scholarly journals A Radiocarbon Age Calculation Program for Windows

Radiocarbon ◽  
2002 ◽  
Vol 44 (1) ◽  
pp. 223-224 ◽  
Author(s):  
D Gallagher ◽  
E J McGee ◽  
P I Mitchell
Keyword(s):  
Data Management ◽  
Laboratory Data ◽  
Successful Operation ◽  
Commercial Software ◽  
Radiocarbon Age ◽  
Storage And Retrieval ◽  
Software Company ◽  
The Creation ◽  
Associated Data

The management of counting files, the calculation of radiocarbon age, and the creation and maintenance of databases for storage and retrieval of laboratory data are time-consuming and exacting tasks. These routine functions are essential to the successful operation of all 14C dating laboratories. However, since the number of 14C dating laboratories worldwide is rather limited, it is unlikely that a commercial software company will produce a program for use in 14C age calculation and associated data management. We have therefore developed Windows based software to meet some of these needs.

The Laboratory Data Management Computer — The appropriate source of cost reports in hospital budgeting systems

1987 ◽  
Vol 2 (3) ◽  
pp. 221-232
Author(s):  
G. Dale ◽  
J.A. Fleetwood ◽  
B. Johnson ◽  
D.R. Walton
Keyword(s):  
Data Management ◽  
Laboratory Data

scholarly journals Characterizing Big Data Management

10.28945/2192 ◽  
2015 ◽  
Author(s):  
Rogério Rossi ◽  
Kechi Hirama
Keyword(s):  
Decision Making ◽  
Information Technology ◽  
Big Data ◽  
Data Management ◽  
Process Management ◽  
Three Dimensions ◽  
Storage And Retrieval ◽  
Human Aspects ◽  
Business Approach ◽  
Support Decision Making

[The final form of this paper was published in the journal Issues in Informing Science and Information Technology.] Considering that big data is a reality for an increasing number of organizations in many areas, its management represents a set of challenges involving big data modeling, storage and retrieval, analysis and visualization. However, technological resources, people and processes are crucial dimensions to facilitate the management of big data in any organization, allowing information and knowledge from a large volume of data to support decision-making. Big data management must be supported by technology, people and processes; hence, this article discusses these three dimensions: the technologies for storage, analysis and visualization of big data; the human aspects of big data; and, in addition, the process management involved in a technological and business approach for big data management.

scholarly journals Clinical features, laboratory data, management and the risk factors that affect the mortality in patients with postoperative meningitis

2008 ◽  
Vol 56 (4) ◽  
pp. 433 ◽  
Author(s):  
Ilknur Erdem ◽  
Tayfun Hakan ◽  
Nurgul Ceran ◽  
Fatma Metin ◽  
SenihaSenbayrak Akcay ◽  
...  
Keyword(s):  
Risk Factors ◽  
Data Management ◽  
Clinical Features ◽  
Laboratory Data ◽  
Postoperative Meningitis

Opportunities and Implementation of Big Data Management in Academic Libraries

2021 ◽  
pp. 35-47
Author(s):  
Mahesh G. T. ◽  
Nandeesha B.
Keyword(s):  
Big Data ◽  
Data Management ◽  
Academic Libraries ◽  
Strong Association ◽  
Karnataka State ◽  
The World ◽  
The Government ◽  
Associated Data

Data has changed the world in an unbelievable way and made an impact on our lifestyles at an exceptional rate. Big data is now the latest science of exploring and forecasting human-machine behavior dealing with a massive amount of associated data. The study is intended to understand the intensity and the competencies of librarians in implementing big data initiative project in academic libraries by the Government of Karnataka State. The study also tries to understand the application of big data in these libraries; 68 (87.17%) librarians completed the survey out of 78 respondents. The results of the study showed a strong association, that is, 72 (92.30%) respondents had the essential competencies and 58 (75.64%) librarians ability, intensity, readiness in implementing big data in academic libraries.

The Creation of a Commercial Software Development Company in a Developing Country for Outsourcing Purposes

2008 ◽  
pp. 862-869
Author(s):  
Sam Lubbe
Keyword(s):  
Software Development ◽  
Developing Country ◽  
Financial Services ◽  
Growth Process ◽  
Technical Skill ◽  
Commercial Software ◽  
The Creation ◽  
Advanced Development

SDC has financial services knowledge with cross-industry technical skill capabilities. Their emphasis is on advanced development techniques and tools. The model they used is proving to be successful for all parties and the growth process had provided them with invaluable experience and expertise in the HR transformation. The lesson they have is that they need to ensure that they have a strong presence in the market.

A microcomputer-based measuring device for biological research

1981 ◽  
Vol 59 (8) ◽  
pp. 1611-1614 ◽  
Author(s):  
W. Gary Sprules ◽  
L. Blair Holtby ◽  
Gerald Griggs
Keyword(s):  
Data Storage ◽  
Biological Research ◽  
Fish Scale ◽  
Body Proportions ◽  
Measuring Device ◽  
Storage And Retrieval ◽  
Phytoplankton Size ◽  
Image Analyzers ◽  
Associated Data ◽  
Size Data

As an inexpensive, more versatile alternative to the Coulter counter and image analyzers for the acquisition of size data in biological research, a semiautomated measuring device with associated data storage and retrieval capabilities has been developed. It can be used for measurement of such diverse characters as zooplankton body size and helmet lengths, phytoplankton size, fish scale measurements, fish egg diameters, and general taxonomic features such as body proportions and inter-setule distances. Any organism, or part thereof, which can be scaled to the device's range of approximately 1–7 cm can be quickly and accurately counted and (or) measured.

scholarly journals A Fully Decentralized Triplestore Managed via the Ethereum Blockchain

2021 ◽  
Author(s):  
Damien Graux ◽  
Sina Mahmoodi
Keyword(s):  
Fault Tolerance ◽  
Data Management ◽  
Management Strategies ◽  
Open Data ◽  
High Quality ◽  
Data Infrastructure ◽  
The Public ◽  
Storage And Retrieval ◽  
Web Of Data ◽  
Barrier To Entry

The growing web of data warrants better data management strategies. Data silos are single points of failure and they face availability problems which lead to broken links. Furthermore the dynamic nature of some datasets increases the need for a versioning scheme. In this work, we propose a novel architecture for a linked open data infrastructure, built on open decentralized technologies. IPFS is used for storage and retrieval of data, and the public Ethereum blockchain is used for naming, versioning and storing metadata of datasets. We furthermore exploit two mechanisms for maintaining a collection of relevant, high-quality datasets in a distributed manner in which participants are incentivized. The platform is shown to have a low barrier to entry and censorship-resistance. It benefits from the fault-tolerance of its underlying technologies. Furthermore, we validate the approach by implementing our solution.

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