Linking SharePoint Documents with Structured Data. Towards Unified Views of Business-critical Information. Andreas Blumauer Director PoolParty Ltd, UK

Transcription

1 Linking SharePoint Documents with Structured Data Towards Unified Views of Business-critical Information Andreas Blumauer Director PoolParty Ltd, UK

2 2 Andreas Blumauer serves customers Semantic Web Company graduates founded Founder & CEO of > parent company of active at Director of partners with located Graph-based Introduction PoolParty Software Ltd London developer & vendor of 7.0 version based on used for part of Text Mining named by manages integrates with Ontologies standard for standard for Graph databases part of Taxonomies Enterprise Knowledge Graphs

3 3 Problem Statements from our customers Data is often bound to specific applications which reduces reuse of the data dramatically. Tight coupling of data to applications limits the options to connect the data to other internal and external sources. People should participate in a data sharing culture which is beneficial for the whole enterprise. When we cannot express data in relational formats we typically leave the data in a non-machine readable format in a document. Data scientists should benefit from more consistent semantics of data to be reused for various machine learning tasks.

4 4 Gartner Hype Cycle for Artificial Intelligence, 2018 > Read more Organizations can expect significant value from knowledge graphs in many areas:... Interrelated data is contextualized data, thereby aiding its discovery and findability via implicit and indirect connections. Once structured in the form of a knowledge graph, unstructured data can be queried, thereby preprocessing it for analysis.

5 5 Example: HR Analytics As an HR manager, for upcoming training programmes, I want to identify employees who have a certain skill set have a specific degree have skills that are increasingly important on the labour market fall into a specific salary range Employee database Resumes Labour market statistics Linking Structured to Unstructured Data

6 6 Example: Research in Life Sciences As a researcher in pharmaceutical industry, I want to plan new experiments more efficiently. I want to know what s already available. I m interested in former experiments where certain genes were tested under specific treatment conditions in a target therapeutic area with help from categorisation systems like disease hierarchies UniProt, ChEMBL Experiments Documentation MeSH DrugBank Linking Structured to Unstructured Data and to Industry Knowledge Graphs

7 7 Making Use of Knowledge Graphs Experiments Knowledge Graphs serve as means to enrich unstructured information to provide a rich set of additional access points to document repositories

8 8 Making Use of Knowledge Graphs and Automated Reasoning

9 9 Example: Recommender System As an expert working for an International Development Bank, I want to get a better way to disseminate information to our staff so that projects would be more efficient and more successful, to receive relevant articles and information when meetings are scheduled, during searches, and eventually to power a chat bot. Project database Meeting notes Interest and working profiles Benefiting from automatic recommendations based on personal profiles

10 Things but not Strings : Semantic Knowledge Graphs manage resources, not just terms Retina Funduscope preflabel taxonomy/ image images/ taxonomy/ preflabel Ophthalmoscope altlabel has broader /taxonomy/ preflabel Diagnostic Equipment

11 11 Taxonomy & Ontology Server Entity Extractor & Semantic Classifier Controlled vocabularies as a basis for highly precise knowledge extraction and text classification PoolParty Semantic Suite Data Integration & Data Linking Unstructured Data Semistructured Data Structured Data Factsheet Bain Capital is a venture capital company based in Boston, MA. Since inception it has invested in hundreds of companies including AMC Entertainment, Brookstone, and Burger King. The company was co-founded by Mitt Romney. Most complete Semantic Middleware on the Global Market Schema mapping based on ontologies UnifiedViews Identify new candidate concepts to be included in a controlled vocabulary RDF Graph Database Entity Extractor informs all incoming data streams about its semantics and links them PoolParty GraphSearch

12 12 Integrating data along the Linked Data Life Cycle

13 13 PowerTagging for SharePoint and PoolParty at a Glance On-premise: PowerTagging Server can be part of SharePoint farm s application server Hybrid scenario: PowerTagging Server can be both on-site or Azure located Integrations: SharePoint 2013 / 2016, Office 365 PowerTagging for SharePoint has been developed by Soitron Group

14 14 Autotagging & Manual Tagging Tags are added automatically based on PoolParty Entity Extractor

15 15 Autotagging & Manual Tagging

16 16 Tag Refinement Dialogue

17 17 Quick Filtering by tags

18 18 PowerSearch: Semantic Search for your SharePoint

19 19 PowerSearch: Introducing your own Knowledge Graph Entity-centric views and context information about your search term Additional search refiners Traversing the knowledge graph Highly configurable knowledge base Search, Learn, and Understand

20 20 Benefits PowerTagging Consistent tagging based on controlled vocabularies Automatic tag suggestions based on text analytics User-friendly enterprise taxonomy management Taxonomies kept in sync with Term Store PowerSearch Concept based search: autocomplete from taxonomy Automatic use of synonyms: get precise results Configurable search refiners: faceted search based on taxonomy hierarchy Include fact box for search term in search results: benefit from additional context information

21 21 Two Integration Scenarios Option 2: Concepts are derived from taxonomies, and any tag event is stored in a Graph Database to link all assets with concepts from the graph. Option 1: Concepts are derived from a taxonomy and tagging is stored together with the asset in the DAM/CMS DAM/CMS DAM/CMS PoolParty API PoolParty API LD Store Pool Party User4711 Pool Party Wed 3 May, DAM/CMS API

22 22 Maturity Model Roadmap for a more agile Data Governance Framework

23 23 GraphSearch over Integrated Data incl. SharePoint

24 24 Demo Link

25 25 How it works Employee database PoolParty Thesaurus Server PoolParty UnifiedViews Resumes Labour market statistics RDF Graph Database Now I can identify employees along many dimensions. PoolParty User PoolParty GraphSearch

26 26 Core Principle The Semantic Layer completes the Four-layered Data & Content Architecture

27 27 CONNECT Andreas Blumauer Director, PoolParty Software Ltd CEO, Semantic Web Company GmbH Semantic Web Company - and