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Knowledge-Based Semantification of Business Communications in ERP Environments Marios Meimaris and Michalis Vafopoulos MBA Thesis National Technical University of Athens University of Piraeus 2012. 1 st International Workshop on Engineering the Semantic Enterprise (ESE2012) - PowerPoint PPT Presentation
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Knowledge-Based Semantification of Business Communications in ERP Environments
Marios Meimaris and Michalis Vafopoulos
MBA ThesisNational Technical University of Athens
University of Piraeus2012
1st International Workshop on Engineering the Semantic Enterprise (ESE2012)The 13th International Conference on Web Information System Engineering (WISE 2012)
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New Business Intelligence• Information is increasingly dynamic and heterogeneous• Information flows are constantly changing form and direction• Faster lifecycles of data• Within corporate contexts:
– Internal sources (ERP databases, company knowledge, mobile phones etc.)
– External sources (Web 2.0, Semantic Web services, (Linked) Open Data etc.)
National Technical University of Athens - University of Piraeus
National Technical University of Athens - University of Piraeus
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External Sources – Social Media
•Rich dynamic layers of information, both inbound and outbound•Social media sales >$30bn by 2016, >50% of web sales•~-60% in marketing costs with the use of social media in 2012•29% of brands have used social networking sites to promote offers•Inefficiency of social media monitoring solutions, ignored and unexploited (e.g. 70% of product/service complaints are ignored by businesses)
*Source: https://www.gartner.com/it/page.jsp?id=2092217
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External Sources – (Linked) Open Data
• Open Data: the notion that certain kinds of data should be freely accessible on the web.
• Linked Data : representation as resource nodes that are interlinked with property edges that connect different datasets.
• No redundant data in companies’ internal databases => no management costs.
• No need to keep data updated => no curation costs.• Retrieval is easy to perform on-demand.• e.g. OpenCorporates.com provides open up-to-date information about
international corporate entities in machine-understandable, open formats (XML, RDF, JSON)
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External Sources – (Linked) Open Data
Source: http://dbpedia.org
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External Sources – Semantic Web• Organizations adopt Semantic Web standards and
knowledge representation formalisms in pursuit of knowledge-based collaboration.
• Builds bridges between remote and heterogeneous resources.
• Ontologies provide common semantic vocabularies, this way promoting interoperability between autonomous software agents.
• E.g. GoodRelations e-commerce ontology – Google, Yahoo!, BuyMore, OpenLink Software (among >10,000
businesses).– Publish or harvest offers described with GoodRelations terms– Find related products/services, identify competing companies,
strategies etc.
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Internal Sources – ERP Database• Enterprise Resource Planning (ERP) systems are
widely used as corporate software solutions.• Customer Relationship Management (CRM),
Human Resources (HR), Logistics etc., limited data management.
• Forms the information core of a business• Our implementation builds on OpenERP, a
widely used opensource ERP system with rounded capabilities.
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Internal Sources – Mobile Devices• Smartphones as data/ metadata live gathering points. • Aggregating and processing the gathered data recreates usage contexts in
communication environments.• The Android environment is equipped with an extensive SDK that makes
the above possible.• Within companies, communication networks share a common layer of
data exchange. The use of smartphones makes this layer identifiable and quantifiable.
• Three levels of information retrieval:
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Internal Sources – Mobile Devices• Communication Level information exhibits a high degree of dynamicity, vs.
relatively static Contacts Level and ERP database.• From voice calls and text messages (sms, emails, IM etc.) to calendar event
participations and social networking interactions.• Within the company AND between the company and the outside world => network
and sub-networks => reflection of actors’ behaviours• Rich taxonomy in the communications domain => diverse classifications.• Aggregation of all communication instances creates a descriptive communication
network. • Existing actor (employee, client etc.) profiles are enriched with communication
information on the fly => – pattern analysis of communication histories– application of informed communication strategies in future endeavours.
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Knitting it all together
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Knitting it all together• Data diversity with respect to form, structure, provenance and
scope.• The need of a common substrate leads us to the use of
ontologies in all levels (KM and SW). Benefits:– Better knowledge management, semantic structure and machine-
understandable meaning. Rule based reasoning, intelligent querying, interchangeable knowledge.
– Data-sharing and semantic web interoperation with others, through the use of reference ontologies and SW services.
• Reuse of existing ontologies for the data that is designed to be shared
• We created an ontology to represent communications, tasks and mobile usage context.
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Existing Ontologies• Friend-of-a-Friend (FOAF):
Describes people and organizations
• GoodRelations: Describes e-commerce offers
• SEMA4A: Contains basic terminology for describing threats and alerts
• Dublin Core: Provides vocabulary for describing non-functional properties of resources
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Local Ontology• Main contribution: Communications domain description• Fills the gaps between ontologies• Provides (domain-specific) descriptions for the Company, such as :
– Internal Structure– Employee and Department Hierarchy– Classifications of resources for internal reference
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Scenario
• We have applied the implementation to a threat-handling scenario that utilizes the above design.
• The implemented system is mostly concerned with internal sources
• Components that interact with external sources (except OpenCorporates) have not been implemented.
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Scenario• The system notifies with alerts when external information triggers threats
about offers of particular products/services. The implemented system handles the alerts in two ways: – Automatic creation of suggestions for handling a particular threat:
• Identification of subsets of employees that will handle the threat, • Assignment of particular clients (or sets of clients) to these employees, • Suggestion of dominant communication strategies (by pointing out communication
styles).
– Browsing environment with related knowledge and statistics for the particular threat, in order to assist managers in manually assigning threat handlers.
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Scenario• Past information drawn from Contacts and Communications Levels shared
among salespeople within the company, based on accessibility rules.• Overall context of the scenario is derived from the ERP system • The system automatically classifies market and clients in order to outline
the conditions• Results are made available to the salesperson and/or their manager(s)
w.r.t. ontology rules• Salespeople adapt their operational plan and communucation strategy
according to the results• The results of their modified strategies are quantified and measured
before they are made part of the shared knowledge, thus rebooting the cycle
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Threat Handling
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Technical Details• Programming Languages and Environments
– Java– Android SDK
• Semantic Data Management– Jena Framework (RDF conversion)– RDF (data storage)– OWL (ontology)– SPARQL (querying language)– OpenLink Virtuoso (quad store)
• Web Environment– PHP– JSP (JavaServer Pages)
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Data Extraction and Conversion•ERP data are extracted, converted and stored in the Virtuoso quad store as shown
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Data Extraction and Conversion• Android data are
retrieved, converted and stored in the quad store as shown in the first figure
• Direct contact data exchange from ERP to Android is shown in the second figure
• Common contacts level, synchronization of all platforms based on their role/permissions
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Screenshots
National Technical University of Athens - University of Piraeus
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Screenshots
National Technical University of Athens - University of Piraeus
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Screenshots
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Screenshots
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Screenshots
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Screenshots
National Technical University of Athens - University of Piraeus
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Issues - Advantages• Platform unification creates super-layers of information,
abundance of classifications• Better and less costly knowledge management due to
knowledge representation• Exploitation of mobile communications rich in information, both
within the company & the outside world• More intelligent in-house HR monitoring• Rule-based reasoning for dynamically changing roles and
permissions• Rules can be modified, activated and deactivated on demand,
and rule notation frameworks (e.g. SPIN) make them easily manageable
• Easy corporate data exchange
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Issues – Drawbacks• Costly development and maintenance of components for all platforms• Automatic capturing of threats from social media not mature enough,
need for manual monitoring• Semantic web services also not mature enough in e-commerce• Extraction of communications and external data is web-dependent• Need for deployment of centralized RDF store (difficult for mobile phones
to act as RDF stores/SPARQL endpoints etc.)
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Future Work
• Expand on the proposed components• Incorporate user-friendly and domain-specific methods for creating rule
sets• Create tools for assessment and analysis of communication patterns• Examine migration of ERP databases to RDF stores
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