BAXSQL: A Functional MRI Data Management Tool for the Medical Grid Using Ninf-G

2006 ◽  
Author(s):  
Epifanio Bagarinao ◽  
Yoshio Tanaka
Keyword(s):  
Data Management ◽  
Functional Mri ◽  
Management Tool

Autonomous production data management tool by using edge computing devices

2016 ◽  
Vol 2016 (0) ◽  
pp. S1440103
Author(s):  
Hikaru ISHIGURI ◽  
Chinghui WU ◽  
Kouhei OGAWA ◽  
Nagomu MORITA ◽  
Yasuyuki NISHIOKA
Keyword(s):  
Data Management ◽  
Edge Computing ◽  
Management Tool ◽  
Production Data

P77 Use of edit-query tables as a data management tool in clinical trials

1995 ◽  
Vol 16 (3) ◽  
pp. 116S
Author(s):  
Glen A.B. Feak ◽  
Brenda W. Gillespie ◽  
Kenneth E. Guire ◽  
David C. Musch
Keyword(s):  
Clinical Trials ◽  
Data Management ◽  
Management Tool

scholarly journals GeoDarwin, an Open-Source Geological Data Management Tool

2019 ◽  
Vol 3 ◽  
Author(s):  
Pascale Lahogue ◽  
Jean-Marc Herpers ◽  
Franck Theeten ◽  
Didier VandenSpiegel
Keyword(s):  
Data Management ◽  
Open Source ◽  
Central Africa ◽  
Biological Data ◽  
Heavy Minerals ◽  
Management Tool ◽  
Field Observations ◽  
Geological Data ◽  
Web Interface ◽  
Natural Heritage

The Royal Museum for Central Africa (RMCA) holds one of the largest world collections of geological samples and documents about Central Africa (Congo, Rwanda, Burundi), offering unique reference material. The Geology services of RMCA contain around 16,000 minerals, 300,000 rocks, 21,500 fossils, and 30,000 maps. Their Archives include field notes, books, maps, and aerial photography containing valuable complementary information. GeoDaRWIN is an “in-house” solution developed by RMCA as a collections management system for geological collections. Created using Microsoft Access, the model is currently transferred to open source software’s consisting of a PostgreSQL database and a customizable web-interface based on the Symfony 3 framework. Development began in 2018 and is still ongoing. Around 12,000 samples, 29,000 documents, and 30,500 localizations are already in the database. GeoDaRWIN manages three categories collection materials: 1) field observations with their localization (e.g., coordinates, lithostratigraphy, drilling, structural analysis), 2) samples (minerals, rocks, fossils) and the results of their analysis (e.g., constituent minerals of rocks, heavy minerals, granulometry, magnetic susceptibility), and 3) documents (e.g., maps, archives, aerial photos, satellite images, documentation). In the model, these three types of information (field observations, samples, and documents) retain the existing relationships between them. The aim of the project is to centralize all data in a single system on a service that can be available both on internet and intranet. It thus offers a common relational data model for these different geological items. The emphasis has been set on the integration of a hierarchical thesaurus of keywords, which can be mapped to several international vocabularies (e.g., INSPIRE, GEMET, examples coming from the GeoSciML documentation). A Github repository of the database web interface in Symfony 3.4 is available at: https://github.com/naturalsciences/ natural_heritage_geology. This system aims also to be compliant with the central data portal developed by the Royal Museum for Central Africa, the Royal Belgian Institute of Natural Sciences, and Meise Botanical Garden. This portal will provide a common gateway to Belgian scientific data, one of the objectives of the project “Natural Heritage”, along with the development of databases for biological data (database called “DaRWIN”, more info on poster “DaRWIN, Open Source system for collections data management”) and geological data (“GeoDaRWIN”). See more info about project “Natural Heritage” in the poster "NaturalHeritage: Bridging Belgian Natural History Collections".

scholarly journals DataUp: A tool to help researchers describe and share tabular data

F1000Research ◽  
2014 ◽  
Vol 3 ◽  
pp. 6 ◽  
Author(s):  
Carly Strasser ◽  
John Kunze ◽  
Stephen Abrams ◽  
Patricia Cruse
Keyword(s):  
At Risk ◽  
Data Management ◽  
Management Practices ◽  
Management Tool ◽  
Long Term Storage ◽  
Large Numbers ◽  
Metadata Standards ◽  
Heterogeneous Datasets ◽  
Analysis Workflow ◽  
Survey Results

Scientific datasets have immeasurable value, but they lose their value over time without proper documentation, long-term storage, and easy discovery and access. Across disciplines as diverse as astronomy, demography, archeology, and ecology, large numbers of small heterogeneous datasets (i.e., the long tail of data) are especially at risk unless they are properly documented, saved, and shared. One unifying factor for many of these at-risk datasets is that they reside in spreadsheets.In response to this need, the California Digital Library (CDL) partnered with Microsoft Research Connections and the Gordon and Betty Moore Foundation to create the DataUp data management tool for Microsoft Excel. Many researchers creating these small, heterogeneous datasets use Excel at some point in their data collection and analysis workflow, so we were interested in developing a data management tool that fits easily into those work flows and minimizes the learning curve for researchers.The DataUp project began in August 2011. We first formally assessed the needs of researchers by conducting surveys and interviews of our target research groups: earth, environmental, and ecological scientists. We found that, on average, researchers had very poor data management practices, were not aware of data centers or metadata standards, and did not understand the benefits of data management or sharing. Based on our survey results, we composed a list of desirable components and requirements and solicited feedback from the community to prioritize potential features of the DataUp tool. These requirements were then relayed to the software developers, and DataUp was successfully launched in October 2012.

scholarly journals Movebank

2018 ◽  
pp. 24-27 ◽  
Author(s):  
Tomasz Mrozewski
Keyword(s):  
Data Management ◽  
Management Tool ◽  
Special Focus ◽  
Tracking Data ◽  
Web Based ◽  
Data Archiving ◽  
Animal Tracking

Movebank is a web-based data management tool and data archiving repository for animal tracking data. Its special focus enables specialized search and discovery tools for users searching for animal tracking data. However, there are some idiosyncrasies with the site and researcher update is not universal.

scholarly journals AUDABLOK: Engaging Citizens in Open Data Refinement through Blockchain

Proceedings ◽  
2019 ◽  
Vol 31 (1) ◽  
pp. 52 ◽  
Author(s):  
Mikel Emaldi ◽  
Koldo Zabaleta ◽  
Diego López-de-Ipiña
Keyword(s):  
Data Management ◽  
Open Data ◽  
Human Computation ◽  
Management Tool ◽  
Data Refinement ◽  
Comprehensive Knowledge ◽  
Change Requests

This work describes how open data and human computation can be brought together through blockchain to foster the collaboration of citizens on the continuous enhancement of open data portals. For that, it contributes with a set of enhancements to the widely adopted data management tool Comprehensive Knowledge Archive Network (CKAN), to allow full audit and management of the change requests posed by citizens to datasets in open data portals. User contributions’ sustainability in time is tackled by providing rewards to users through AudaCoins, a currency that rewards citizens according to their refinement contributions, thus encouraging their continuous engagement with city co-creation activities.

scholarly journals VCPA: genomic variant calling pipeline and data management tool for Alzheimer’s Disease Sequencing Project

2019 ◽  
Vol 35 (11) ◽  
pp. 1985-1985
Author(s):  
Yuk Yee Leung ◽  
Otto Valladares ◽  
Yi-Fan Chou ◽  
Han-Jen Lin ◽  
Amanda B Kuzma ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Data Management ◽  
Variant Calling ◽  
Management Tool ◽  
Sequencing Project ◽  
Genomic Variant

scholarly journals DataUp: A tool to help researchers describe and share tabular data

F1000Research ◽  
2014 ◽  
Vol 3 ◽  
pp. 6 ◽  
Author(s):  
Carly Strasser ◽  
John Kunze ◽  
Stephen Abrams ◽  
Patricia Cruse
Keyword(s):  
At Risk ◽  
Data Management ◽  
Management Practices ◽  
Management Tool ◽  
Long Term Storage ◽  
Large Numbers ◽  
Metadata Standards ◽  
Heterogeneous Datasets ◽  
Analysis Workflow ◽  
Survey Results

Scientific datasets have immeasurable value, but they lose their value over time without proper documentation, long-term storage, and easy discovery and access. Across disciplines as diverse as astronomy, demography, archeology, and ecology, large numbers of small heterogeneous datasets (i.e., the long tail of data) are especially at risk unless they are properly documented, saved, and shared. One unifying factor for many of these at-risk datasets is that they reside in spreadsheets. In response to this need, the California Digital Library (CDL) partnered with Microsoft Research Connections and the Gordon and Betty Moore Foundation to create the DataUp data management tool for Microsoft Excel. Many researchers creating these small, heterogeneous datasets use Excel at some point in their data collection and analysis workflow, so we were interested in developing a data management tool that fits easily into those work flows and minimizes the learning curve for researchers. The DataUp project began in August 2011. We first formally assessed the needs of researchers by conducting surveys and interviews of our target research groups: earth, environmental, and ecological scientists. We found that, on average, researchers had very poor data management practices, were not aware of data centers or metadata standards, and did not understand the benefits of data management or sharing. Based on our survey results, we composed a list of desirable components and requirements and solicited feedback from the community to prioritize potential features of the DataUp tool. These requirements were then relayed to the software developers, and DataUp was successfully launched in October 2012.

scholarly journals The Ark: a customizable web-based data management tool for health and medical research

2016 ◽  
pp. btw675 ◽  
Author(s):  
Adrian Bickerstaffe ◽  
Thilina Ranaweera ◽  
Travis Endersby ◽  
Christopher Ellis ◽  
Sanjaya Maddumarachchi ◽  
...  
Keyword(s):  
Data Management ◽  
Medical Research ◽  
Management Tool ◽  
Web Based
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