Linked Data promises to make data integration easier for academic and industrial use. However, performing such data integration tasks currently requires high investments because of several major challenges. Available tools are not connected to each other, access restrictions on private data and certain tools have to be enforced, processes have to be managable and easy to use, and, nally, data processing needs to be comprehensible in terms of provenance and traceability. The GeoKnow Generator Workbench solves these problems by providing an integrated Web interface on top of an extensible solution for easy access to tools dedicated to certain Linked Data lifecycle phases, also addressing major industrial requirements. While it focuses on geospatial aspects, it is generally applicable to Linked Data management tasks.
In the last decade, many open data sources have been
published following the Linked Data (LD) principles [
The paper is organized as follows. We discuss primary requirements in Section 2. The GeoKnow Generator Workbench is presented in Section 3. Section 4 outlines applications based on the proposed solution. Related work is discussed in Section 5. Finally, the paper closes with the conclusions and future work.
In this section, we describe the use cases and the related derived requirements which led to the creation of the GeoKnow Generator. 2.1
Tourism e-Commerce. In this use case by Unister2 internal data have to be enriched with public geospatial data in order to improve online search applications. Thus, Unister can understand user's search motives and support queries beyond basic hotel features.
Storage/ Querying Quality
Analysis Linked Data
Lifecycle Search/ Browsing/ Exploration
Classification/ Enrichment
EvRoeluptaioirn / Supply Chain. In order to visualize key information of the logistics in a supply chain, information from supply chain transactions have to be connected to related LD. As a result, the ow of material and accompanying information can be observed in real-time, bottlenecks can be identi ed early, media breaks in the information ows are minimised. This use case by a large automotive company incorporates tra c, weather, and transport information, which is linked to the supply chain information.
E-Government Services. The Linked Data Service3 (LINDAS) has the objective to provide information about authorities. Their services and software solutions are collected decentralised by the Swiss Confederation, the cantons or communes. The service gathers, homogenises, and publishes authority data using Semantic Web standard.
Automotive Data Investigation. Geosocial networks for sharing location-based messages, such as recommendations and noti cations, bene t from providing context-related information. For services like community-based truck networks developed by Continental Automotive GmbH, relevant geospatial LD has to be ltered and selected, e.g., motorway service areas. Of future interest are further touristic information, such as museums and playgrounds, which are readily available in public data sets.
Concerning functional requirements, the primary functionality of tools for LD lifecycle phases has to be extended towards geospatial data, e.g., by implementating geospatial distance metrics for interlinking and fusing datasets, and appropriate quality metrics. In addition, non-functional requirements include:
Scalability for working with large data sets Authentication, Authorization and Role Management as a primary requirement in companies Data Provenance tracking for tracability of changes Job Monitoring and Robustness for applicability in production Modularity and Composability in order to provide exibility w.r.t. integrating additional tools
The GeoKnow Generator is a stack of tools for data preparation following the LD lifecycle. The GeoKnow Generator Workbench is the common entry point of all those tools. The actual architecture is presented in Figure 2. This diagram re ects the stack of tools integrated for each stage of the LD lifecycle. This architecture lays on following three pillars: Software integration and deployment using the Debian packaging system. This infrastructure facilitates the packaging and integration as well as the maintenance of dependencies between the various components. Using the Debian system also enables the deployment on individual servers or cloud infrastructures.
Use of a central SPARQL endpoint and standardized vocabularies for knowledge base access and integration between the di erent tools. All components can access this central knowledge base repository and write their data back to it. In order for other tools to make sense out of the information it is important to de ne vocabularies for each of the stages of the LD lifecycle. Integration of the user interfaces based on REST enabled Web applications. Currently the user interfaces of the various tools are technologically and methodologically heterogeneous. Thus, a common entry point for accessing the tools can forward a user to a speci c UI component provided by a certain tool in order to complete a certain task. For tools that do not provide an interface, extra development e ort is needed.
For integrating components, some JavaScript and basic RDF editing are required. Speci cally, the AngularJS framework4 is used for straight-forward creation of GUIs and application routing. A more detailed description of the GeoKnow Generator Workbench and how to integrate components can be found in the repository wiki5.
wiki Table 1 describes the actual software tools integrated in the GeoKnow Generator Workbench. Besides these integration work, the main bene ts of the GeoKnow Generator Workbench are the following features: (1) Authentication and Role Management: Access to di erent components can be restricted via the Workbench using roles. (2) Authorisation: A graph-based security access control allows users to create and con gure public and user-speci c access control to datasets. For components accessing private graphs, Crossorigin resource sharing (CORS) and proxy-based model is provided. (3) Job Monitoring: For some of the software tools, which can have long runtime on large-scale input, the user can execute batch jobs that are con gured and observable in a dashboard (Figure 3b). (4) Data Provenance: When working with several datasources and di erent processing stages, it is required to keep information about the provenance of certain triples. The Workbench adds metadata about the tools used to process these data, timestamp, and authors. (5) Scalability: Storage scalability is supported thanks to Virtuoso Cluster edition. Workbench and integrated tools can be easly scaled out to di erent nodes. All software tools used in the GeoKnow Generator Workbench and the GeoKnow Generator Workbench itself are availeble in the LD Stack6 repositories. The LD Stack is an independent project that aims to ease the distribution and installation and integration of LD tools developed in di ernt research projects. GeoKnow project is an active contributor and supporter of the LD Stack.
In the Tourism e-Commerce use case, the GeoKnow Generator Workbench has been applied to generate an interlinked dataset used for a motive-based search infrastructure. External datasets have been transformed to RDF using Triple
Geo and Sparqlify. The linking of external data and internal data was performed using LIMES with immense performance gains compared to a comparable custom approach. Besides integration of structured data, unstructured data such as hotel reviews can be processed using DEER. That way, related entities can be identi ed and integrated so their attributes (such as locations) can be used for further analysis of places, providing useful information for a search engine. In the Supply Chain use case, a Dashboard (see Figure 3a) o ers a uni ed spatial view on the logistics in the supply chain. Companies can bene t from the Supply Chain Dashboard by gaining a better picture of the current state of the supply chain and the spatial distribution of goods and products in the supply chain. The required data integration and linking were enabled by the Sparqlify and LIMES components of the Workbench. The resulting information allows live visualisation of orders and shipments status in the Dashboard. Circulated messages and a supplier score card provide live analytics of the supply chain based on user-de ned metrics.
Continental products DropYa and TruckYa use GeoKnow technology in the Automotive Data Investigation use case. DropYa is a geosocial network where users can send and receive location-based messages sharing their experience and recommendations. TruckYa is a community-based tool for nding adequate parking spaces aimed at truck drivers. In the investigation process of assessing LD sources, Facete provides the functionality to browse data on a map, view attributes of interest, export relevant parts and support the editorial process.
The Ontos AG7 Linked Data Information Workbench (OntosLDIW) is a generic, enterprise-ready workbench on the GeoKnow architecture supporting the LD Lifecycle. OntosLDIW was applied to a real world e-government scenario for the State Secretariat for Economic A airs (SECO) in Switzerland8. The developed Linked Data Service (LINDAS) has centralized the tasks of the data scientist into one common workbench allowing to orchestrate, monitor and execute processes from one standardized UI. Thus, it reduces the e orts to learn various tools and front ends, improves e ciency, and reduces costs.
As generalized feedback from these use case applications, an integrated workbench brings the bene t of orchestrating the process from a single point of view. It reduces the time required for learning and switching between tools, and it reduces the interface and data exchange through a single point of access and common UI.
The LOD2 Statistical Workbench [
(a) The supply chain dashboard.
(b) Task monitoring dashbord.
framework created under the EU project COSMODE9
using components from the LD Stack. This platform requires
implementing Data Processing Units for each component in
order to be integrated. Moreover, Uni edviews doesn't
provide support for authentication or authorisation features.
Still, it represents a relevant reference point for the
GeoKnow Generator Workbench. [
The main contribution of this paper, presented in 3, is the GeoKnow Generator Workbench, which is a web-based user interface that integrates all components needed for processing data following the LD lifecycle. It enables simple access and interaction with the di erent components needed for di erent tasks. Moreover, it provides APIs for being integrated into other systems and to exchange the components currently available out-of-the-box. Future tools can be integrated easily. An online demo and video tutorials of the Workbench are available at http://generator.geoknow.eu. We described the GeoKnow Generator and the main features enabling an enterprise use. All requirements, including those w.r.t managing geospatial data, are derived from real world use cases, which also demonstrate the usability of the Generator components and the Workbench in enterprise environments. In the future we will integrate additional tools and decouple the Workbench from Virtuoso.
Acknowledgments.
This work is part of the European Commission FP7 Project GeoKnow (GA No 318159).