Linked open data statistics: Collection and exploitation

2017

An increasing number of governments, organisations and enterprises publish huge amounts of data as open data. The major part of this data concern statistics, e.g. data in the Open Data Portal of the European Commission (open-data.europa.eu). This data has the potential for innovative uses including performing advanced data analytics and visualizations on top of combined data that were previously isolated. From a technological point of view, statistical data can be combined by employing linked open data technologies and, specifically, the W3C RDF Data Cube vocabulary [1]. This has the potential to realise the vision of performing data analytics on top of integrated but previously isolated statistical data across the Web [2] [3]. Although several practical solutions have been developed during the last years for creating and exploiting Linked Open Statistical Data (e.g. [4] [5]), these solutions are mainly technology-driven and are not able to address the complexity and dynamics of pub...

Linked data has been existing in web services since several years. But how efficient we are using it is a key question for our interaction with Internet world. The difficulty to achieve a clear form of published datasets on Web, makes it also hard to have broad benefits and usage of information. In order to reach this aim, variable tools are provided by researches. LODStats is one of the developed approaches in this area, enabling users to gather overall view on the structure, coverage and the coherence of the data[1]. In this paper, the motivation,​ ​ features,​ ​ architecture​ ​ and​ ​ results​ ​ of​ ​ the​ ​ LODStats​ ​ ​ ​ are​ ​ discussed.

Proceedings of the 18th Annual International Conference on Digital Government Research, 2017

Open data have tremendous potential which however remains unexploited. A large part of open data is numerical and highly structured. We concentrate on those data and capitalize on linked open data (LOD) as the underlying technology. In this paper, we present a number of tools to facilitate publishing and reusing of linked open statistical data. We propose an architecture and implementation that allows developing custom visualization and analysis tools without knowledge of LOD technologies. We further present work towards deploying relevant tools in six di erent countries to improve decision-making and transparency and thus support public administration.

To make the Web of Data a reality, and push large scale integration of, and reasoning on, data on the Web, huge amounts of data must be made available in a standard format, reachable and manageable by Semantic Web tools. National statistical offices across the world already possess an abundance of structured data, both in their databases and files in various formats. We will first consider the reasons for making such data available as Linked Data. Then, some novel data representation methods, compatible with SDMX, an international standard for exchanging statistical data, will be showcased. We will then explain how to move from structured statistical data, represented in XML, to RDF, as well as how to enrich such datasets using standard classification schemas. Finally, we will present a way of increasing data visibility through cataloging newly created linked statistical data at both local and international level.

2012

Linked Open Data (LOD) is a growing movement for organizations to make their existing data available in a machinereadable format. There are two equally important viewpoints to LOD: publishing and consuming. This article analyzes the requirements for both sub-processes and presents an example of publishing statistical data in RDF format and integrating the data into the LOD cloud via the PublicData.eu portal. In particular, it discusses the establishment of the Serbian CKAN metadata repository that serves for publishing open governmental data from Serbia, as well as a source catalogue for the PublicData.eu portal. Furthermore, by using an illustrative case study of the Statistical Office of the Republic of Serbia, it elaborates the adaption of the LOD2 Stack for analysis and dissemination of official statistics information.

2015

A major part of open data provided by international and governmental organizations include facts and figures that are described in a multi-dimensional manner (aka data cubes). The real value, however, of these open data cubes will unveil from combining and exploiting them in analytics across the Web. Linked data paradigm promises to facilitate the realization of this vision. The RDF data cube (QB) vocabulary, which enables modeling multidimensional data as RDF graphs, is a major step towards this direction. Based on the QB vocabulary a number of data cubes are provided as linked data either by the owners of the data or by third parties. However, existing linked open data cubes do not facilitate the development of generically applicable tools that could use data from different sources. The aim of this paper is to present challenges related to the development of software tools that combine and exploit linked open data cubes in analytics and visualizations. These challenges have been e...

Most current visualizations for Linked Open Data are created for a single purpose or a single dataset. These ad hoc approaches can hardly exploit the linkedness of LOD, and we miss the tools for comfortable and enjoyable LOD browsing. On the other hand WWW has mature generic visualization: the web browsers. With the LODmilla browser we try to find the basic commodity features for generic LOD browsing including views, graph manipulation, searching, etc. With our browser users can navigate and explore multiple LOD datasets and they can also save LOD views and share them with other users.

In this demo paper we describe the current prototype of our new platform LodHub that allows users to publish and share linked datasets. The platform further allows to run SPARQL queries and execute Pig scripts on these datasets to support users in their data processing and analysis tasks.

2014

The adoption of the Linked Data principles and technologies has promised to enhance the analysis of statistics at a Web scale. Statistical data, however, is typically organized in data cubes where a numeric fact (aka measure) is categorized by dimensions. Both data cubes and linked data introduce complexity that raises the barrier for reusing the data. The majority of linked data tools are not able to support or do not facilitate the reuse of linked data cubes. In this demo we present the OpenCube Toolkit that enables the easy publishing and exploitation of linked data cubes using visualizations and data analytics.

2014

syntax to make statements about resources, and thanks to LOD principles, construct links to available external datasets in a simple manner, making them accessible and queryable through the Internet and promoting data reusability. As the amount of information at hand is greater every day, the need to handle it efficiently becomes a key requirement for anybody interested in working with it. This situation settles a great scenario for the Information Visualization field (or InfoVis, as it is known by academics and industry), taking advantage of humans capacity to identify patterns and gain insights from visual representations of abstract data. InfoVis positions itself in the intersection of other data-related fields: Statistics, Analytics, Dissemination and so on. One of the biggest issues concerning mass adoption of LOD outside the Semantic Web (SW) community, is the technical and conceptual knowledge required to take full advantage of the benefits provided by this type of data publis...

Semantic Technology, 2018

In 2016, the Japanese Statistics Center published a large-scale statistical linked open data (LOD) site consisting of approximately 300 million triples. The LOD simplify processing data, such as filtering, aggregation, and integration of data. The aim of this action is to promote domestic and international utilization of the statistics. In this paper, we introduce publishing processes and a use case of statistical LOD. Afterwards, we show our approach to speed up the SPARQL search for the vast number of LOD.

IEEE Intelligent Systems, 2016

In this article, we introduce the notion of Linked Open Cube Analytics (LOCA) systems. These systems enable the performance of analytics on top of multiple open statistical data (OSD) that reside in disparate portals. We present OSD's potential and highlight problems hampering OSD integration and reuse. To overcome these problems, we introduce an approach for OSD integration. The proposed approach capitalizes on the data cube model and linked data technologies to enable unified access to multiple OSD published disparate portals. Finally, we present an online analytical processing (OLAP) browser for linked data cubes as a proof of concept of LOCA systems. Throughout this article, we also outline the challenges that need to be addressed for the wide adoption of LOCA systems.

2021

In the context of the European project “GIOCOnDa”, this paper describes the conversion process from Open Data to Linked Open Data (LOD) and its implementation in the GIOCOnDa LOD platform. The platform contains a number of conversion configurations that allow different data sources from a variety of Open Data domains to be converted into LOD, without the need of software programming. In addition, the platform is configurable and extensible, as it enables to define mapping configurations for new datasets. Keywords-Linked Open Data (LOD); GIOCOnDa; OntoPia.

an inaugural event bridging the concepts and the communities devoted to each of data categories for a better understanding of data semantics and their use, by taking advantage from the development of Semantic Web, Deep Web, Internet, non-SQL and SQL structures, progresses in data processing, and the new tendency for acceptance of open environments. The volume and the complexity of available information overwhelm human and computing resources. Several approaches, technologies and tools are dealing with different types of data when searching, mining, learning and managing existing and increasingly growing information. From understanding Small data, the academia and industry recently embraced Big data, Linked data, and Open data. Each of these concepts carries specific foundations, algorithms and techniques, and is suitable and successful for different kinds of application. While approaching each concept from a silo point of view allows a better understanding (and potential optimizatio...

Lecture Notes in Computer Science

Demographic, economic, social and other datasets are often used in policy-making processes. These types of statistical data are opened more and more by governments, which enables the use of these datasets by the public. However, statistical data needs often to combine different datasets. Data cubes can be used to combine datasets and are a multi-dimensional array of values typically used to describe time series of geographical areas. While Linked Open Statistical Data (LOSD) cube software is still in an initial stage of maturity, there is a need for evaluation the software platforms used to process this open data. Yet there is a lack of evaluation methods. The objective of this ongoing research paper is to identify functional requirements for open data cubes infrastructures. Eight main processes are identified and a list of 23 functional requirements are used to evaluate the OpenCube platform. The evaluation results of a LOSD platform show that many functions are not automated and need to be manually executed. We recommend the further integration of the building blocks in the platform to reduce the barriers for the use of datasets by the public.