Enabling Spatio-Temporal Search in Open Data

Intuitively, most datasets found in Open Data are organised by spatio-temporal scope, that is, single datasets provide data for a certain region, valid for a certain time period. For many use cases (such as for instance data journalism and fact checking) a pre-dominant need is to scope down the relevant datasets to a particular period or region. Therefore, we argue that spatio-temporal search is a crucial need for Open Data portals and across Open Data portals, yet - to the best of our knowledge - no working solution exists. We argue that - just like for for regular Web search - knowledge graphs can be helpful to significantly improve search: in fact, the ingredients for a public knowledge graph of geographic entities as well as time periods and events exist already on the Web of Data, although they have not yet been integrated and applied - in a principled manner - to the use case of Open Data search. In the present paper we aim at doing just that: we (i) present a scalable approach to construct a spatio-temporal knowledge graph that hierarchically structures geographical, as well as temporal entities, (ii) annotate a large corpus of tabular datasets from open data portals, (iii) enable structured, spatio-temporal search over Open Data catalogs through our spatio-temporal knowledge graph, both via a search interface as well as via a SPARQL endpoint, available at data.wu.ac.at/odgraphsearch/Series: Working Papers on Information Systems, Information Business and Operation

Geo-Semantic Labelling of Open Data. SEMANTiCS 2018-14th International Conference on Semantic Systems

In the past years Open Data has become a trend among governments to increase transparency and public engagement by opening up national, regional, and local datasets. However, while many of these datasets come in semi-structured file formats, they use di ff erent schemata and lack geo-references or semantically meaningful links and descriptions of the corresponding geo-entities. We aim to address this by detecting and establishing links to geo-entities in the datasets found in Open Data catalogs and their respective metadata descriptions and link them to a knowledge graph of geo-entities. This knowledge graph does not yet readily exist, though, or at least, not a single one: so, we integrate and interlink several datasets to construct our (extensible) base geo-entities knowledge graph: (i) the openly available geospatial data repository GeoNames, (ii) the map service OpenStreetMap, (iii) country-specific sets of postal codes, and (iv) the European Union's classification system NUTS. As a second step, this base knowledge graph is used to add semantic labels to the open datasets, i.e., we heuristically disambiguate the geo-entities in CSV columns using the context of the labels and the hierarchical graph structure of our base knowledge graph. Finally, in order to interact with and retrieve the content, we index the datasets and provide a demo user interface. Currently we indexed resources from four Open Data portals, and allow search queries for geo-entities as well as full-text matches at http://data.wu.ac.at/odgraph/

Geo-Semantic Labelling of Open Data

In the past years Open Data has become a trend among governments to increase transparency and public engagement by opening up national, regional, and local datasets. However, while many of these datasets come in semi-structured file formats, they use different schemata and lack geo-references or semantically meaningful links and descriptions of the corresponding geo-entities. We aim to address this by detecting and establishing links to geo-entities in the datasets found in Open Data catalogs and their respective metadata descriptions and link them to a knowledge graph of geo-entities. This knowledge graph does not yet readily exist, though, or at least, not a single one: so, we integrate and interlink several datasets to construct our (extensible) base geo-entities knowledge graph: (i) the openly available geospatial data repository GeoNames, (ii) the map service OpenStreetMap, (iii) country-specific sets of postal codes, and (iv) the European Union¿s classification system NUTS. As a second step, this base knowledge graph is used to add semantic labels to the open datasets, i.e., we heuristically disambiguate the geo-entities in CSV columns using the context of the labels and the hierarchical graph structure of our base knowledge graph. Finally, in order to interact with and retrieve the content, we index the datasets and provide a demo user interface. Currently we indexed resources from four Open Data portals, and allow search queries for geo-entities as well as full-text matches at http://data.wu.ac.at/odgraph/

Policy Patterns for Usage Control in Data Spaces

Data-driven technologies have the potential to initiate a transportation related revolution in the way we travel, commute and navigate within cities. As a major effort of this transformation relies on Mobility Data Spaces for the exchange of mobility data, the necessity to protect valuable data and formulate conditions for data exchange arises. This paper presents key contributions to the development of automated contract negotiation and data usage policies in the Mobility Data Space. A comprehensive listing of policy patterns for usage control is provided, addressing common requirements and scenarios in data sharing and governance. The use of the Open Digital Rights Language (ODRL) is proposed to formalize the collected policies, along with an extension of the ODRL vocabulary for data space-specific properties.Comment: 12 pages, 1 figure, 1 table, 2 listing

Towards a Critical Open-Source Software Database

Open-source software (OSS) plays a vital role in the modern software ecosystem. However, the maintenance and sustainability of OSS projects can be challenging. In this paper, we present the CrOSSD project, which aims to build a database of OSS projects and measure their current project "health" status. In the project, we will use both quantitative and qualitative metrics to evaluate the health of OSS projects. The quantitative metrics will be gathered through automated crawling of meta information such as the number of contributors, commits and lines of code. Qualitative metrics will be gathered for selected "critical" projects through manual analysis and automated tools, including aspects such as sustainability, funding, community engagement and adherence to security policies. The results of the analysis will be presented on a user-friendly web platform, which will allow users to view the health of individual OSS projects as well as the overall health of the OSS ecosystem. With this approach, the CrOSSD project provides a comprehensive and up-to-date view of the health of OSS projects, making it easier for developers, maintainers and other stakeholders to understand the health of OSS projects and make informed decisions about their use and maintenance.Comment: 4 pages, 1 figur

Search, Filter, Fork, and Link Open Data - The ADEQUATe platform: data- and community-driven quality improvements.

The present work describes the ADEQUATe platform: a framework to monitor the quality of (Governmental) Open Data catalogs, to re-publish improved and linked versions of the datasets and their respective metadata descriptions, and to include the community in the quality improvement process. The information acquired by the linking and (meta)data improvement steps is then integrated in a semantic search engine. In the paper, we first describe the requirements of the platform, which are based on focus group interviews and a web-based survey. Second, we use these requirements to formulate the goals and show the architecture of the overall platform, and third, we showcase the potential and relevance of the platform to resolve the requirements by describing exemplary user journeys exploring the system. The platform is available at: https://www.adequate.at/

A Survey of Dataspace Connector Implementations

The concept of dataspaces aims to facilitate secure and sovereign data exchange among multiple stakeholders. Technical implementations known as "connectors" support the definition of usage control policies and the verifiable enforcement of such policies. This paper provides an overview of existing literature and reviews current open-source dataspace connector implementations that are compliant with the International Data Spaces (IDS) standard. To assess maturity and readiness, we review four implementations with regard to their architecture, underlying data model and usage control language.Comment: 12 pages, 5 figure

An advanced knowledge-based analysis of company vision statements

What distinguishes a good vision? A knowledge perspective on organizational visions can be helpful in order to identify which content vision statements should include. Knowledge enablers aim to respond to the question what organizations need to know for planning effectively and performing their activities well. Previous studies identified three knowledge enablers in organizational visions: knowledge about organizational identity (OI), emerging potentiality (EP) and mutual embeddedness (ME). In this paper, we empirically tested these findings through a qualitative content analysis of a large number of Forbes-2000 companies vision statements. As a result, we detected all three knowledge enablers in our sample. Moreover, we found that the rank of companies in the Forbes 2000 list correlates not only with the occurrence of knowledge enablers, but also with the frequency of knowledge about emerging potentiality. Consequently, companies have to be supported to generate especially this knowledge enabler. Our results can contribute to research on knowledge-based vision development and inspire an ongoing discussion in the KM community about future research priorities