Data-driven Applications with conStruct
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Michael K. Bergman presented on the Bibliographic Knowledge Network (BKN) project. BKN aims to develop tools and services for scientific communities to select, filter and enhance bibliographic data. It uses a network of collaboration portals, gateways to external content, and dataset hubs. The core is a Drupal-based collaboration portal called a BKN node, which integrates a triplestore and search index to provide a structured dataset management environment. The presentation demonstrated a BKN node and described the data models, architecture, and benefits of the open source BKN software suite.
![Contacts & Information Bibliographic Knowledge Network Dr. Jim Pitman Director [email_address] Nitin Borwankar Project Manager [email_address] Web Site www.BibKN.org Structured Dynamics Michael K. Bergman CEO [email_address] blog: www.mkbergman.com Web Sites conStructSCS.com www.structureddynamics.com www.umbel.org](https://image.slidesharecdn.com/bknsemtech0920090611-090621131321-phpapp01/85/Data-driven-Applications-with-conStruct-37-320.jpg)
Data-driven Applications with conStruct
- 1. Michael K. Bergman Structured Dynamics LLC presented at Semantic Technologies ’09 Conference San Jose, CA June 16, 2009 “ BKN: Building Knowledge through Communities, and Communities through Knowledge”
- 2. Presentation Outline Overview of BKN Demonstration of a BKN Node More on Design Architecture and Web Services Framework Collaboration Demonstration Design Benefits conStruct and Next Plans Contact Info
- 3. I. Overview of BKN
- 4. Introduction BibKN or BKN : the Bib liographic K nowledge N etwork Develop tools and services for virtual organizations (“ VOs ”): Scientific communities of varied sizes, interests Conference groups Departmental research groups Students, teachers and faculty alike Select, filter and enhance bibliographic data for each VO : Multiple input citation, bibliographic and formats Apply new and existing methods to these bibliographic collections Bibliometric analysis Machine learning Statistical visualization Research, provide authoring tools for relevant structured data First math and statistics then any knowledge community
- 5. The Project Two-year effort Began October 2008 Joint consortium effort of: University of California, Berkeley Harvard University Stanford University American Institute of Mathematics (AIM) Director: Dr. Jim Pitman Professor of Statistics and Mathematics, UC Berkeley Funded by NSF (Grant No. 0835851) All software and data to be open source
- 6. Some Points for this Talk Four kinds of network “nodes”: VO Nodes – collaboration portals Gateways – connections to existing external content Hubs – aggregate suppliers of useful datasets Individual dataset contributors and clients Data formats and models: BibJSON : human readable, exchange format Ingest of various existing citation/biblio formats RDF : “canonical” internal data model VO Nodes the emphasis of this talk: CMS: Drupal RDF triplestore: Virtuoso Full-text, faceted search: Solr
- 7. Preview of Benefits Comprehensive toolset for structured data (semantic Web) conversion, use and exposure Data-driven via ontologies; easily scoped, tailored Naïve data formats and RDF APIs via RESTful Web services Web services framework can mix-and-match: Standalone Integrated with any CMS External tools access Web-wide user and dataset access and permissions Available as a distro of the Drupal CMS Open source and extensible
- 8. conStruct SCS A ‘data-driven app’ (ontologies + structured data) Datasets + permissions Context-sensitive display templates Use and exposure of linked data Hosted by Drupal
- 9. II. Demonstration of a BKN Node
- 11. III. More on Design
- 12. Data Formats and Exchange Ingest standard structured and bibliographic data: BibTeX Bibsonomy RePEc etc., etc. Standard ‘naïve’ data format: BibJSON Attribute-value pair orientation Human readable Easily authored and edited RDF as the internal, ‘canonical’ data model Also can be used for exchange
- 13. Data Formats and Exchange
- 14. Four Kinds of ‘Nodes’ VO Nodes – collaboration portals Gateways – connections to existing external content Hubs – aggregate suppliers of useful datasets Individual dataset contributors and clients The primary construct for data exchange and use is the dataset
- 17. The Backend Structure Drupal: User interface and theming User and group management Content management system Many third-party tools and modules Virtuoso: RDF triple store SPARQL and endpoints; linked data exposure Some structured data conversions Solr: Full-text indexing Faceting and aggregating (counts) Innovative complete RDF search
- 19. IV. Architecture and Web Services Framework
- 21. structWSF (Web services framework) Standard functionality: Data management: C reate R ead U pdate D elete Browse and search Import/export Display templates Dataset registration w/ permissions Ontology registration User authorization and access (IP-based initially) RESTful design
- 22. structWSF Schema
- 23. V. Collaboration Demonstration
- 24. Topology of the Collaboration Demo
- 25. VI. Design Benefits
- 26. Comprehensive Toolset Standard functionality: Data management: C reate R ead U pdate D elete Browse and search Import/export Display templates Dataset registration w/ permissions Ontology registration User authorization and access (via Drupal OG) Drupal modules are lightweight wrappers over structWSF
- 27. Data-driven via Ontologies Ontologies (OWL) guide: Instance records and attributes Data relationships Data presentation: Trees/hierarchies Display templates User interface, e.g .: Autocompletion Contextual dropdown list selections New record entry New attribute entry etc. Addition or swap out of ontologies drives generic tools
- 28. RESTful structWSF Independent, standalone piece Naïve data formats and RDF APIs via RESTful Web services Web services framework can mix-and-match: Standalone Integrated with any CMS External tools access Web-wide user and dataset access and permissions As described
- 29. Open Source Drupal Distro Provided as the conStruct module See conclusion
- 30. Re-cap of Benefits Comprehensive toolset for structured data (semantic Web) conversion, use and exposure Data-driven via ontologies; easily scoped, tailored Naïve data formats and RDF APIs via RESTful Web services Web services framework can mix-and-match: Standalone Integrated with any CMS External tools access Web-wide user and dataset access and permissions Available as a distro of the Drupal CMS Open source and extensible
- 31. VII. conStruct and Next Plans
- 32. conStruct SCS conStruct SCS is a structured content system Open source version of the BKN project that runs on Drupal Drupal components: Drupal conStruct module (core functionality) structDisplay module (display templating) Required additional modules (e.g., Organic Groups, WYSIWYG, etc.) Structured Dynamics: structWSF (Web services framework) Third parties: Virtuoso RDF triple store Solr full-text faceted search Smarty templating system
- 34. conStruct Distribution Options Initially: Downloads from multiple sites Download, Install & Configuration manual Next option: Single-click Amazon EC2 AMI install Planned: Complete, packaged Drupal distro Hoped: Multiple CMS versions
- 35. conStruct Plans and Schedule conStructSCS.com now open Online demo available OpenStructs.org now open Also the distribution point for open source display templates, converters and extractors conStruct alpha distro to be available June 30 sturctWSF alpha distro to be available June 30 Additional conStruct supporting modules planned on an ongoing basis
- 36. VII. Contact Info
- 37. Contacts & Information Bibliographic Knowledge Network Dr. Jim Pitman Director [email_address] Nitin Borwankar Project Manager [email_address] Web Site www.BibKN.org Structured Dynamics Michael K. Bergman CEO [email_address] blog: www.mkbergman.com Web Sites conStructSCS.com www.structureddynamics.com www.umbel.org