A Community-Based IoT Service Platform to Locally Disseminate Socially-Valuable Data : Best effort local data sharing network with no conscious effort?

2019 ◽  
Author(s):  
Yozo Shoji ◽  
Kiyohide Nakauchi ◽  
Wei Liu ◽  
Yoshito Watanabe ◽  
Kazuhiro Maruyama ◽  
...  
Keyword(s):  
Data Sharing ◽  
Local Data ◽  
Community Based ◽  
Service Platform ◽  
Best Effort ◽  
Valuable Data ◽  
Conscious Effort

5G based SmartCity Convergence Service Platform for Data sharing

2020 ◽  
Author(s):  
Jiyeon Kim ◽  
Sooyoung Jang ◽  
Deockgu Jee ◽  
Eunjin Ko ◽  
Seung Han Choi ◽  
...  
Keyword(s):  
Data Sharing ◽  
Service Platform

scholarly journals Designing a podiatry service to meet the needs of the population: a service simulation

2007 ◽  
Vol 31 (1) ◽  
pp. 63 ◽  
Author(s):  
Jackie A Campbell
Keyword(s):  
Local Community ◽  
Deterministic Model ◽  
Waiting Lists ◽  
Local Data ◽  
Community Based ◽  
Foot Health ◽  
Skill Mix ◽  
Staffing Levels ◽  
Number Of Patients ◽  
Community Based Services

A model of a podiatry service has been developed which takes into consideration the effect of changing access criteria, skill mix and staffing levels (among others) given fixed local staffing budgets and the foot-health characteristics of the local community. A spreadsheet-based deterministic model was chosen to allow maximum transparency of programming. This work models a podiatry service in England, but could be adapted for other settings and, with some modification, for other community-based services. This model enables individual services to see the effect on outcome parameters such as number of patients treated, number discharged and size of waiting lists of various service configurations, given their individual local data profile. The process of designing the model has also had spin-off benefits for the participants in making explicit many of the implicit rules used in managing their services.

scholarly journals Building an Up-and-Coming City – An overview of the Geological Data Sharing Service Platform of the Xiongan New Area

China Geology ◽  
2019 ◽  
Vol 3 (4) ◽  
pp. 566-568
Author(s):  
Qian Wang ◽  
◽  
Xiao-yuan Zhou ◽  
Zhi-bin Huo ◽  
Lei Shi ◽  
...  
Keyword(s):  
Data Sharing ◽  
Geological Data ◽  
Service Platform

A Blockchain-Based Federated Learning

2021 ◽  
pp. 158-177
Author(s):  
Ankit Khushal Barai ◽  
Robin Singh Bhadoria ◽  
Jyotshana Bagwari ◽  
Ivan A. Perl
Keyword(s):  
Machine Learning ◽  
Neural Networks ◽  
Data Sharing ◽  
Training Data ◽  
Local Data ◽  
Audit Trail ◽  
Blockchain Technology ◽  
Conventional Machine ◽  
Healthcare Finance ◽  
Access Policies

Conventional machine learning (ML) needs centralized training data to be present on a given machine or datacenter. The healthcare, finance, and other institutions where data sharing is prohibited require an approach for training ML models in secured architecture. Recently, techniques such as federated learning (FL), MIT Media Lab's Split Neural networks, blockchain, aim to address privacy and regulation of data. However, there are difference between the design principles of FL and the requirements of Institutions like healthcare, finance, etc., which needs blockchain-orchestrated FL having the following features: clients with their local data can define access policies to their data and define how updated weights are to be encrypted between the workers and the aggregator using blockchain technology and also prepares audit trail logs undertaken within network and it keeps actual list of participants hidden. This is expected to remove barriers in a range of sectors including healthcare, finance, security, logistics, governance, operations, and manufacturing.

scholarly journals Promoting FAIR Data Through Community-driven Agile Design: the Open Data Commons for Spinal Cord Injury (odc-sci.org)

2021 ◽  
Author(s):  
Abel Torres-Espín ◽  
Carlos A. Almeida ◽  
Austin Chou ◽  
J. Russell Huie ◽  
Michael Chiu ◽  
...  
Keyword(s):  
Spinal Cord ◽  
Spinal Cord Injury ◽  
Data Sharing ◽  
Open Data ◽  
Current Data ◽  
Community Based ◽  
Stage Of Development ◽  
Cord Injury ◽  
Agile Design ◽  
Data Commons

AbstractThe past decade has seen accelerating movement from data protectionism in publishing toward open data sharing to improve reproducibility and translation of biomedical research. Developing data sharing infrastructures to meet these new demands remains a challenge. One model for data sharing involves simply attaching data, irrespective of its type, to publisher websites or general use repositories. However, some argue this creates a ‘data dump’ that does not promote the goals of making data Findable, Accessible, Interoperable and Reusable (FAIR). Specialized data sharing communities offer an alternative model where data are curated by domain experts to make it both open and FAIR. We report on our experiences developing one such data-sharing ecosystem focusing on ‘long-tail’ preclinical data, the Open Data Commons for Spinal Cord Injury (odc-sci.org). ODC-SCI was developed with community-based agile design requirements directly pulled from a series of workshops with multiple stakeholders (researchers, consumers, non-profit funders, governmental agencies, journals, and industry members). ODC-SCI focuses on heterogeneous tabular data collected by preclinical researchers including bio-behaviour, histopathology findings and molecular endpoints. This has led to an example of a specialized neurocommons that is well-embraced by the community it aims to serve. In the present paper, we provide a review of the community-based design template and describe the adoption by the community including a high-level review of current data assets, publicly released datasets, and web analytics. Although odc-sci.org is in its late beta stage of development, it represents a successful example of a specialized data commons that may serve as a model for other fields.

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