OPM: Object-Protocol Model Data Management Tools ’97

BACKGROUND Health-related data being collected by smartphones offer a promising complementary approach to in-clinic assessments. OBJECTIVE Here we introduce the JuTrack platform as a secure, reliable and extendable open-source solution for remote monitoring in daily-life and digital phenotyping. METHODS JuTrack consists of an Android-based smartphone application and a web-based project management dashboard. A wide range of anonymized measurements from motion-sensors, social and physical activities and geolocation information can be collected in either active or passive modes. The dashboard also provides management tools to monitor and manage data collection across studies. To facilitate scaling, reproducibility, data management and sharing we integrated DataLad as a data management infrastructure. JuTrack was developed to comply with security, privacy and the General Data Protection Regulation (GDPR) requirements. RESULTS JuTrack is an open-source (released under open-source Apache 2.0 licenses) platform for remote assessment of digital biomarkers (DB) in neurological, psychiatric and other indications. The main components of the JuTrack platform and examples of data being collected using JuTrack are presented here. CONCLUSIONS Smartphone-based Digital Biomarker data may provide valuable insight into daily life behaviour in health and disease. JuTrack provides an easy and reliable open-source solution for collection of such data.

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The Geometrical Analysis of Deformations Based on an Optimal Network Design and Proper Data Management Tools

Optimization and Artificial Intelligence in Civil and Structural Engineering ◽

10.1007/978-94-017-2490-6_21 ◽

1992 ◽

pp. 503-524

Author(s):

L. Gründig

Keyword(s):

Data Management ◽

Network Design ◽

Geometrical Analysis ◽

Management Tools ◽

Optimal Network Design ◽

Optimal Network

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Data Management Tools

Data Management and Data Description ◽

10.4324/9780429463662-4 ◽

2019 ◽

pp. 115-138

Author(s):

Richard Williams

Keyword(s):

Data Management ◽

Management Tools

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Managing Data Persistence in Network Enabled Servers

Scientific Programming ◽

10.1155/2005/151604 ◽

2005 ◽

Vol 13 (4) ◽

pp. 333-354 ◽

Cited By ~ 1

Author(s):

Eddy Caron ◽

Bruno DelFabbro ◽

Frédéric Desprez ◽

Emmanuel Jeannot ◽

Jean-Marc Nicod

Keyword(s):

Data Management ◽

Experimental Results ◽

Model Data ◽

Client Server ◽

University Of Tennessee ◽

Communication Time ◽

Data Persistence ◽

Remote Client ◽

The University ◽

Global Grid

The GridRPC model [17] is an emerging standard promoted by the Global Grid Forum (GGF) that defines how to perform remote client-server computations on a distributed architecture. In this model data are sent back to the client at the end of every computation. This implies unnecessary communications when computed data are needed by an other server in further computations. Since, communication time is sometimes the dominant cost of remote computations, this cost has to be lowered. Several tools instantiate the GridRPC model such as NetSolve developed at the University of Tennessee, Knoxville, USA, and DIET developed at LIP laboratory, ENS Lyon, France. They are usually called Network Enabled Servers (NES). In this paper, we present a discussion of the data management solutions chosen for these two NES (NetSolve and DIET) as well as experimental results.

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