Pub Date : 2018-10-01DOI: 10.1109/eScience.2018.00066
C. D. Vreese, C. Martinez-Ortiz
n/a
{"title":"Message from the eScience 2018 Program Committee Chairs for the Focused Session on Advances in eScience for the Humanities and Social Sciences","authors":"C. D. Vreese, C. Martinez-Ortiz","doi":"10.1109/eScience.2018.00066","DOIUrl":"https://doi.org/10.1109/eScience.2018.00066","url":null,"abstract":"n/a","PeriodicalId":6476,"journal":{"name":"2018 IEEE 14th International Conference on e-Science (e-Science)","volume":"144 1","pages":"307-307"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77816906","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-10-01DOI: 10.1109/eScience.2018.00020
Raúl Palma, Andres Garcia-Silva, José Manuél Gómez-Pérez, M. Krystek
Data-intensive science disciplines, like Earth Science, are increasingly producing and consuming a variety of digital resources during the course of a scientific investigation. Instead of having these resources in isolated repositories, scientists are seeking ways for managing and making these resources available from a single place, and at the same time they are also increasingly interested in the adoption of FAIR principles to enhance the visibility and reusability of scientific results. This has called for new methods to improve the access and communication of results. Research Objects are a key building block towards realising this vision. They provide a structured way (a model) to describe scientific resources related to an investigation, along with the context in which they were used and the people involved. But research objects are as useful in practice as the availability of tools supporting their adoption. In this paper, we present a toolkit, tailored for Earth Sciences, comprising a set of services and applications around research objects that support scientists throughout the research lifecycle to manage, share, find and reuse scientific results, and we discuss initial insights into the community adoption.
{"title":"A Research Object-Based Toolkit to Support the Earth Science Research Lifecycle","authors":"Raúl Palma, Andres Garcia-Silva, José Manuél Gómez-Pérez, M. Krystek","doi":"10.1109/eScience.2018.00020","DOIUrl":"https://doi.org/10.1109/eScience.2018.00020","url":null,"abstract":"Data-intensive science disciplines, like Earth Science, are increasingly producing and consuming a variety of digital resources during the course of a scientific investigation. Instead of having these resources in isolated repositories, scientists are seeking ways for managing and making these resources available from a single place, and at the same time they are also increasingly interested in the adoption of FAIR principles to enhance the visibility and reusability of scientific results. This has called for new methods to improve the access and communication of results. Research Objects are a key building block towards realising this vision. They provide a structured way (a model) to describe scientific resources related to an investigation, along with the context in which they were used and the people involved. But research objects are as useful in practice as the availability of tools supporting their adoption. In this paper, we present a toolkit, tailored for Earth Sciences, comprising a set of services and applications around research objects that support scientists throughout the research lifecycle to manage, share, find and reuse scientific results, and we discuss initial insights into the community adoption.","PeriodicalId":6476,"journal":{"name":"2018 IEEE 14th International Conference on e-Science (e-Science)","volume":"43 1","pages":"50-57"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82537997","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-10-01DOI: 10.1109/eScience.2018.00062
Shuang Li, K. V. D. Velde, M. Swertz
The rapid advances in the genomic study have made genetics testing common in today's diagnostic practices [1]. Next-generation sequencing provides researchers with a huge amount of genomic data, yet the interpretation still in its infancy [5].The diagnostics yield is still around 30% [1, 3, 8]. Interpretation tools for analyzing the genomic data is needed.
{"title":"Machine Learning for Multi-Omics Data Integration and Variant Pathogenicity Estimation","authors":"Shuang Li, K. V. D. Velde, M. Swertz","doi":"10.1109/eScience.2018.00062","DOIUrl":"https://doi.org/10.1109/eScience.2018.00062","url":null,"abstract":"The rapid advances in the genomic study have made genetics testing common in today's diagnostic practices [1]. Next-generation sequencing provides researchers with a huge amount of genomic data, yet the interpretation still in its infancy [5].The diagnostics yield is still around 30% [1, 3, 8]. Interpretation tools for analyzing the genomic data is needed.","PeriodicalId":6476,"journal":{"name":"2018 IEEE 14th International Conference on e-Science (e-Science)","volume":"48 1","pages":"301-301"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79932455","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-10-01DOI: 10.1109/eScience.2018.00052
J. Heringa, V. V. Hees
n/a
{"title":"Message from the eScience 2018 Program Committee Chairs for the Focused Session on Data Handling and Analytics for Health","authors":"J. Heringa, V. V. Hees","doi":"10.1109/eScience.2018.00052","DOIUrl":"https://doi.org/10.1109/eScience.2018.00052","url":null,"abstract":"n/a","PeriodicalId":6476,"journal":{"name":"2018 IEEE 14th International Conference on e-Science (e-Science)","volume":"2015 1","pages":"285-285"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88660075","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-10-01DOI: 10.1109/ESCIENCE.2018.00140
A. Truskinger, M. Brereton, P. Roe
Monitoring the environment with acoustic sensors is now practical; sensors are sold as commercial devices, storage is cheap, and the field of ecoacoustics is recognized as an effective way to scale monitoring of the environment. However, a pressing challenge faced in many eScience projects is how to manage, analyze, and visualize very large data so that scientists can benefit, with ecoacoustic data presenting its own particular challenges. This paper presents a new zoomable interactive visualization interface for the exploration of environmental audio data. The interface is a new tool in the Acoustic Workbench, an ecoacoustics software platform built for managing environmental audio data. This Google Maps like interface for audio data, enables zooming in and out of audio data by incorporating specialized, multiresolution, visual representations of audio data into the workbench website. The ‘zooming’ visualization allows scientists to surface the structure, detail, and patterns in content that would otherwise be opaque to them, from scales of seconds through to weeks of data. The Ecosounds instance of the Acoustic Workbench contains 52 years (108 TB) of audio data, from 1016 locations, which results in a 180 million-tile, 8.3 terapixel visualization. The design and implementation of this novel big audio data visualization is presented along with some design considerations for storing visualization tiles.
{"title":"Visualizing five decades of environmental acoustic data","authors":"A. Truskinger, M. Brereton, P. Roe","doi":"10.1109/ESCIENCE.2018.00140","DOIUrl":"https://doi.org/10.1109/ESCIENCE.2018.00140","url":null,"abstract":"Monitoring the environment with acoustic sensors is now practical; sensors are sold as commercial devices, storage is cheap, and the field of ecoacoustics is recognized as an effective way to scale monitoring of the environment. However, a pressing challenge faced in many eScience projects is how to manage, analyze, and visualize very large data so that scientists can benefit, with ecoacoustic data presenting its own particular challenges. This paper presents a new zoomable interactive visualization interface for the exploration of environmental audio data. The interface is a new tool in the Acoustic Workbench, an ecoacoustics software platform built for managing environmental audio data. This Google Maps like interface for audio data, enables zooming in and out of audio data by incorporating specialized, multiresolution, visual representations of audio data into the workbench website. The ‘zooming’ visualization allows scientists to surface the structure, detail, and patterns in content that would otherwise be opaque to them, from scales of seconds through to weeks of data. The Ecosounds instance of the Acoustic Workbench contains 52 years (108 TB) of audio data, from 1016 locations, which results in a 180 million-tile, 8.3 terapixel visualization. The design and implementation of this novel big audio data visualization is presented along with some design considerations for storing visualization tiles.","PeriodicalId":6476,"journal":{"name":"2018 IEEE 14th International Conference on e-Science (e-Science)","volume":"273 1","pages":"1-10"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84780462","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-10-01DOI: 10.1109/eScience.2018.00127
F. Diblen, J. Attema, R. Bakhshi, B. Stienen, L. Hendriks, S. Caron
n/a
N/A
{"title":"SPOT: Open Source Visual Data Analytics Platform for High-Dimensional Scientific Data","authors":"F. Diblen, J. Attema, R. Bakhshi, B. Stienen, L. Hendriks, S. Caron","doi":"10.1109/eScience.2018.00127","DOIUrl":"https://doi.org/10.1109/eScience.2018.00127","url":null,"abstract":"n/a","PeriodicalId":6476,"journal":{"name":"2018 IEEE 14th International Conference on e-Science (e-Science)","volume":"87 11 1","pages":"411-411"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87687623","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-10-01DOI: 10.1109/eScience.2018.00050
I. G. Martí, G. Schrier, J. Noteboom, P. Diks
n/a
{"title":"Detecting Probability of Ice Formation on Overhead Lines of the Dutch Railway Network","authors":"I. G. Martí, G. Schrier, J. Noteboom, P. Diks","doi":"10.1109/eScience.2018.00050","DOIUrl":"https://doi.org/10.1109/eScience.2018.00050","url":null,"abstract":"n/a","PeriodicalId":6476,"journal":{"name":"2018 IEEE 14th International Conference on e-Science (e-Science)","volume":"8 1","pages":"281-282"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79675310","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-10-01DOI: 10.1109/eScience.2018.00073
M. Alfano, S. Cunningham, Wouter Meulemans, Ignaz Rutter, Max Sondag, B. Speckmann, Emily Sullivan
n/a
{"title":"Social Network-Epistemology","authors":"M. Alfano, S. Cunningham, Wouter Meulemans, Ignaz Rutter, Max Sondag, B. Speckmann, Emily Sullivan","doi":"10.1109/eScience.2018.00073","DOIUrl":"https://doi.org/10.1109/eScience.2018.00073","url":null,"abstract":"n/a","PeriodicalId":6476,"journal":{"name":"2018 IEEE 14th International Conference on e-Science (e-Science)","volume":"40 1","pages":"320-321"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88220867","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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