MyCrystals– a simple visual data management program for laboratory-scale crystallization experiments

2009 ◽  
Vol 42 (4) ◽  
pp. 741-742
Author(s):  
Monika Nøhr Løvgreen ◽  
Mikkel Løvgreen ◽  
Hans E. M. Christensen ◽  
Pernille Harris
Keyword(s):  
Data Management ◽  
Management Program ◽  
Laboratory Scale ◽  
Visual Data ◽  
Crystallization Experiments ◽  
Crystallization Conditions ◽  
User Friendly

MyCrystalsis designed as a user-friendly program to display crystal images and list crystallization conditions. The crystallization conditions entry fields can be customized to suit the experiments.MyCrystalsis also able to sort the images by the entered crystallization conditions, which presents a unique opportunity to easily assess the effect of, for example, changing pH or concentration and thus establish the best conditions to be used for optimization.

scholarly journals A local platform for user-friendly FAIR data management and reproducible analytics

2021 ◽  
Author(s):  
Florian Wieser ◽  
Sarah Stryeck ◽  
Konrad Lang ◽  
Christoph Hahn ◽  
Gerhard Thallinger ◽  
...  
Keyword(s):  
Data Management ◽  
User Friendly

Towards an Indigenist data management program: reflections on experiences developing an atlas of sea ice knowledge and use

2011 ◽  
Vol 55 (1) ◽  
pp. 108-124 ◽  
Author(s):  
Peter L. Pulsifer ◽  
Gita J. Laidler ◽  
D. R. Fraser Taylor ◽  
Amos Hayes
Keyword(s):  
Sea Ice ◽  
Data Management ◽  
Management Program

Learnings From Data Management and Integration Efforts on the Enbridge Pipeline System

2004 ◽  
Author(s):  
Garry L. Sommer ◽  
Brad S. Smith
Keyword(s):  
Data Management ◽  
Management Program ◽  
Pipeline System ◽  
Data Set ◽  
Data Alignment ◽  
Commercial Market ◽  
History Of ◽  
Integrity Management ◽  
Management Effort ◽  
Analysis System

Enbridge Pipelines Inc. operates one of the longest and most complex pipeline systems in the world. A key aspect of the Enbridge Integrity Management Program (IMP) is the trending, analysis, and management of data collected from over 50 years of pipeline operations. This paper/presentation describes Enbridge’s challenges, learnings, processes, and innovations for meeting today’s increased data management/integration demands. While much has been written around the premise of data management/integration, and many software solutions are available in the commercial market, the greatest data management challenge for mature pipeline operators arises from the variability of data (variety of technologies, data capture methods, and data accuracy levels) collected over the operating history of the system. Ability to bring this variable data set together is substantially the most difficult aspect of a coordinated data management effort and is critical to the success of any such project. Failure to do this will result in lack of user confidence and inability to gain “buy-in” to new data management processes. In 2001 Enbridge began a series of initiatives to enhance data management and analysis. Central to this was the commitment to accurate geospatial alignment of integrity data. This paper/presentation describes Enbridge’s experience with development of custom software (Integrated Spatial Analysis System – ISAS) including critical learnings around a.) Data alignment efforts and b.) Significant efforts involved in development of an accurate pipe centreline. The paper/presentation will also describe co-incident data management programs that link to ISAS. This includes enhanced database functionality for excavation data and development of software to enable electronic transfer of data to this database. These tools were built to enable rapid transfer of field data and “real time” tool validation through automated unity plots of tool defect data vs. that measured in the field.

Diabetes Data Management Program Available for Microcomputers

Diabetes Care ◽  
1984 ◽  
Vol 7 (4) ◽  
pp. 401-402 ◽  
Author(s):  
D. Rodbard ◽  
N. Pernick ◽  
M. L. Jaffe
Keyword(s):  
Data Management ◽  
Management Program

scholarly journals Design of Reference Phantom for Quality Control of Conventional X-ray Radiography Units in Port Sudan

2020 ◽  
Vol 7 (1) ◽  
pp. 01-09
Author(s):  
Yousif Mohamed Y. Abdallah ◽  
Wail Zaki ◽  
Babeker Ahmadoun ◽  
Abuobeada Musa
Keyword(s):  
Quality Control ◽  
Quality Assurance ◽  
Medical Physics ◽  
Low Cost ◽  
Management Program ◽  
X Rays ◽  
Resource Limited ◽  
Physics Department ◽  
User Friendly ◽  
Product Output

The Quality Control (QC) system, based on simple, cheap equipment and minimum personnel time, enables a resource-limited facility and staff to control the fundamental components of the imaging process on a low cost basis. Quality Assurance (QA) is a product or service quality management program. Customer reviews, capacity building and quality control can also be included. Quality control requires specific measures for ensuring measurable process-related aspects of product output or for the delivery of services within a given limit. Research was conducted at the Medical Physics Department of Red Sea University. The main objective of this work was to boost quality assurance rays. The imagination is more user-friendly and produces better results than a person or object. Phantoms, including fluoroscopy or x-rays, and certain image quality measurements have been used in x-rays imaging. The manufactured phantom in this study showed high precision in different QC tests.

scholarly journals SisGen: A CORBA–Based Data Management Program for DNA Sequencing Projects

2008 ◽  
pp. 116-123 ◽  
Author(s):  
Georgios J. Pappas ◽  
Robson P. Miranda ◽  
Natália F. Martins ◽  
Roberto C. Togawa ◽  
Marcos M. C. Costa
Keyword(s):  
Dna Sequencing ◽  
Data Management ◽  
Management Program

scholarly journals SISTEM INFORMASI PENGELOLAAN DATA LAUNDRY PADA RUMAH LAUNDRY BEKASI

2019 ◽  
Vol 5 (1) ◽  
pp. 29-36
Author(s):  
Susy Rosyida ◽  
Verry Riyanto
Keyword(s):  
Data Collection ◽  
Data Management ◽  
Management Program ◽  
Software Requirements ◽  
The Public ◽  
Transaction Process ◽  
Previous Note ◽  
Long Time ◽  
Analysis Design ◽  
Software Requirements Analysis

Laundry house is a business engaged in services in washing and drying, especially clothing. To serve the public in the field of laundry services, the laundry house in managing the data is still done manually and has not been computerized so there are still errors in the transaction process. Problems that occur in a laundry house such as incorrectly recording the type of package, the calculation is still using a calculator tool, in making the report must see the notes that have been collected previously, must see previous records recorded in the ledger, and be vulnerable to losing previous note notes so that it takes a long time and the results obtained are less accurate. The purpose of this study is to build a laundry data management program using the waterfall method which consists of 5 stages, namely, software requirements analysis, design, programming code, testing and support or maintenance. While the data collection is through observation, interviews and searching for literature related to this research so that it can solve problems related to laundry data management activities, especially in the process of receiving laundry services transactions to be more effective and efficient and can improve service to customers. The results of the study show that this laundry data management program can help and simplify the process of receiving laundry services at the laundry house.

scholarly journals Knowledge and Practice changes following a student data focused data management education program.

2021 ◽  
Author(s):  
Tina M Griffin
Keyword(s):  
Life Cycle ◽  
Graduate Students ◽  
Data Management ◽  
Management Education ◽  
Management Program ◽  
Management Skills ◽  
Student Knowledge ◽  
Data Life Cycle ◽  
Knowledge And Practice ◽  
Faculty Mentors

Introduction It is known that graduate students work with research data more intimately than their faculty mentors. Because of this, much data management education is geared toward this population. However, student learning has predominantly been assessed through measures of satisfaction and attendance rather than through evaluating knowledge and skills acquired. This study attempts to advance assessment efforts by asking students to report their knowledge and practice changes before, immediately after, and six months following education. Methods Graduate students in STEM and Health sciences disciplines self-enrolled in an eight-week data management program that used their research projects as the focus for learning. Three surveys were administered (pre, post, and six months following) to determine changes in students’ knowledge and practices regarding data management skills. The survey consisted of approximately 115 Likert-style questions and covered major aspects of the data life cycle. Results & discussion Overall students increased their data management knowledge and improved their skills in all areas of the data life cycle. Students readily adopted practices for straightforward tasks like determining storage and improving file naming. Students improved but struggled with tasks that were more involved like sharing data and documenting code. For most of these practices, students consistently implemented them through the six month follow up period. Conclusion Impact of data management education lasts significantly beyond immediate instruction. In depth assessment of student knowledge and practices indicates where this education is effective and where it needs further support. It is likely that this effect is due to the program length and focus on implementation.

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