Long term stabilities of magnetic tape for data storage in office environment

2015 ◽  
Vol 117 (17) ◽  
pp. 17E305 ◽  
Author(s):  
Kazutoshi Katayama ◽  
Yuka Chinda ◽  
Osamu Shimizu ◽  
Yasutomo Goto ◽  
Mayumi Suzuki ◽  
...  
Keyword(s):  
Data Storage ◽  
Magnetic Tape ◽  
Office Environment

Long-Term Stability of Magnetic Tape for Data Storage Under an Accelerated Condition

2016 ◽  
Vol 52 (7) ◽  
pp. 1-4
Author(s):  
Kazutoshi Katayama ◽  
Yuka Chinda ◽  
Osamu Shimizu ◽  
Tatsuo Mikami ◽  
Mayumi Suzuki ◽  
...  
Keyword(s):  
Data Storage ◽  
Magnetic Tape ◽  
Term Stability ◽  
Long Term Stability

Skew Estimation and Compensation in Tape Drives With Flangeless Rollers

2013 ◽  
Author(s):  
Kazuhiro Tsuruta ◽  
Angeliki Pantazi ◽  
Giovanni Cherubini ◽  
Jens Jelitto
Keyword(s):  
Growth Rate ◽  
Data Storage ◽  
Magnetic Tape ◽  
Information Storage ◽  
Annual Growth Rate ◽  
Track Width ◽  
Compound Annual Growth Rate ◽  
Head Positioning ◽  
Term Data

Magnetic tape remains the medium of choice for long-term data storage at the lowest possible cost. Moreover, tape-cartridge capacities are expected to maintain a compound annual growth rate of about 40%, resulting in a 128 TByte tape-cartridge capacity by 2022, as forecast by the Information Storage Industry Consortium (INSIC) roadmap [1]. To achieve these capacities in future tape products, the data track width has to be aggressively reduced through ultra-precise tape head positioning.

scholarly journals The on-premise data sharing infrastructure e!DAL: Foster FAIR data for faster data acquisition

GigaScience ◽  
2020 ◽  
Vol 9 (10) ◽  
Author(s):  
Daniel Arend ◽  
Patrick König ◽  
Astrid Junker ◽  
Uwe Scholz ◽  
Matthias Lange
Keyword(s):  
Data Management ◽  
Data Storage ◽  
Best Practice ◽  
Research Process ◽  
Research Data ◽  
Primary Data ◽  
Data Repository ◽  
Plant Genomics ◽  
Quality Of Data

Abstract Background The FAIR data principle as a commitment to support long-term research data management is widely accepted in the scientific community. Although the ELIXIR Core Data Resources and other established infrastructures provide comprehensive and long-term stable services and platforms for FAIR data management, a large quantity of research data is still hidden or at risk of getting lost. Currently, high-throughput plant genomics and phenomics technologies are producing research data in abundance, the storage of which is not covered by established core databases. This concerns the data volume, e.g., time series of images or high-resolution hyper-spectral data; the quality of data formatting and annotation, e.g., with regard to structure and annotation specifications of core databases; uncovered data domains; or organizational constraints prohibiting primary data storage outside institional boundaries. Results To share these potentially dark data in a FAIR way and master these challenges the ELIXIR Germany/de.NBI service Plant Genomic and Phenomics Research Data Repository (PGP) implements a “bring the infrastructure to the data” approach, which allows research data to be kept in place and wrapped in a FAIR-aware software infrastructure. This article presents new features of the e!DAL infrastructure software and the PGP repository as a best practice on how to easily set up FAIR-compliant and intuitive research data services. Furthermore, the integration of the ELIXIR Authentication and Authorization Infrastructure (AAI) and data discovery services are introduced as means to lower technical barriers and to increase the visibility of research data. Conclusion The e!DAL software matured to a powerful and FAIR-compliant infrastructure, while keeping the focus on flexible setup and integration into existing infrastructures and into the daily research process.

A Minicomputer-Based Emission Spectrographic Analysis System Dependent on Scanning Microphotometry

1979 ◽  
Vol 33 (6) ◽  
pp. 604-612 ◽  
Author(s):  
Catharine P. Thomas
Keyword(s):  
Preliminary Data ◽  
Magnetic Tape ◽  
Data Bank ◽  
Spectrographic Analysis ◽  
Geologic Materials ◽  
Analytical Curve ◽  
Priority Scheme ◽  
Analysis System ◽  
Survey Analyses

A minicomputer-based, semiquantitative, emission spectrographic system was designed to perform survey analyses (64 elements per sample), on a wide variety of geologic materials rapidly (9 s per determination). The system can analyze as many as 40 000 samples per year, while maintaining long-term consistency of results, and can provide archival storage capability (photoplate, microfiche, data bank). The minicomputer's partitioned memory allows simultaneous execution of programs to acquire 92 000 sequential, digitized, transmittance-readings per spectrum from a precision scanning microphotometer in 70 s, and to reduce these data to the peak and background transmittances, the location, and a profile code of as many as 500 analytical lines. The plate emulsion is calibrated in 10 equal segments between 2300 and 4700 Å. Intensities and preliminary concentrations based on prestored analytical curve coefficients are calculated for each line. Corrections for spectral interferences are made, and final results are selected according to a predetermined priority scheme. A report form for every 10 samples is printed within 5 min after a plate is recorded. All the preliminary data are stored on magnetic tape for production of microfiche within 24 h. Spectra on a second plate can be scanned while analysis of the first plate is being performed.

scholarly journals A Self-contained and Self-explanatory DNA Storage System

2021 ◽  
Author(s):  
Min Li ◽  
Junbiao Dai ◽  
Qingshan Jiang ◽  
Yang Wang
Keyword(s):  
Data Storage ◽  
Storage System ◽  
Data File ◽  
Data Redundancy ◽  
Dna Storage ◽  
Data Restoration ◽  
Gene Data ◽  
High Uncertainty ◽  
Term Data

Abstract Current research on DNA storage usually focuses on the improvement of storage density with reduced gene synthesis cost by developing effective encoding and decoding schemes while lacking the consideration on the uncertainty in ultra long-term data storage and retention. Consequently, the current DNA storage systems are often not self-containment, implying that they have to resort to external tools for the restoration of the stored gene data. This may result in high risks in data loss since the required tools might not be available due to the high uncertainty in far future. To address this issue, we propose in this paper a self-contained DNA storage system that can make self-explanatory to its stored data without relying on any external tools. To this end, we design a specific DNA file format whereby a separate storage scheme is developed to reduce the data redundancy while an effective indexing is designed for random read operations to the stored data file. We verified through experimental data that the proposed self-contained and self-explanatory method can not only get rid of the reliance on external tools for data restoration but also minimize the data redundancy brought about when the amount of data to be stored reaches a certain scale.

scholarly journals An agenda-setting paper on data sharing platforms: euCanSHare workshop

2021 ◽  
Vol 1 ◽  
pp. 80
Author(s):  
Thijs Devriendt ◽  
Clemens Ammann ◽  
Folkert W. Asselbergs ◽  
Alexander Bernier ◽  
Rodrigo Costas ◽  
...  
Keyword(s):  
Data Sharing ◽  
Data Storage ◽  
Agenda Setting ◽  
Research Agenda ◽  
Data Access ◽  
Medical Data ◽  
Future Research ◽  
Future Research Agenda ◽  
Optimal Functioning

Various data sharing platforms are being developed to enhance the sharing of cohort data by addressing the fragmented state of data storage and access systems. However, policy challenges in several domains remain unresolved. The euCanSHare workshop was organized to identify and discuss these challenges and to set the future research agenda. Concerns over the multiplicity and long-term sustainability of platforms, lack of resources, access of commercial parties to medical data, credit and recognition mechanisms in academia and the organization of data access committees are outlined. Within these areas, solutions need to be devised to ensure an optimal functioning of platforms.

A new opportunity for the emerging tellurium semiconductor: resistive switching device implementation

2021 ◽  
Author(s):  
Yifei Yang ◽  
Mingkun Xu ◽  
Lujie Xu ◽  
Xinxin Wang ◽  
Huan Liu ◽  
...  
Keyword(s):  
Data Storage ◽  
Resistive Switching ◽  
High Performance ◽  
Visual Recognition ◽  
Stimulus Frequency ◽  
Dielectric Materials ◽  
Cross Point ◽  
Electrochemically Active ◽  
Event Based

Abstract The electrochemical (EC) resistive switching (RS) cross-point arrays, composed of nonvolatile RS (NV-RS) memories and volatile RS (V-RS) selectors, hold promise for high-density data storage, in-memory computing and neuromorphic computing. However, the conventional EC-RS devices based on metallic filaments suffer from the notorious current-volatility dilemma that the low and high current requirements for NV-RS memories and V-RS selectors, respectively, cannot be satisfied simultaneously, due to the dominant EC nature of the RS. In this work, we demonstrate electrochemically active, low thermal-conductivity and low melting-temperature semiconducting tellurium filament-based RS devices that solve this dilemma, enabling NV-RS memories to operate under lower currents than do V-RS selectors. This novel phenomenon arises as the consequence of the adversarial EC and Joule heating (JH) effects. The devices also show unusual stimulus frequency dependent long-term plasticity (LTP)-to-short-term plasticity (STP) transition. Devices with this property can be generically utilized as spatial-temporal filters in spiking neural networks (SNNs) for high-performance event-based visual recognition tasks, as illustrated in our noise filtering simulations. By regulating the EC-JH relationship using dielectric materials with decreasing thermal conductivities, full functional-range tunable Te filament-based devices, from always-NV RS, to NV-to-V transitionable RS, and to always-V RS, are also demonstrated. The tellurium filament-based RS devices are promising enablers for functional cross-point arrays.

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