scholarly journals CyBy2: A Structure-based Data Management Tool for Chemical and Biological Data

2012 ◽  
Vol 66 (3) ◽  
pp. 132-134 ◽  
Author(s):  
Stefan Höck ◽  
Rainer Riedl
Keyword(s):  
Data Management ◽  
Biological Data ◽  
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".

Enabling Massive XML-Based Biological Data Management in HBase

2020 ◽  
Vol 17 (6) ◽  
pp. 1994-2004 ◽  
Author(s):  
Jian Liu ◽  
Qiuru Liu ◽  
Lei Zhang ◽  
Shuhui Su ◽  
Yongzhuang Liu
Keyword(s):  
Data Management ◽  
Biological Data ◽  
Biological Data Management

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 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 grant is dead, long live the data - migration as a pragmatic exit strategy for research data preservation

2019 ◽  
Vol 4 ◽  
pp. 104 ◽  
Author(s):  
Tomasz Zielinski ◽  
Johnny Hay ◽  
Andrew J. Millar
Keyword(s):  
Systems Biology ◽  
Data Management ◽  
Data Gathering ◽  
Research Data ◽  
Biological Data ◽  
Data Migration ◽  
Exit Strategy ◽  
Data Preservation ◽  
Plant Systems Biology ◽  
Future Outcomes

Open research, data sharing and data re-use have become a priority for publicly- and charity-funded research. Efficient data management naturally requires computational resources that assist in data description, preservation and discovery. While it is possible to fund development of data management systems, currently it is more difficult to sustain data resources beyond the original grants. That puts the safety of the data at risk and undermines the very purpose of data gathering. PlaSMo stands for ‘Plant Systems-biology Modelling’ and the PlaSMo model repository was envisioned by the plant systems biology community in 2005 with the initial funding lasting until 2010. We addressed the sustainability of the PlaSMo repository and assured preservation of these data by implementing an exit strategy. For our exit strategy we migrated data to an alternative, public repository with secured funding. We describe details of our decision process and aspects of the implementation. Our experience may serve as an example for other projects in a similar situation. We share our reflections on the sustainability of biological data management and the future outcomes of its funding. We expect it to be a useful input for funding bodies.

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