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Cloud based linked data platform for Structural Engineering Experiment Xiaohui Zhang

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Presentation on theme: "Cloud based linked data platform for Structural Engineering Experiment Xiaohui Zhang"— Presentation transcript:

1 Cloud based linked data platform for Structural Engineering Experiment Xiaohui Zhang

2 Outline  Motivation  The CLDP-SEE Platform  Conclusion and Future Work 2

3 Motivation  Structural Engineering  A discipline analyzing the force and deformation of buildings by mechanical methods.  Experiment is one of the main means for domain research.  Large amounts of experimental data is accumulated, but be maintained by each experimental user dispersedly.  Due to the complexity and heterogeneity of the experimental data, the sharing and integrating with the traditional methods is difficult. 3

4 Motivation  Linked Data  Linked Data is simply about using the Web to publish structured data and create typed links between data from different sources.  Based on semantic web, linked data uses RDF to make typed statements that link arbitrary things in the world.  Linked data provides a wonderful approach to publish and consume data on the web and make the web be a global data space which can be understood both by computer and human. 4

5 Motivation  Linked Data for Structure Engineering  The data represented based on semantic can be understood by machines, which is helpful for the integration and processing of experimental data.  The interlinking among data from different sources is a effective measure for the heterogeneity.  Linked data will make it easy for the sharing and intelligent processing of experimental data. 5

6 Motivation  A huge challenge for domain researchers to deploy and use Linked Data related tools to make operations on the data:  Conversion of data format  Publication of experiment data  Integration of experiment data  Consuming of linked experiment data 6

7 Motivation  A centralized platform providing all the functions needed by experiencing linked data in services is necessary for domain researchers.  A linked data platform based on cloud for Structural Engineering Experiment (CLDP-SEE) is proposed by this paper.  The publishing, interlinking and consuming of experiment data is an intact ecosystem of data sharing. CLDP-SEE can  lower the threshold of sharing data with linked data technology for domain users;  promote the growth of the linked data ecosystem and the development of Structural Engineering discipline. 7

8 The CLDP-SEE Platform The application scenario of CLDP-SEE 8

9 The CLDP-SEE Platform  The operations in application scenario :  Uploading and managing the RDF data, setting access control policies of each datasets.  Uploading raw data in traditional formats, such as CSV, Excel, Relational Database. And then converting these raw data into RDF.  Querying datasets from the shared data space, private data space according to the authority and even the datasets from the Web, and then interlinking data among these datasets to generate a Virtual Data Space.  Reasoning and querying the data in Virtual Data Space.  Publishing data with Linked Data Server. 9

10 The CLDP-SEE Platform  The Architecture of CLDP-SEE 10

11 The CLDP-SEE Platform  Portal Layer  Provides graphical web interface for users to experience almost all the functions providing by CLDP-SEE. 11

12 The CLDP-SEE Platform  Core Service Layer  Data Manage Service: is mainly used to help users to manage their data.  Data Upload  Data Format Transform  Dataset Registry  Dataset Manage  Data Publish  Authority Manage 12

13 The CLDP-SEE Platform  Core Service Layer  Data Link Service  Provides the capabilities of data integration;  Coreference Interlink is responsible for getting the request of users, and finding the coreference relations between data from different datasets.  The coreference relation of RDF data refers to two different URI pointing to the same entity.  Two methods of coreference interlinking:  Similarity computation: implemented according to SILk(Isele, R.; Jentzsch, A. & Bizer, C. 2010)  Rules matching: Link Rule Manage service provides graphical interface for the experts and users to define rules.  Links Update will update the links with the information collected by Dataset Monitor service. 13

14 The CLDP-SEE Platform  Core Service Layer  Data Reason Service  The rule-based inference is mainly done by this service.  Users can select any datasets from Virtual Data Space, Private Space or Shared Data Space according to the authority.  Inference Rule Manage supports each user to define and manage their private inference rules, and check the consistency with default rules provided by domain experts.  Default rules and user-defined rules can be applied in the inference. 14

15 The CLDP-SEE Platform  Core Service Layer  Data Query Service  The basis of consuming linked experiment data.  Two kinds of query interfaces:  navigation query based on SEE ontology  query based on keywords  Support users self-defining the scope of query.  Query Engine is responsible for processing the request from self-service portal, and executes SPARQL query on the datasets selected by users. 15

16 The CLDP-SEE Platform  Supporting Service Layer  The services in this layer are mainly supporting the functions of the services in Core Service Layer.  Data service mainly provides the underlying functions of RDF data management and access.  Ontology Manage service, Dataset Access service , Dataset Storage service, Dataset Monitor.  Publish Service mainly supports the Data Publish in Data Manage Service.  Linked Data Server  RDF File Server 16

17 The CLDP-SEE Platform  Supporting Service Layer  User Service:  Metadata Manage service: manages the information of users and make user can update personal materials.  Role Manage service: be provided for platform administrator to manage the roles of users.  Social Network Manage service: manages the friend relationships among users, and provides personal space for each user. 17

18 The CLDP-SEE Platform  Data Storage Layer  SEE Ontology  stores the unified ontology schema and the data in Shared Data Space.  RDF Datasets  stores the datasets in users’ Private Data Space, and ensure the isolation between users.  Links of Data  stores the relation between the entities from different datasets.  Rule Base  default rule bases  user defined rules 18

19 Conclusion and Future Work  CLDP-SEE provides almost all the services needed by Structural Engineering domain users to manage and share experiment data based on linked data technology.  Future work:  Improving the performance of data linking and inference.  More flexible access control policy and fine- grained access control model. 19

20 Thank You! 20

21 Related Works  Publication of Linked Data  D2R Server (Prud’hommeaux & Seaborne. 2006) : publishing the content of relational databases as RDF.  Pubby and Elda: providing Linked Data interfaces for RDF data sources. 21

22 Related Works  Searching and Browsing of Linked Data  linked data browser: enables people to view data from one dataset to another by following RDF links.  Tabulator (Berners-Lee et al., 2006)  OpenLink Browser (  Marbles (  linked data engine: provides service for people querying the Web of Data.  Falcons, Sindice, Swoogle and SWSE 22

23 Related Works  Interlinking of Linked Data  SILK (Robert et al., 2010)  DSNotify(Haslhofer & Popitsch, 2009)  LinkedDataBR (Kelli et al., 2011): a platform used by Brazil for linking open Brazilian governmental data.  Talis: a platform for RDF data sharing via weaving data with the Web to create a highly available and adaptable environment. ( 23

24 Related Works  CLDP-SEE provides services for the storage, query, publishing and management of RDF data.  CLDP-SEE provides more perfect services with cloud characteristics:  More flexible and personalized self-service model;  Query the datasets according to subject, and ineterlink the data in the result datasets;  Elastical reasoning service on the user-defined datasets;  A shared RDF repository with rich interlinks among data. 24

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