Guest editorial: large-scale data curation and metadata management

The recent and growing focus on reproducibility in neuroimaging studies has led many major academic centers to use cloud-based imaging databases for storing, analyzing, and sharing complex imaging data. Flywheel is one such database platform that offers easily accessible, large-scale data management, along with a framework for reproducible analyses through containerized pipelines. The Brain Imaging Data Structure (BIDS) is the de facto standard for neuroimaging data, but curating neuroimaging data into BIDS can be a challenging and time-consuming task. In particular, standard solutions for BIDS curation are limited on Flywheel. To address these challenges, we developed “FlywheelTools,” a software toolbox for reproducible data curation and manipulation on Flywheel. FlywheelTools includes two elements: fw-heudiconv, for heuristic-driven curation of data into BIDS, and flaudit, which audits and inventories projects on Flywheel. Together, these tools accelerate reproducible neuroscience research on the widely used Flywheel platform.

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An India Towards Global Ranking Standards: A Move Towards Data Curation

International Journal of Innovative Technology and Exploring Engineering - Special Issue ◽

10.35940/ijitee.g5551.019320 ◽

2020 ◽

Vol 9 (3) ◽

pp. 504-509

Keyword(s):

Higher Education ◽

Human Resource Development ◽

Large Scale ◽

Education Sector ◽

Data Curation ◽

Open Architecture ◽

Global Ranking ◽

Large Scale Data ◽

Vision 2030 ◽

Scale Data

Ministry of Human Resource Development (MHRD) is not only a source of inspiration for sectors such as Research and Development, Services, Agriculture and Entrepreneurship. They are also enhancing our competitiveness and relevance by proposing and executing different projects across the nation. The approach is in line with the vision 2030. As per 2018 Shanghai report of Times Higher Education (THE), only 40% academic and 10% of employer reputation is built as per the Global Ranking Standards. Indian Higher Educational warehouses with the help of National Institutional Ranking Framework (NIRF), Rashtriya Uchchatar Shiksha Abhiyan (RUSA) and University Grant Commission (UGC) are generating data which is of least relevance to end users. We propose peer to peer data curation model which shall be extended as per business need using a cloud technology. We have harnessed data related to the Higher Education Sector (HES) from Indian Institute of Sciences (IISc), RUSA, and MHRD, to understand Indian contribution towards global ranking standards in Higher Education Sector. The approach is in line with the Escuela Nueva Model and Open Architecture Information System (OAIS) as existing standards in traditional data curation process. It is supported by the patent in large-scale data curation

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Guest Editorial: Computational Solutions to Large-Scale Data Management and Analysis in Translational and Personalized Medicine

IEEE Journal of Biomedical and Health Informatics ◽

10.1109/jbhi.2014.2315513 ◽

2014 ◽

Vol 18 (3) ◽

pp. 720-721 ◽

Cited By ~ 3

Author(s):

Manolis Tsiknakis ◽

Vasilis J. Promponas ◽

Norbert Graf ◽

May D. Wang ◽

Stephen T. C. Wong ◽

...

Keyword(s):

Personalized Medicine ◽

Data Management ◽

Large Scale ◽

Guest Editorial ◽

Large Scale Data ◽

And Personalized Medicine ◽

Scale Data

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Guest Editorial: Thematic Issue on ‘Metaheuristics for large scale data mining’

Memetic Computing ◽

10.1007/s12293-010-0050-7 ◽

2010 ◽

Vol 2 (3) ◽

pp. 163-164 ◽

Cited By ~ 1

Author(s):

Jaume Bacardit ◽

Xavier Llorà

Keyword(s):

Data Mining ◽

Large Scale ◽

Guest Editorial ◽

Thematic Issue ◽

Large Scale Data ◽

Scale Data

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GUEST EDITORIAL Introduction to the Special Issue Using Transparency to Achieve Equality

Law in Context. A Socio-legal Journal ◽

10.26826/law-in-context.v37i2.165 ◽

2021 ◽

Vol 37 (2) ◽

pp. 6-11

Author(s):

Dominique Allen ◽

Alysia Blackham

Keyword(s):

Large Scale ◽

Guest Editorial ◽

Public Life ◽

Editorial Introduction ◽

Special Issue ◽

Large Scale Data ◽

Scale Data

This Guest Editorial introduces a Special Issue of Law in Context which considers how the collection of large-scale data by government entities and organisations might advance the equality agenda across diverse areas of public life, and how best to manage the risks of this emerging strategy. Drawing on interdisciplinary perspectives and the insights of policymakers, the articles and comments listed below seek to develop new principles to guide government and organisational activity in this novel endeavour.

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