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Article
Publication date: 20 March 2017

David Stuart Holmes Rosenthal

Increasingly, the content that libraries collect is no longer on paper, a long-lived, medium whose technology changes very slowly and with which they have centuries of…

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1869

Abstract

Purpose

Increasingly, the content that libraries collect is no longer on paper, a long-lived, medium whose technology changes very slowly and with which they have centuries of experience. Instead, it is stored on relatively short-lived digital media whose technology appears to change rapidly and with which they have little history. The paper aims to discuss this issue.

Design/methodology/approach

The storage media industry is highly competitive and is currently evolving rapidly as flash, a solid state medium, displaces spinning disk from many applications. Long-term archival storage is a small part of the total storage market. It typically re-uses media and systems intended for more general bulk storage.

Findings

What are the medium-term prospects for change in this market?

Originality/value

Much of this material has appeared in blog posts and talks aimed at storage experts, such as the recent DARPA workshop on future of storage. It is presented here for a librarian audience with the necessary additional exposition and background.

Details

Library Hi Tech, vol. 35 no. 1
Type: Research Article
ISSN: 0737-8831

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Article
Publication date: 29 January 2018

Wasim Ahmad Bhat

The purpose of this paper is to investigate the prospects of current storage technologies for long-term preservation of big data in digital libraries.

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2282

Abstract

Purpose

The purpose of this paper is to investigate the prospects of current storage technologies for long-term preservation of big data in digital libraries.

Design/methodology/approach

The study employs a systematic and critical review of the relevant literature to explore the prospects of current storage technologies for long-term preservation of big data in digital libraries. Online computer databases were searched to identify the relevant literature published between 2000 and 2016. A specific inclusion and exclusion criterion was formulated and applied in two distinct rounds to determine the most relevant papers.

Findings

The study concludes that the current storage technologies are not viable for long-term preservation of big data in digital libraries. They can neither fulfil all the storage demands nor alleviate the financial expenditures of digital libraries. The study also points out that migrating to emerging storage technologies in digital libraries is a long-term viable solution.

Research limitations/implications

The study suggests that continuous innovation and research efforts in current storage technologies are required to lessen the impact of storage shortage on digital libraries, and to allow emerging storage technologies to advance further and take over. At the same time, more aggressive research and development efforts are required by academics and industry to further advance the emerging storage technologies for their timely and swift adoption by digital libraries.

Practical implications

The study reveals that digital libraries, besides incurring significant financial expenditures, will suffer from potential loss of information due to storage shortage for long-term preservation of big data, if current storage technologies are employed by them. Therefore, policy makers and practitioners should meticulously choose storage technologies for long-term preservation of big data in digital libraries.

Originality/value

This type of holistic study that investigates the prospects of magnetic drive technology, solid-state drive technology, and data-reduction techniques for long-term preservation of big data in digital libraries has not been conducted in the field previously, and so provides a novel contribution. The study arms academics, practitioners, policy makers, and industry with the deep understanding of the problem, technical details to choose storage technologies meticulously, greater insight to frame sustainable policies, and opportunities to address various research problems.

Details

Library Hi Tech, vol. 36 no. 3
Type: Research Article
ISSN: 0737-8831

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Article
Publication date: 15 June 2015

Yan Han

The purpose of this paper is to use cloud storage in digital preservation by analyzing the pricing and data retrieval models. The author recommends strategies to minimize…

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2791

Abstract

Purpose

The purpose of this paper is to use cloud storage in digital preservation by analyzing the pricing and data retrieval models. The author recommends strategies to minimize the costs and believes cloud storage is worthy of serious consideration.

Design/methodology/approach

Few articles have been published to show the uses of cloud storage in libraries. The cost is the main concern. An overview of cloud storage pricing shows a price drop once every one or one-and-a-half years. The author emphasize the data transfer-out costs and demonstrate a case study. Comparisons and analysis of S3 and Glacier have been conducted to show the differences in retrieval and costs.

Findings

Cloud storage solutions like Glacier can be very attractive for long-term digital preservation if data can be operated within the provider’s same data zone and data transfer-out can be minimized.

Practical implications

Institutions can benefit from cloud storage by understanding the cost models and data retrieval models. Multiple strategies are suggested to minimize the costs.

Originality/value

The paper is intended to bridge the gap of uses of cloud storage. Cloud storage pricing especially data transfer-out pricing charts are presented to show the price drops over the past eight years. Costs and analysis of storing and retrieving data in Amazon S3 and Glacier are discussed in details. Comparisons of S3 and Glacier show that Glacier has uniqueness and advantages over other cloud storage solutions. Finally strategies are suggested to minimize the costs of using cloud storage. The analysis shows that cloud storage can be very useful in digital preservation.

Details

Library Hi Tech, vol. 33 no. 2
Type: Research Article
ISSN: 0737-8831

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Article
Publication date: 11 January 2013

Gursans Guven and Esin Ergen

The main purpose of this study is to present an overview of the state of the art of the RFID technology in terms of data storage approaches in construction cases, and to…

Abstract

Purpose

The main purpose of this study is to present an overview of the state of the art of the RFID technology in terms of data storage approaches in construction cases, and to identify the factors that require different approaches to data storage (e.g. on tags or on a remote database) in RFID applications in the construction industry.

Design/methodology/approach

A literature survey was conducted and the contexts of 37 construction industry cases were investigated to determine the factors that affect the decision of data storage approach and the types of information groups that were stored in each case. Additionally, 79 cases were reviewed from other industries to provide insights.

Findings

The literature review showed that, many cases in the construction industry preferred storing additional data on RFID tags such as identification, technical and historical information. The factors affecting the selection of data storage approach in RFID applications were identified: application environment, cost efficiency, multiple number of parties, need for monitoring up‐to‐date progress data, collecting environmental conditions, in situ (on‐board) data storage, industry‐related specifications, and reading range requirement.

Practical implications

The high proportion of cases which stored data on tags demonstrate that there is a need for tags/storage media that are specially designed for the construction industry because most tags currently have either minimum or limited memories.

Originality/value

The analysis of the investigated cases and the factors that were identified to be affecting the data storage approach decision making can assist construction practitioners and owners in selecting an appropriate data storage approach for their projects.

Details

Construction Innovation, vol. 13 no. 1
Type: Research Article
ISSN: 1471-4175

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Article
Publication date: 31 December 2006

Mu‐Huan Chiang and Gregory T. Byrd

Data‐centric storage is an efficient scheme to store and retrieve event data in sensor networks, but with the multi‐hop routing nature of sensor networks, the…

Abstract

Data‐centric storage is an efficient scheme to store and retrieve event data in sensor networks, but with the multi‐hop routing nature of sensor networks, the communication cost of the home nodes and their neighboring nodes tends to be much higher than the other nodes. These hot‐spots can adversely impact system lifetime by draining off their limited energy rapidly. In this paper, we present Zone‐Repartitioning, a load‐balancing mechanism that reduces the energy consumption of the hot‐spots by distributing their communication load while event frequency is high. The trade‐off between event storage cost and query cost makes Zone Repartitioning a competitive approach in different kinds of applications. We compare the performance of Zone Repartitioning against GHT and show that Zone Repartitioning provides better adaptability in various sensor network scenarios.

Details

International Journal of Pervasive Computing and Communications, vol. 2 no. 4
Type: Research Article
ISSN: 1742-7371

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Article
Publication date: 30 August 2011

Hannes Mühleisen, Tilman Walther and Robert Tolksdorf

The purpose of this paper is to show the potential of self‐organized semantic storage services. The semantic web has provided a vision of how to build the applications of…

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1315

Abstract

Purpose

The purpose of this paper is to show the potential of self‐organized semantic storage services. The semantic web has provided a vision of how to build the applications of the future. A software component dedicated to the storage and retrieval of semantic information is an important but generic part of these applications. Apart from mere functionality, these storage components also have to provide good performance regarding the non‐functional requirements scalability, adaptability and robustness. Distributing the task of storing and querying semantic information onto multiple computers is a way of achieving this performance. However, the distribution of a task onto a set of computers connected using a communication network is not trivial. One solution is self‐organized technologies, where no central entity coordinates the system's operation.

Design/methodology/approach

Based on the available literature on large‐scale semantic storage systems, the paper analyzes the underlying distribution algorithm, with special focus on the properties of semantic information and corresponding queries. The paper compares the approaches and identify their shortcomings.

Findings

All analyzed approaches and their underlying technologies were unable to distribute large amounts of semantic information and queries in a generic way while still being able to react on changing network infrastructure. Nonetheless, as each concept represented a unique trade‐off between these goals, the paper points out how self‐organization is crucial to perform well at least in a subset of them.

Originality/value

The contribution of this paper is a literature review aimed at showing the potential of self‐organized semantic storage services. A case is made for self‐organization in a distributed storage system as the key to excellence in the relevant non‐functional requirements: scalability, adaptability and robustness.

Details

International Journal of Web Information Systems, vol. 7 no. 3
Type: Research Article
ISSN: 1744-0084

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Article
Publication date: 19 October 2015

Wasim Ahmad Bhat and S.M.K. Quadri

The purpose of this paper is to explore the challenges posed by Big Data to current trends in computation, networking and storage technology at various stages of Big Data

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3072

Abstract

Purpose

The purpose of this paper is to explore the challenges posed by Big Data to current trends in computation, networking and storage technology at various stages of Big Data analysis. The work aims to bridge the gap between theory and practice, and highlight the areas of potential research.

Design/methodology/approach

The study employs a systematic and critical review of the relevant literature to explore the challenges posed by Big Data to hardware technology, and assess the worthiness of hardware technology at various stages of Big Data analysis. Online computer-databases were searched to identify the literature relevant to: Big Data requirements and challenges; and evolution and current trends of hardware technology.

Findings

The findings reveal that even though current hardware technology has not evolved with the motivation to support Big Data analysis, it significantly supports Big Data analysis at all stages. However, they also point toward some important shortcomings and challenges of current technology trends. These include: lack of intelligent Big Data sources; need for scalable real-time analysis capability; lack of support (in networks) for latency-bound applications; need for necessary augmentation (in network support) for peer-to-peer networks; and rethinking on cost-effective high-performance storage subsystem.

Research limitations/implications

The study suggests that a lot of research is yet to be done in hardware technology, if full potential of Big Data is to be unlocked.

Practical implications

The study suggests that practitioners need to meticulously choose the hardware infrastructure for Big Data considering the limitations of technology.

Originality/value

This research arms industry, enterprises and organizations with the concise and comprehensive technical-knowledge about the capability of current hardware technology trends in solving Big Data problems. It also highlights the areas of potential research and immediate attention which researchers can exploit to explore new ideas and existing practices.

Details

Industrial Management & Data Systems, vol. 115 no. 9
Type: Research Article
ISSN: 0263-5577

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Article
Publication date: 1 January 1987

Alison Jameson

Downloading and uploading offer labour‐saving advantages and are now accepted as useful options in online searching. All aspects are here considered, from recent technical…

Abstract

Downloading and uploading offer labour‐saving advantages and are now accepted as useful options in online searching. All aspects are here considered, from recent technical advances, applications and legal attitudes. There is also a review of current software for downloading. Recent developments mean a trend to higher internal memory and storage capacity, and greater transmission speeds. Packages now offer access to more than one host, give maximum assistance to the user without being menu‐driven and incorporate the latest developments in artificial intelligence. Disadvantages are in the length of time involved in the process and the fact that the legal issue of copyright has not yet been finalised. Database producers have turned to licensing under contract law, but there is still need to rely on user ethics, and the need for a standard permissions form is highlighted.

Details

Library Management, vol. 8 no. 1
Type: Research Article
ISSN: 0143-5124

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Article
Publication date: 1 July 2003

Zhou ke, Zhang Jiangling and Feng Dan

When the controller of a storage system becomes more and more powerful, it sometimes creates new data and stores this data in the system, just like parity information in…

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1081

Abstract

When the controller of a storage system becomes more and more powerful, it sometimes creates new data and stores this data in the system, just like parity information in RAID level 5. We call these phenomena data self‐create. This paper provides a theory about data self‐create which separates data self‐create phenomena into 16 kinds. Three applications are introduced. From a pansystems view, this paper also gives an explanation of data self‐create.

Details

Kybernetes, vol. 32 no. 5/6
Type: Research Article
ISSN: 0368-492X

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Article
Publication date: 18 January 2021

Fatimah Jibril Abduldayan, Fasola Petunola Abifarin, Georgina Uchey Oyedum and Jibril Attahiru Alhassan

The purpose of this study was to understand the research data management practices of chemistry researchers in the five specialized federal universities of technology in…

Abstract

Purpose

The purpose of this study was to understand the research data management practices of chemistry researchers in the five specialized federal universities of technology in Nigeria. Appropriate research data management practice ensures that research data are available for reuse by secondary users, and research findings can be verified and replicated within the scientific community. A poor research data management practice can lead to irrecoverable data loss, unavailability of data to support research findings and lack of trust in the research process.

Design/methodology/approach

An exploratory research technique involving semi-structured, oral and face-to-face interview is used to gather data on research data management practices of chemistry researchers in Nigeria. Interview questions were divided into four major sections covering chemistry researchers’ understanding of research data, experience with data loss, data storage method and backup techniques, data protection, data preservation and availability of data management plan. Braun and Clarke thematic analysis approach was adapted, and the Provalis Qualitative Data Miner (version 5) software was used for generating themes and subthemes from the coding framework and for presenting the findings.

Findings

Findings revealed that chemistry researchers in Nigeria have a good understanding of the concept of research data and its importance to research findings. Chemistry researchers have had several experiences of irrecoverable loss of data because of poor choice of storage devices, back-up methods and weak data protection systems. Even though the library was agreed as the most preferred place for long-term data preservation, there is the issue of trust and fear of loss of ownership of data to unauthorized persons or party. No formal data management plan is used while conducting their scientific research.

Research limitations/implications

The research focused on research data management practices of chemistry researchers in the five specialized federal universities of technology in Nigeria. Although the findings of the study are similar to perceptions and practices of researchers around the world, it cannot be used as a basis for generalization across other scientific disciplines.

Practical implications

This study concluded that chemistry researchers need further orientation and continuous education on the importance and benefits of appropriate research data management practice. The library should also roll out research data management programs to guide researchers and improve their confidence throughout the research process.

Social implications

Appropriate research data management practice not only ensures that the underlying research data are true and available for reuse and re-validation, but it also encourages data sharing among researchers. Data sharing will help to ensure better collaboration among researchers and increased visibility of the datasets and data owners through the use of standard data citations and acknowledgements.

Originality/value

This is a qualitative and in-depth study of research data management practices and perceptions among researchers in a particular scientific field of study.

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