Application of tools to support Linked Open Data

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Sujan Saha ◽  
Sukumar Mandal
Keyword(s):  
Data Storage ◽  
Linked Data ◽  
Storage System ◽  
Open Data ◽  
Large Data ◽  
Third Party ◽  
Bibliographic Databases ◽  
Data Sets ◽  
Content Type ◽  
Authority Control

Purpose These projects aim to improve library services for users in the future by combining Link Open Data (LOD) technology with data visualization. It displays and analyses search results in an intuitive manner. These services are enhanced by integrating various LOD technologies into the authority control system. Design/methodology/approach The technology known as LOD is used to access, recycle, share, exchange and disseminate information, among other things. The applicability of Linked Data technologies for the development of library information services is evaluated in this study. Findings Apache Hadoop is used for rapidly storing and processing massive Linked Data data sets. Apache Spark is a free and open-source data processing tool. Hive is a SQL-based data warehouse that enables data scientists to write, read and manage petabytes of data. Originality/value The distributed large data storage system Apache HBase does not use SQL. This study’s goal is to search the geographic, authority and bibliographic databases for relevant links found on various websites. When data items are linked together, all of the data bits are linked together as well. The study observed and evaluated the tools and processes and recorded each data item’s URL. As a result, data can be combined across silos, enhanced by third-party data sources and contextualized.

Design of FPGA-Based Missile-Borne Image Acquisition and Storage Recorder

2015 ◽  
Vol 713-715 ◽  
pp. 1448-1451
Author(s):  
Lin Lu ◽  
Yan Feng Zhang ◽  
Xiao Feng Li
Keyword(s):  
Real Time ◽  
Data Storage ◽  
Storage System ◽  
Large Data ◽  
Engineering Practice ◽  
Image Storage ◽  
Video Images ◽  
Stable Performance ◽  
And Storage ◽  
Time Image

The high-altitude missile and other special application occasions have requirements on image storage system, such as small size, high storage speed, low temperature resistance, etc. Commonly used image storage system in the market cannot meet such requirement. In the paper, real-time image storage system solutions on missile based on FPGA should be proposed. The system mainly consists of acquisition module and memory reading module. The whole system adopts FPGA as main control chip for mainly completing real-time decoding and acquisition on one path of PAL format video images, reading and writing of NandFlash chipset, erasure, bad block management and so on. The solution has passed various environmental tests with stable performance, large data storage capacity and easy expansion, which has been used in engineering practice.

Enhancing transparency through open government data: the case of data portals and their features and capabilities

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Martin Lněnička ◽  
Renata Machova ◽  
Jolana Volejníková ◽  
Veronika Linhartová ◽  
Radka Knezackova ◽  
...  
Keyword(s):  
Open Data ◽  
Open Government ◽  
Data Sets ◽  
Web Content ◽  
Content Type ◽  
Domain Experts ◽  
Computer Mediated ◽  
Open Government Data ◽  
Decision Making Processes ◽  
Government Data

PurposeThe purpose of this paper was to draw on evidence from computer-mediated transparency and examine the argument that open government data and national data infrastructures represented by open data portals can help in enhancing transparency by providing various relevant features and capabilities for stakeholders' interactions.Design/methodology/approachThe developed methodology consisted of a two-step strategy to investigate research questions. First, a web content analysis was conducted to identify the most common features and capabilities provided by existing national open data portals. The second step involved performing the Delphi process by surveying domain experts to measure the diversity of their opinions on this topic.FindingsIdentified features and capabilities were classified into categories and ranked according to their importance. By formalizing these feature-related transparency mechanisms through which stakeholders work with data sets we provided recommendations on how to incorporate them into designing and developing open data portals.Social implicationsThe creation of appropriate open data portals aims to fulfil the principles of open government and enables stakeholders to effectively engage in the policy and decision-making processes.Originality/valueBy analyzing existing national open data portals and validating the feature-related transparency mechanisms, this paper fills this gap in existing literature on designing and developing open data portals for transparency efforts.

Asymmetric Open Government Data (OGD) framework in India

2018 ◽  
Vol 20 (5) ◽  
pp. 434-448 ◽  
Author(s):  
Stuti Saxena
Keyword(s):  
Economic Value ◽  
Open Data ◽  
Developed Countries ◽  
Open Government ◽  
Data Sets ◽  
Indian States ◽  
Content Type ◽  
Open Government Data ◽  
Government Data ◽  
The Government

Purpose With the ongoing drives towards Open Government Data (OGD) initiatives across the globe, governments have been keen on pursuing their OGD policies to ensure transparency, collaboration and efficiency in administration. As a developing country, India has recently adopted the OGD policy (www.data.gov.in); however, the percolation of this policy in the States has remained slow. This paper aims to underpin the “asymmetry” in OGD framework as far as the Indian States are concerned. Besides, the study also assesses the contribution of “Open Citizens” in furthering the OGD initiatives of the country. Design/methodology/approach An exploratory qualitative following a case study approach informs the present study using documentary analysis where evidentiary support from five Indian States (Uttar Pradesh, Telangana, West Bengal, Sikkim and Gujarat) is being drawn to assess the nature and scope of the OGD framework. Further, conceptualization for “Open Citizen” framework is provided to emphasize upon the need to have aware, informed and pro-active citizens to spearhead the OGD initiatives in the country. Findings While the National OGD portal has a substantial number of data sets across different sectors, the States are lagging behind in the adoption and implementation of OGD policies, and while Telangana and Sikkim have been the frontrunners in adoption of OGD policies in a rudimentary manner, others are yet to catch up with them. Further, there is “asymmetry” in terms of the individual contribution of the government bodies to the open data sets where some government bodies are more reluctant to share their datasets than the others. Practical implications It is the conclusion of the study that governments need to institutionalize the OGD framework in the country, and all the States should appreciate the requirement of adopting a robust OGD policy for furthering transparency, collaboration and efficiency in administration. Social implications As an “Open Citizen”, it behooves upon the citizens to be pro-active and contribute towards the open data sets which would go a long way in deriving social and economic value out of these data sets. Originality/value While there are many studies on OGD in the West, studies focused upon the developing countries are starkly lacking. This study plugs this gap by attempting a comparative analysis of the OGD frameworks across Indian States. Besides, the study has provided a conceptualization of “Open Citizen” (OGD) which may be tapped for further research in developing and developed countries to ascertain the linkage between OGD and OC.

Academic social networks and collaboration patterns

2019 ◽  
Vol 38 (2) ◽  
pp. 293-307
Author(s):  
Po-Yen Chen
Keyword(s):  
Social Networks ◽  
Data Collection ◽  
Research Collaboration ◽  
Open Data ◽  
Data Sets ◽  
Content Type ◽  
Open Government Data ◽  
Collaboration Patterns ◽  
Academic Social Networks ◽  
Government Data

Purpose This study attempts to use a new source of data collection from open government data sets to identify potential academic social networks (ASNs) and defines their collaboration patterns. The purpose of this paper is to propose a direction that may advance our current understanding on how or why ASNs are formed or motivated and influence their research collaboration. Design/methodology/approach This study first reviews the open data sets in Taiwan, which is ranked as the first state in Global Open Data Index published by Open Knowledge Foundation to select the data sets that expose the government’s R&D activities. Then, based on the theory review of research collaboration, potential ASNs in those data sets are identified and are further generalized as various collaboration patterns. A research collaboration framework is used to present these patterns. Findings Project-based social networks, learning-based social networks and institution-based social networks are identified and linked to various collaboration patterns. Their collaboration mechanisms, e.g., team composition, motivation, relationship, measurement, and benefit-cost, are also discussed and compared. Originality/value In traditional, ASNs have usually been known as co-authorship networks or co-inventorship networks due to the limitation of data collection. This study first identifies some ASNs that may be formed before co-authorship networks or co-inventorship networks are formally built-up, and may influence the outcomes of research collaborations. These information allow researchers to deeply dive into the structure of ASNs and resolve collaboration mechanisms.

An Unsupervised Approach for Determining Link Specifications

2018 ◽  
Vol 13 (4) ◽  
pp. 104-123
Author(s):  
Khayra Bencherif ◽  
Mimoun Malki ◽  
Djamel Amar Bensaber
Keyword(s):  
Linked Data ◽  
Open Data ◽  
Real Data ◽  
Knowledge Bases ◽  
Structured Data ◽  
Data Sets ◽  
Novel Approach ◽  
Link Discovery ◽  
Unsupervised Approach

This article describes how the Linked Open Data Cloud project allows data providers to publish structured data on the web according to the Linked Data principles. In this context, several link discovery frameworks have been developed for connecting entities contained in knowledge bases. In order to achieve a high effectiveness for the link discovery task, a suitable link configuration is required to specify the similarity conditions. Unfortunately, such configurations are specified manually; which makes the link discovery task tedious and more difficult for the users. In this article, the authors address this drawback by proposing a novel approach for the automatic determination of link specifications. The proposed approach is based on a neural network model to combine a set of existing metrics into a compound one. The authors evaluate the effectiveness of the proposed approach in three experiments using real data sets from the LOD Cloud. In addition, the proposed approach is compared against link specifications approaches to show that it outperforms them in most experiments.

scholarly journals Practical Constraint K-Segment Principal Curve Algorithms for Generating Railway GPS Digital Map

2013 ◽  
Vol 2013 ◽  
pp. 1-11
Author(s):  
Dewang Chen ◽  
Long Chen
Keyword(s):  
Data Storage ◽  
Expert Knowledge ◽  
Low Cost ◽  
Large Data ◽  
Gps Data ◽  
Small Data ◽  
Data Sets ◽  
Digital Map ◽  
Digital Maps ◽  
Practical Algorithms

In order to obtain a decent trade-off between the low-cost, low-accuracy Global Positioning System (GPS) receivers and the requirements of high-precision digital maps for modern railways, using the concept of constraint K-segment principal curves (CKPCS) and the expert knowledge on railways, we propose three practical CKPCS generation algorithms with reduced computational complexity, and thereafter more suitable for engineering applications. The three algorithms are named ALLopt, MPMopt, and DCopt, in which ALLopt exploits global optimization and MPMopt and DCopt apply local optimization with different initial solutions. We compare the three practical algorithms according to their performance on average projection error, stability, and the fitness for simple and complex simulated trajectories with noise data. It is found that ALLopt only works well for simple curves and small data sets. The other two algorithms can work better for complex curves and large data sets. Moreover, MPMopt runs faster than DCopt, but DCopt can work better for some curves with cross points. The three algorithms are also applied in generating GPS digital maps for two railway GPS data sets measured in Qinghai-Tibet Railway (QTR). Similar results like the ones in synthetic data are obtained. Because the trajectory of a railway is relatively simple and straight, we conclude that MPMopt works best according to the comprehensive considerations on the speed of computation and the quality of generated CKPCS. MPMopt can be used to obtain some key points to represent a large amount of GPS data. Hence, it can greatly reduce the data storage requirements and increase the positioning speed for real-time digital map applications.

Semantically Enriched Task and Workflow Automation in Crowdsourcing for Linked Data Management

2014 ◽  
Vol 08 (04) ◽  
pp. 415-439 ◽  
Author(s):  
Amna Basharat ◽  
I. Budak Arpinar ◽  
Shima Dastgheib ◽  
Ugur Kursuncu ◽  
Krys Kochut ◽  
...  
Keyword(s):  
Data Management ◽  
Linked Data ◽  
Critical Role ◽  
Workflow Management ◽  
Open Data ◽  
Control Flow ◽  
Human Computation ◽  
Amazon Mechanical Turk ◽  
Data Sets ◽  
Task Specification

Crowdsourcing is one of the new emerging paradigms to exploit the notion of human-computation for harvesting and processing complex heterogenous data to produce insight and actionable knowledge. Crowdsourcing is task-oriented, and hence specification and management of not only tasks, but also workflows should play a critical role. Crowdsourcing research can still be considered in its infancy. Significant need is felt for crowdsourcing applications to be equipped with well defined task and workflow specifications ranging from simple human-intelligent tasks to more sophisticated and cooperative tasks to handle data and control-flow among these tasks. Addressing this need, we have attempted to devise a generic, flexible and extensible task specification and workflow management mechanism in crowdsourcing. We have contextualized this problem to linked data management as our domain of interest. More specifically, we develop CrowdLink, which utilizes an architecture for automated task specification, generation, publishing and reviewing to engage crowdworkers for verification and creation of triples in the Linked Open Data (LOD) cloud. The LOD incorporates various core data sets in the semantic web, yet is not in full conformance with the guidelines for publishing high quality linked data on the web. Our approach is not only useful in efficiently processing the LOD management tasks, it can also help in enriching and improving quality of mission-critical links in the LOD. We demonstrate usefulness of our approach through various link creation and verification tasks, and workflows using Amazon Mechanical Turk. Experimental evaluation demonstrates promising results not only in terms of ease of task generation, publishing and reviewing, but also in terms of accuracy of the links created, and verified by the crowdworkers.

Consuming and producing linked open data: the case of OpenCourseWare

2014 ◽  
Vol 48 (1) ◽  
pp. 16-40 ◽  
Author(s):  
Nelson Piedra ◽  
Edmundo Tovar ◽  
Ricardo Colomo-Palacios ◽  
Jorge Lopez-Vargas ◽  
Janneth Alexandra Chicaiza
Keyword(s):  
Linked Data ◽  
Design Methodology ◽  
Open Data ◽  
Linked Open Data ◽  
Open Learning ◽  
Content Type ◽  
Educational Contents ◽  
Initial Framework

Purpose – The aim of this paper is to present an initiative to apply the principles of Linked Data to enhance the search and discovery of OpenCourseWare (OCW) contents created and shared by the universities. Design/methodology/approach – This paper is a case study of how linked data technologies can be applied for the enhancement of open learning contents. Findings – Results presented under the umbrella of OCW-Universia consortium, as the integration and access to content from different repositories OCW and the development of a query method to access these data, reveal that linked data would offer a solution to filter and select semantically those open educational contents, and automatically are linked to the linked open data cloud. Originality/value – The new OCW-Universia integration with linked data adds new features to the initial framework including improved query mechanisms and interoperability.

Enabling and integrating ETD repositories through linked data

2014 ◽  
Vol 35 (4/5) ◽  
pp. 284-292 ◽  
Author(s):  
Lucas Mak ◽  
Devin Higgins ◽  
Aaron Collie ◽  
Shawn Nicholson
Keyword(s):  
Linked Data ◽  
Data Sets ◽  
General Applicability ◽  
Institutional Assessment ◽  
Content Type ◽  
Data Architecture ◽  
New Perspective ◽  
Data Elements ◽  
Model Formation ◽  
Institutional Relationships

Purpose – The purpose of this paper is to illustrate that Electronic Theses and Dissertation (ETD) metadata can be used as data for institutional assessment and to map an extended research landscape when connected to other data sets through linked data models. Design/methodology/approach – This paper presents conceptual consideration of ideas behind linked data architecture to leverage ETD and attendant metadata to build a case for institutional assessment. Analysis of graph data support the considerations. Findings – The study reveals first and foremost that ETD metadata is in itself data. Concerns with creating URIs for data elements and general applicability of linked data model formation result. The analysis positively points up a rich environment of institutional relationships not readily found in traditional flat metadata records. Originality/value – This paper provides a new perspective in examining research landscape through ETDs produced by graduate students in higher education sector.

scholarly journals Blind Queries Applied to JSON Document Stores

Information ◽  
2019 ◽  
Vol 10 (10) ◽  
pp. 291 ◽  
Author(s):  
Stefania Marrara ◽  
Mauro Pelucchi ◽  
Giuseppe Psaila
Keyword(s):  
Real Life ◽  
Open Data ◽  
Large Data ◽  
General Information ◽  
Data Sets ◽  
Heterogeneous Structure ◽  
Data Set ◽  
Document Database ◽  
Job Vacancy ◽  
Document Stores

Social Media, Web Portals and, in general, information systems offer their own Application Programming Interfaces (APIs), used to provide large data sets concerning every aspect of day-by-day life. APIs usually provide data sets as collections of JSON documents. The heterogeneous structure of JSON documents returned by different APIs constitutes a barrier to effectively query and analyze these data sets. The adoption of NoSQL document stores, such as MongoDB, is useful for gathering these data sets, but does not solve the problem of querying the final heterogeneous repository. The aim of this paper is to provide analysts with a tool, named HammerJDB, that allows for blind querying collections of JSON documents within a NoSQL document database. The idea below is that users may know the application domain but it may be that they are not aware of the real structures of the documents stored in the database—the tool for blind querying tries to bridge the gap, by adopting a query rewriting mechanism. This paper is an evolution of a technique for blind querying Open Data portals and of its implementation within the Hammer framework, presented in some previous work. In this paper, we evolve that approach in order to query a NoSQL document database by evolving the Hammer framework into the HammerJDB framework, which is able to work on MongoDB databases. The effectiveness of the new approach is evaluated on a data set (derived from a real-life one), containing job-vacancy ads collected from European job portals.

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