Linked Open Government Data Analytics

Kalampokis, Evangelos; Tambouris, Efthimios; Tarabanis, Konstantinos

doi:10.1007/978-3-642-40358-3_9

Cited by 34 publications

(34 citation statements)

References 16 publications

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“…Shadbolt et al [2] described a project for integrating CSV data and spreadsheet data published on the U.K. data catalog site in the Web of Linked Data. Kalampokis et al [9] asserted that the real value of OGD comes from performing data analytics on top of combined datasets from different sources. As a test case, they used various published datasets including the unemployment rate dataset published in spreadsheet form on data.gov.uk and datasets regarding the outcome of UK general elections published in spreadsheet form on the Guardian newspaper's web site under an open license.…”

Section: Related Workmentioning

confidence: 99%

Crowdsourcing chart digitizer: task design and quality control for making legacy open data machine-readable

Oyama

Baba

Ohmukai

et al. 2016

Int J Data Sci Anal

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Despite recent open data initiatives in many countries, a significant percentage of the data provided is in non-machine-readable formats like image format rather than in a machine-readable electronic format, thereby restricting their usability. Various types of software for digitizing data chart images have been developed. However, such software is designed for manual use and thus requires human intervention, making it unsuitable for automatically extracting data from a large number of chart images. This paper describes the first unified framework for converting legacy open data in chart images into a machine-readable and reusable format by using crowdsourcing. Crowd workers are asked not only to extract data from an image of a chart but also to reproduce the chart objects in a spreadsheet. The properties of the reproduced chart objects give their data structures, including series names and values, which are useful for automatic processing of data by computer. Since results produced by crowdsourcing inherently contain errors, a quality control mechanism This paper is an extended version of the DSAA 2015 long presentation paper "From One Star to Three Stars: Upgrading Legacy Open Data Using Crowdsourcing" [1].

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Section: Related Workmentioning

confidence: 99%

Crowdsourcing chart digitizer: task design and quality control for making legacy open data machine-readable

Oyama

Baba

Ohmukai

et al. 2016

Int J Data Sci Anal

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“…More specifically, the following appointments were made per area:  Open data: 6 . The interviews along with the relevant literature resulted in the series of consecutive steps that structure the linked data cube process presented in section 5.…”

Section: Approachmentioning

confidence: 99%

“…In the case of statistical data, linked data has the potential to create value to society, enterprises, and public administration through combining statistics from various sources and performing analytics on top of integrated statistical data [6] [7].…”

Section: Introductionmentioning

confidence: 99%

Processing Linked Open Data Cubes

Tambouris

Kalampokis

Tarabanis

2015

Lecture Notes in Computer Science

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Part 2: Open and Smart GovernmentInternational audienceA significant part of open data provided by governments and international organizations concerns statistics such as demographics and economic indicators. The real value, however, of open statistical data will unveil from performing analytics on top of combined datasets from disparate sources. Linked data provide the most promising technological paradigm to enable such analytics across the Web. Currently, however, relevant processes and tools do not fully exploit the distinctive characteristics of statistical data. The aim of this paper is to present a process that enables publishing statistical raw data as linked data, combining statistics from multiple sources, and exploiting them in data analytics and visualizations. Moreover, the capability of existing software tools to support the vision of linked statistical data analytics is evaluated. We anticipate that the proposed process will contribute to the development of a roadmap for future research and development in the area

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“…Users define the relationships between the columns of a spreadsheet [7] asserted that the real value of OGD comes from performing data analytics on top of combined datasets from different sources. As a test case, they used various published datasets including the unemployment rate dataset published in spreadsheet form on data.gov.uk and datasets regarding the outcome of UK general elections published in spreadsheet form on the Guardian newspaper's web site under an open license.…”

Section: Related Workmentioning

confidence: 99%

From one star to three stars: Upgrading legacy open data using crowdsourcing

Oyama

Baba

Ohmukai

et al. 2015

2015 IEEE International Conference on Data Science and Advanced Analytics (DSAA)

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Abstract-Despite recent open data initiatives in many countries, a significant percentage of the data provided is in nonmachine-readable formats like image format rather than in a machine-readable electronic format, thereby restricting their usability. This paper describes the first unified framework for converting legacy open data in image format into a machinereadable and reusable format by using crowdsourcing. Crowd workers are asked not only to extract data from an image of a chart but also to reproduce the chart objects in spreadsheets. The properties of the reconstructed chart objects give their data structures including series names and values, which are useful for automatic processing of data by computer. Since results produced by crowdsourcing inherently contain errors, a quality control mechanism was developed that improves the accuracy of extracted tables by aggregating tables created by different workers for the same chart image and by utilizing the data structures obtained from the reproduced chart objects. Experimental results demonstrated that the proposed framework and mechanism are effective.

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Linked Open Government Data Analytics

Cited by 34 publications

References 16 publications

Crowdsourcing chart digitizer: task design and quality control for making legacy open data machine-readable

Crowdsourcing chart digitizer: task design and quality control for making legacy open data machine-readable

Processing Linked Open Data Cubes

From one star to three stars: Upgrading legacy open data using crowdsourcing

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