 / Accepted: 23 January 2018 / Published: 26 January 2018
Cited by 1 | PDF Full-text (3366 KB) | HTML Full-text | XML Full-text
Abstract
Medicinal plants are the main natural pools for the primary health care system, ethno-medicine, as well as traditional Indian system of several medicines. Uttarakhand also known as ‘Herbal State’, is a rich source of medicinal plants and traditional medicinal knowledge. A great deal
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Medicinal plants are the main natural pools for the primary health care system, ethno-medicine, as well as traditional Indian system of several medicines. Uttarakhand also known as ‘Herbal State’, is a rich source of medicinal plants and traditional medicinal knowledge. A great deal of information about medicinal plants of Uttarakhand is scattered in different forms. Although many medicinal plant databases are available, currently there is no cohesive manually curated database of medicinal plants widely distributed in Uttarakhand state. A comprehensive database has been developed, known as the Uttarakhand Medicinal Plants Database (UMPDB). UMPDB provides extensive information on botanical name, common name, taxonomy, genomic taxonomy id, habit, habitat, location in Uttarakhand, part use, medicinal use, genomic information (including number of nucleotides, proteins, ESTs), chemical information, and scientific literature. Annotated medicinal plants integrated in the current version of the database were collected from the existing books, databases, and available literature. The current version of UMPDB contains the 1127 records of medicinal plants which belong to 153 plant families distributed across 13 districts of Uttarakhand. The primary goal of developing this database is to provide traditional, genomic, and chemical descriptions of the medicinal plants exclusively found in various regions of Uttarakhand. We anticipate that embedded information in the database would help users to readily obtain desired information. Full article
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Open AccessEditorial Acknowledgement to Reviewers of Data in 2017
Received: 26 January 2018 / Revised: 26 January 2018 / Accepted: 26 January 2018 / Published: 26 January 2018
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Abstract
Peer review is an essential part in the publication process, ensuring that Data maintains high quality standards for its published papers [...] Full article
Open AccessData Descriptor Thirty Thousand 3D Models from Thingiverse
Received: 18 December 2017 / Revised: 12 January 2018 / Accepted: 16 January 2018 / Published: 18 January 2018
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Abstract
This dataset contains files and geometrical analysis of 3D model data, acquired from the thingiverse online repository. More than thirty thousand stereolithography files (STL) were retrieved and analysed. The geometrical analysis of the respective models is presented along with model renderings in both
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This dataset contains files and geometrical analysis of 3D model data, acquired from the thingiverse online repository. More than thirty thousand stereolithography files (STL) were retrieved and analysed. The geometrical analysis of the respective models is presented along with model renderings in both GIF and PNG format, and pre-sliced machine instructions as GCode. This dataset is intended to be used as a basis for further research in Additive Manufacturing (AM), such as 3D printing time estimation, printability assessment or slicing algorithm development. All files retrieved are user-generated, with the respective user and associated licence presented in the overview. The dataset was acquired between 2016 and 2017. Full article
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Open AccessData Descriptor Long-Term WiFi Fingerprinting Dataset for Research on Robust Indoor Positioning
Received: 24 November 2017 / Revised: 22 December 2017 / Accepted: 9 January 2018 / Published: 16 January 2018
Cited by 1 | PDF Full-text (3259 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
WiFi fingerprinting, one of the most popular methods employed in indoor positioning, currently faces two major problems: lack of robustness to short and long time signal changes and difficult reproducibility of new methods presented in the relevant literature. This paper presents a WiFi
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WiFi fingerprinting, one of the most popular methods employed in indoor positioning, currently faces two major problems: lack of robustness to short and long time signal changes and difficult reproducibility of new methods presented in the relevant literature. This paper presents a WiFi RSS (Received Signal Strength) database created to foster and ease research works that address the above-mentioned two problems. A trained professional took several consecutive fingerprints while standing at specific positions and facing specific directions. The consecutive fingerprints may enable the study of short-term signals variations. The data collection spanned over 15 months, and, for each month, one type of training datasets and five types of test datasets were collected. The measurements of a dataset type (training or test) were taken at the same positions and directions every month, in order to enable the analysis of long-term signal variations. The database is provided with supporting materials and software, which give more information about the collection environment and eases the database utilization, respectively. The WiFi measurements and the supporting materials are available at the Zenodo repository under the open-source MIT license. Full article
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Open AccessArticle CoeViz: A Web-Based Integrative Platform for Interactive Visualization of Large Similarity and Distance Matrices
Received: 2 December 2017 / Revised: 10 January 2018 / Accepted: 11 January 2018 / Published: 13 January 2018
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Abstract
Similarity and distance matrices are general data structures that describe reciprocal relationships between the objects within a given dataset. Commonly used methods for representation of these matrices include heatmaps, hierarchical trees, dimensionality reduction, and various types of networks. However, despite a well-developed foundation
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Similarity and distance matrices are general data structures that describe reciprocal relationships between the objects within a given dataset. Commonly used methods for representation of these matrices include heatmaps, hierarchical trees, dimensionality reduction, and various types of networks. However, despite a well-developed foundation for the visualization of such representations, the challenge of creating an interactive view that would allow for quick data navigation and interpretation remains largely unaddressed. This problem becomes especially evident for large matrices with hundreds or thousands objects. In this work, we present a web-based platform for the interactive analysis of large (dis-)similarity matrices. It consists of four major interconnected and synchronized components: a zoomable heatmap, interactive hierarchical tree, scalable circular relationship diagram, and 3D multi-dimensional scaling (MDS) scatterplot. We demonstrate the use of the platform for the analysis of amino acid covariance data in proteins as part of our previously developed CoeViz tool. The web-platform enables quick and focused analysis of protein features, such as structural domains and functional sites. Full article
(This article belongs to the Special Issue Biological Data Visualization)
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Open AccessData Descriptor A Data Set of Human Body Movements for Physical Rehabilitation Exercises
Received: 10 November 2017 / Revised: 8 January 2018 / Accepted: 8 January 2018 / Published: 11 January 2018
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Abstract
The article presents University of Idaho-Physical Rehabilitation Movement Data (UI-PRMD), a publically available data set of movements related to common exercises performed by patients in physical rehabilitation programs. For the data collection, 10 healthy subjects performed 10 repetitions of different physical therapy movements
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The article presents University of Idaho-Physical Rehabilitation Movement Data (UI-PRMD), a publically available data set of movements related to common exercises performed by patients in physical rehabilitation programs. For the data collection, 10 healthy subjects performed 10 repetitions of different physical therapy movements with a Vicon optical tracker and a Microsoft Kinect sensor used for the motion capturing. The data are in a format that includes positions and angles of full-body joints. The objective of the data set is to provide a basis for mathematical modeling of therapy movements, as well as for establishing performance metrics for evaluation of patient consistency in executing the prescribed rehabilitation exercises. Full article
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Open AccessData Descriptor World Ocean Isopycnal Level Absolute Geostrophic Velocity (WOIL-V) Inverted from GDEM with the P-Vector Method
Received: 28 September 2017 / Revised: 21 December 2017 / Accepted: 2 January 2018 / Published: 7 January 2018
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Abstract
Three-dimensional dataset of world ocean climatological annual and monthly mean absolute geostrophic velocity in isopycnal level (called WOIL-V) has been produced from the United States (U.S.) Navy’s Generalized Digital Environmental Model (GDEM) temperature and salinity fields (open access from the website http://data.nodc.noaa.gov/cgi-bin/iso?id=gov.noaa.nodc:9600094)
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Three-dimensional dataset of world ocean climatological annual and monthly mean absolute geostrophic velocity in isopycnal level (called WOIL-V) has been produced from the United States (U.S.) Navy’s Generalized Digital Environmental Model (GDEM) temperature and salinity fields (open access from the website http://data.nodc.noaa.gov/cgi-bin/iso?id=gov.noaa.nodc:9600094) using the P-vector method. The data have horizontal resolution of 0.5° × 0.5°, and 222 isopycnal-levels. The total 13 data files include annual and monthly mean values. The WOIL-V is the only dataset of absolute geostrophic velocity in isopycnal level compatible to the GDEM (T, S) fields, and provides background ocean currents for oceanographic and climatic studies, especially in ocean modeling with the isopycnal coordinate system. Full article
(This article belongs to the Special Issue Open Data and Robust & Reliable GIScience)
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