GraphDB Cloud: an on-demand enterprise ready RDF database

We, from Ontotext, are excited to announce GraphDB Cloud – the easy way to introduce you to a semantic database like our signature GraphDB product. The automated tasks in GraphDB Cloud save the organizations the time and effort to install and manage hardware and software as well as the cost to buy it. Compared to a do-it-yourself database, DBaaS offers developers the opportunity to cut down the time it took them to work with their databases and spend their valuable time on creating and innovating instead of administrating.

GraphDB Cloud is one part of the Cognitive Cloud solutions for low-cost and on-demand smart data management.

The users are with the following profile:

  • Small cognitive-technology oriented team in a big organization that needs low upfront and ongoing costs for a database.
  • Start-up companies without a database infrastructure, which requires a reliable technology that scales up along with their business.
  • Corporate solution architects working to solve the challenges their enterprise faces when handling huge amounts of data and information

As a next step, we want to invite you to watch our webinar “GraphDB Cloud – Enterprise Ready RDF Database on Demand” where we introduce you to the DraphDB Cloud console and advise you how you could create custom solutions to address your company’s specific data and information needs.

The proDataMarket Ontology: Enabling Semantic Interoperability of Real Property Data

Real property data (often referred to as real estate, realty, or immovable property data) represent a valuable asset that has the potential to enable innovative services when integrated with related contextual data (e.g., business data). Such services can range from providing evaluation of real estate to reporting on up-to-date information about state-owned properties. Real property data integration is a difficult task primarily due to the heterogeneity and complexity of the real property data, and the lack of generally agreed upon semantic descriptions of the concepts in this domain. The proDataMarket ontology is developed in the project as a key enabler for integration of real property data.

The proDataMarket ontology design and development process followed techniques and design choices supported by existing methodologies, mainly the one proposed by Noy [1]. Requirements are extracted from a set of relevant business cases and competency questions [2] are defined for each business case, so as core concepts and relationships. A conceptual model is then developed based on the requirements mentioned above and international standards including ISO 19152:2012 and European Union’s INSPIRE data specifications. For example, the LADM conceptual model from ISO 19152:2012 is used as reference model to the proDataMarket cadastral domain conceptual model. Afterwards we implemented the conceptual model using RDFS/OWL linked data standard. RDFS is used to model concepts, properties and simple relationships such as rdfs:subClassOf. OWL is built upon RDFS and provides a richer language for web ontology modelling and it is used to model constraints and other advanced relationships, such as the cardinality constraint needed to express the relationship between properties and buildings.

The proDataMarket ontology can be accessed at http://vocabs.datagraft.net/proDataMarket/. The ontology has been divided into several sub-ontologies (see Table below), reflecting the cross-domain nature of the requirements. This modular approach also helped to handle the complexity of the model and made it easier to maintain. In the current version, there are 11 sub-ontologies with 43 native classes and 43 native properties.

Table: Composition of the proDataMarket ontology

Domain/module Namespace prefix URL Classes Properties Business cases
Common prodm-com http://vocabs.datagraft.net/proDataMarket/0.1/Common# 4 4 ALL
Cadaster prodm-cad http://vocabs.datagraft.net/proDataMarket/0.1/Cadastre# 6 16 SoE, RVAS, NNAS, SIM
State of Estate Report prodm-soe http://vocabs.datagraft.net/proDataMarket/0.1/SoE# 4 2 SoE, RVAS
Business Entity Reuse the existing vocabularies, no new classes and properties 0 0 SoE, RVAS
Building Accessibility Reuse the existing vocabularies, no new classes and properties 0 0 SoE
Natural Hazard prodm-nh http://vocabs.datagraft.net/proDataMarket/0.1/NaturalHazard# 1 0 RVAS
Land Parcel Identification System (LPIS) prodm-lpis http://vocabs.datagraft.net/proDataMarket/0.1/LPIS# 1 7 CAPAS
Protected Sites prodm-ps http://vocabs.datagraft.net/proDataMarket/0.1/ProtectedSite# 2 0 CAPAS
Sentinel data prodm-sen http://vocabs.datagraft.net/proDataMarket/0.1/Sentinel# 1 1 CAPAS
Landscape Elements (LiDAR data) prodm-lid http://vocabs.datagraft.net/proDataMarket/0.1/Lidar# 3 0 CAPAS
Assessment prodm-asm http://vocabs.datagraft.net/proDataMarket/0.1/Assessment# 3 3 CAPAS
CensusTract prodm-ct http://vocabs.datagraft.net/proDataMarket/0.1/CensusTract# 1 0 CST,CCRS
Urban Infrastructure prodm-ui http://vocabs.datagraft.net/proDataMarket/0.1/UrbanInfrastructure# 17 10 SIM
Total: 43 43

More than 30 datasets have been published through the DataGraft platform [3] [4] using the proDataMarket ontology as a central reference model. All seven business cases use the proDataMarket ontology in data publishing. More details on the proDataMarket vocabulary can be found in the paper under review: http://www.semantic-web-journal.net/content/prodatamarket-ontology-enabling-semantic-interoperability-real-property-data

References

  • [1] Noy, Natalya F., and Deborah L. McGuinness. “Ontology development 101: A guide to creating your first ontology.” (2001).
  • [2] Grüninger, Michael, and Mark S. Fox. “Methodology for the Design and Evaluation of Ontologies.” (1995).
  • [3] Roman, D., et al. DataGraft: One-Stop-Shop for Open Data Management. 2017. Semantic Web, vol. Preprint, no. Preprint, pp. 1-19, 2017. DOI: 10.3233/SW-170263.
  • [4] Roman, D., et al. DataGraft: Simplifying Open Data Publishing. ESWC (Satellite Events) 2016: 101-106.

Recent proDataMarket presentations

 

 

 

 

Ontotext in the proDataMarket Project

Ontotext is a SME founded in 2000 in Sofia, Bulgaria. For more than a decade Ontotext has successfully delivered Semantic Technology products and solutions that improve data integration, data management and search within enterprises. Key products of Ontotext include GraphDB – one of the leading enterprise RDF graph databases, and the Self-Service Semantic Suite (S4) – a platform for on-demand smart applications and data management. Ontotext is also delivering semantic data management solutions to organizations in various verticals: media & publishing, healthcare & life sciences, museums and digital libraries.

Ontotext’s vision for smart data management is based on using ontologies and vocabularies for modelling data, analyzing free flowing text content and extracting structured information and facts. The RDF graphs data model provides an agile way to manage and query heterogeneous data, and powerful semantic search can be implemented on top of the graph data. This way the business users can ask more complex questions and find more precise answers, than by using traditional enterprise full-text search approaches.

Ontotext is one of the technology partners in the proDataMarket project. Ontotext’s responsibilities include delivering a scalable data management infrastructure, which will allow for data stored in various legacy data sources to be transformed into RDF graphs with proper metadata mappings to popular ontologies and vocabularies. A scalable RDF database-as-a-service running in the Cloud will be one of the key components of the proDataMarket infrastructure, and it will enable quick deployment of new data services on top of 3rd party datasets. This way, the numerous data publishers will not need to deal with the overhead of provisioning and maintaining the access to their data, while developers will get an easy, instant and reliable access to valuable property related via simple RESTful APIs.