Semantic Enterprise Composite Offering

From MIKE2.0 Methodology

This Solution Offering currently receives Minor-to-Medium Coverage in the MIKE2.0 Methodology through the Overall Implementation Guide and SAFE Architecture, but Activities are missing and there are still many Supporting Assets still under development. In summary, the Solution Offering has guidance and usefulness for prototype and initial increment deployments, but has not yet been formulated to the point of proven, commercial readiness.

Contents 1 Introduction 1.1 Executive Summary 1.2 Solution Offering Purpose 1.3 Solution Offering Relationship Overview 2 Solution Offering Definition 2.1 Reference Concepts 3 Relevant Characteristics as a Composite Solution 4 Relationship to Solution Capabilities 4.1 Relationship to Enterprise Views 4.2 Mapping to Overall Implementation Guide 4.2.1 Phase 1 - Business Assessment and Strategy Definition Blueprint 4.2.1.1 Overall Business Strategy for Information Development 4.2.1.2 Organisational QuickScan 4.2.1.3 Initial Data Governance Organisation 4.2.1.4 Future State Vision for Information Management 4.2.2 Phase 2 - Technology Assessment and Selection Blueprint 4.2.2.1 Technology Requirements for the Semantic Layer 4.2.2.2 Ontology and Vocabulary Design 4.2.2.3 Strategic Non-Functional Requirements 4.2.2.4 Future-State Logical Architecture and Gap Analysis 4.2.3 Phase 3 - Information Development Roadmap and Foundation Activities 4.2.3.1 Detailed Business Requirements 4.2.3.2 Transition of Legacy to Semantic Data 4.2.3.3 Prototype the Solution Framework 4.2.4 Phase 4 - Design Increment 4.2.4.1 Information Security Design 4.2.4.2 Data Integration Logical Design 4.2.4.3 Design for User Collaboration 4.2.4.4 User Interface Design 4.2.5 Phase 5 - Develop, Test & Deploy Increment 4.2.5.1 Technology Backplane Modifications 4.2.5.2 Testing Activities 4.2.6 Updates to the Implementation Guide 4.3 Mapping to the SAFE Architecture Framework 4.4 Mapping to the Information Governance Framework 4.5 Mapping to Supporting Assets 4.5.1 Architecture, Design and Development 4.5.2 Implementation Frameworks 4.5.3 Products and Tools 4.5.4 Selected External Assets 4.5.5 Assets Under Development 4.5.5.1 Kinds of Assets 4.5.5.2 Revisions to Existing Assets 4.5.5.3 Priority New Assets Under Development 4.5.5.4 Other Specific Work Products in-Progress 5 Relationships to Other Solution Offerings 5.1 Composite Offerings 5.2 Core Offerings 5.2.1 Business Intelligence 5.2.2 Information Asset Management 5.2.3 Access, Search and Content Delivery 5.2.4 Enterprise Data Management 5.2.5 Enterprise Content Management 5.2.6 IM Strategy, Architecture and Governance 6 Extending the Open Methodology 6.1 Relation to Solution Offerings 6.1.1 Composite Offerings 6.1.2 Core Offerings 6.1.3 Other Assets 6.2 Possible Effects on Governance or Policy 6.3 Key Unknowns, Uncertainties or Information Gaps

Introduction

The Semantic Enterprise Solution Offering provides a framework -- actually, a layer -- for the enterprise to establish coherence, consistency and interoperability across its information assets. Applicable information assets may range fully from structured to unstructured (text and document) sources. The methodology of this Offering is inherently incremental, is layered onto existing capabilities and resources, and is flexible to accommodate expansions in scope or new learning and new structural understandings. As implementation proceeds and extends across the enterprise, there are exciting prospects to shift the locus of knowledge management and tools from vendors and the IT function to practicing knowledge workers. Real prospects exist from this Offering to overcome decades of frustration in breaking down information silos within the organization, in the process enabling more effective information sharing and interoperability. This approach is generally based on the languages and techniques of the semantic Web, as distilled and refined by the pragmatic lens of business requirements.

Executive Summary

The Semantic Enterprise Offering provides an incremental approach to bring interoperability and common understandings regarding information to the enterprise. The Offering uses an "open" style (not in the sense of free or open source, but in the sense of an "open world" in which there are unknowns and incomplete information). An "open" Semantic Enterprise is one that adopts the languages and standards of the semantic Web, including RDF, RDFS, OWL and SPARQL and others, and applies them to the issues of information interoperability, preferably using the best practices of linked data. Some principles of Web-oriented architectures are also suggested, but not absolutely essential. The framework is also highly useful for incorporating existing information resources into the enterprise.

There is a gradient — or spectrum — of possible styles in what it means to be a "semantic enterprise." The more traditional and familiar style is comprehensive, complete and “engineered” in its approach. This approach may also not strictly adhere to semantic Web languages and standards. The second "open" style, the basis of this Offering, is more adaptive and incremental. The applicability of either approach — or any gradient between — is a function of objectives, circumstances and use cases.

This Semantic Enterprise Offering is purposefully geared to knowledge management, information discovery and information management functions. It is also purposefully designed as an integration layer over existing information assets and infrastructure.

See further the standalone executive overview.

Solution Offering Purpose

The Semantic Enterprise Offering is a Composite Solution. As such, it is by nature bridging or cross-cutting across many other MIKE2.0 offerings (see more fully the Relevant Characteristics section below). Though many of the assets used by this Offering already exist, its reach touches a majority of other offerings, the exact potential interactions of which are still being defined. There are also many potential assets not yet described in MIKE2.0 nor yet with demonstrable case studies or best practices.

Nonetheless, sufficient assets and elements exist for this Offering to enable its deployment at departmental, prototype, or proof-of-concept levels. There are both proprietary and open source options across the range of existing elements.

The inherent open, incremental and extensible nature of this Offering means that scope and risks can be readily managed, with subsequent expansions in scope, sophistication or depth accommodated without adverse impact or modifications to prior efforts.

Solution Offering Relationship Overview

The Semantic Enterprise Offering is a layer bridging existing Core Solutions, and with many interactions with other Composite Solutions. The offering "sits on top" of existing information, components and assets. This role is in keeping with the purpose of the Offering to integrate and provide interoperability. The essence of the layer is to provide the semantics and common data model based on RDF that enables all existing information sources and formats to be related.

This fundamental role means that all of the solutions in this diagram could potentially be highlighted in red. However, since the basic deployment approach of this Offering is incremental and can be targeted in scope, it is more appropriate to show it as a separate, integrative layer.

Solution Offering Definition

Many enterprise information systems, particularly relational ones, embody a closed world assumption that holds that any statement that is not known to be true is false. This premise works well where there is complete coverage of the entities, such as the enumeration of all customers or all products.

Yet, in most areas of the real (”open”) world there is no guarantee or likelihood of complete coverage. Thus, under an open world assumption the lack of a given assertion or fact does not imply whether that possible assertion is true or false: it simply is not known. An open world assumption is one of the key factors that defines the open Semantic Enterprise Offering and enables it to be deployed incrementally. It is also the basis for enabling linkage to external (often incomplete) datasets.

Fortunately, there is no requirement for enterprises to make some philosophical commitment to either closed- or open-world systems or reasoning. It is perfectly acceptable to combine traditional closed-world relational systems with open-world reasoning. It is also not necessary to make any choices or trade-offs about using public v. private data or combinations thereof. All combinations are acceptable when the basis for integration is an open-world one.

When this logical basis is matched with the simple, but flexible and expressive Resource Description Framework (RDF) data model, a very powerful basis for data integration and interoperability across a diversity of sources and systems emerges.

RDF is expressed as simple subject-predicate-object “triples”. They are how data can be represented and built up into more complex structures and stories. A triple is a “statement” and is the basic “fact” or asserted unit of knowledge in RDF. Multiple statements get combined together by matching the subjects or objects as “nodes” to one another (the predicates act as connectors or “edges”). As these node-edge-node triple statements get aggregated, a network structure emerges, known as the RDF graph.

RDF triples can be applied equally to all structured, semi-structured and unstructured content. By defining new types and predicates, it is possible to create more expressive vocabularies within RDF. This expressiveness enables RDF to define controlled vocabularies with exact semantics. These features make RDF a powerful data model and language for data federation and interoperability across disparate datasets. It is also a model that allows starting domains to be expanded in either scope or expressiveness in a building block manner.

Similar to ETL options, there are also a wide variety of "RDFizers" that enable virtually any existing data format from diverse sources to be expressed as RDF. The differences in semantic meanings and relationships from different sources are often written in the RDF ontology language, OWL. This combination of expressive languages and vocabularies and converters means that existing information assets, such as industry standards, XML, MDM, relational schema or corporate taxonomies, can now be related and combined. The mappings of these structures in the resulting ontologies thus become the means to codify the enterprise’s circumstances into an actionable set of relationships bridging across multiple, existing information assets.

There are, of course, key deployment and management factors for the Semantic Enterprise Offering, as with similar information management offerings, as described in the related Guiding Principles for the Open Semantic Enterprise. These principles also describe some other important aspects, such as linked data or Web-oriented architecture. But it is really the unique combination of open-world approach and the RDF data model and its semantic power that provide the distinctive differences for this Offering.

Clearly, the nature of this Offering in semantics, relationships, and integration make it most suited for applications in knowledge management, business intelligence and information discovery. Yet as the Offering's potential relationships with most of the MIKE2.0 solutions shows, any circumstance involving the need to combine or interoperate information could potentially benefit from this Offering.

Reference Concepts

Here are some of the important reference concepts related to the Semantic Enterprise:

Controlled Vocabulary Concept Data Definition Metadata Data Dictionary Concept Data Mapping Description Logics Concept FOAF Concept Folksonomy Concept

Metadata Concept OWL Concept Ontology Concept Open World Assumption Concept RDF Concept RDFizer Concept REST Concept

Semantic Enterprise Concept Semantic Web Concept Social Networking Concept Tagging Concept Taxonomy Concept Web-oriented Architecture Concept XML Concept

Relevant Characteristics as a Composite Solution

Information integration with meaning, of course, is nearly universal to the objectives of MIKE2.0. Because of this, there are significant overlaps of the Semantic Enterprise Offering with other Core or Composite Solutions.

As the diagram shows, more than half of the Core Solutions in MIKE2.0 have some degree of interaction with the Offering, about one-quarter of which are very important (major). Similarly, there are key interactions with most of the Composite Solutions as well.

In these regards, the Semantic Enterprise Offering is perhaps the best exemplar within MIKE2.0 for a Composite Solution.

Relationship to Solution Capabilities

This section now begins relating the Offering to the specific aspects of MIKE2.0.

Relationship to Enterprise Views

The Semantic Enterprise Offering is a potential game-changer in that it offers new ways to directly involve practitioners into most aspects of the Information Development process, while simultaneously providing a vehicle for finally bringing effective information federation to the enterprise. But the transition to ontology-based information management and ontology-driven applications is in its mere infancy. For these latent potentials to be realized, much innovation, development, testing and accumulation of best practices will be required. This transition to a more democratized basis for the information management function will involve many aspects of people, process, organisation and technology.

Mapping to Overall Implementation Guide

There is much substance in the Semantic Enterprise Offering applicable to The 5 Phases of MIKE2. Where major questions and uncertainties reside is in how subsequent increments may work and play out. This is particularly important for this Offering given its inherent incremental nature. Also, because of this nature, this Offering is well suited to smaller initial increments with fast phase transitions.

The Programme Review activity is important for assessing that the Offering is aligning with overall strategy and the methodological approach. It should be performed after each phase or more frequently if appropriate.

Phase 1 - Business Assessment and Strategy Definition Blueprint

Phase 1 tends to emphasize awareness, strategy development, vision, planning and organization. For the Semantic Enterprise Offering, this phase is critical for targeting and bounding the first deployment, as well as for setting key organizational and information development objectives.

Overall Business Strategy for Information Development

In the Overall Business Strategy for Information Development activity, the strategic business initiatives are defined in the context of the semantic information requirements. For Semantic Enterprise engagements, this activity defines the scope and sequencing of information to be inter-related and collaboratively mapped.

Organisational QuickScan

The Organisational QuickScan for Information Development is about trying to quickly understand the organisation’s current environment and to begin to establish the vision for where it would like to go. This process sets the ground state from which the various objectives in subsequent phases and increments are based. QuickScan assessments are a core part of this activity as they not only provide a rich starter set of questions but also provide maturity guidelines for organisations. The gap between the current-state assessment and the envisioned future-state gives as early indicator of the progress for the overall programme.

Initial Data Governance Organisation

The Initial Data Governance Organisation is focused on establishing the roles and responsibilities throughout the deployment programme. Communications models, frequencies and methods are also established, which are important to possible issue resolution and prevention throughout the implementation process. The data governance organisation that is established at this point will become more sophisticated over time.

Future State Vision for Information Management

The Future State Vision for Information Management is an important activity for defining the strategic objectives, scope and architecture for the Semantic Enterprise. As this typically involves a large number of different conceptual components and interactions, a systematic approach is important. This activity also defines the future-state business processes for semantic information management. Implementation of Semantic Enterprise techniques and technologies will introduce fundamental changes to business process.

Phase 2 - Technology Assessment and Selection Blueprint

Phase 2 tends to emphasize functional and non-functional analysis, architecture development, policies, standards, and initial component and application selection.

Technology Requirements for the Semantic Layer

Using the Layered Semantic Enterprise Architecture for guidance, technology requirements for the semantic layer are defined in relation to the existing SAFE Architecture and Technology Backplane, and in relation to the goals of Information Development and Infrastructure Development. This activity is used to define the capabilities that are needed for the strategic implementation of this Offering.

This activity gets expressed as the Technology Requirements for the Semantic Layer. At least for initial increments and to lower risk, requirements can be developed quickly if there is an emphasis on the use of open and common standards. Through this approach, strategic requirements do not need to be defined for a multi-year programme as new technologies can be more easily “plugged in” during future release cycles, reducing the amount of time required during the strategy.

Ontology and Vocabulary Design

Ontology and Vocabulary Design, which builds from Metadata Driven Architecture, sets the high-level design goals and management-level architectural framework for what existing information assets will be exposed to the semantic layer, and what major ontologies and instance record vocabularies will be put in place to support that aim. A critical aspect is to identify existing semantic assets in the enterprise (such as schema, taxonomies, industry standards, controlled vocabularies, MDM reference systems, and so forth) that can readily contribute prior efforts in common language. Another key aspect is to identify external vocabularies and ontologies that may contribute to the effort as well.

Though not yet implemented at this phase, other high-level objectives for the ontologies are also included in the design. These additions are from the standpoint of best practice requirements that will enable the resulting ontologies and information structures to provide the input to ontology-driven applications.

Another design aspect is to define the stakeholders and then the goals and mechanisms by which these stakeholders can collaborate and provide guidance to the overall ontology and vocabulary efforts. These efforts begin with assembly and formulation, and then continue with expansion, modifications and refinements.

It is important to get ontology and vocabulary management practices in place from the onset. As Phase 2 involves strategic technology requirements and product selection, the implementation team may still lack sufficient tools. Therefore, projects may need to take a tactical approach in the early stages.

Strategic Non-Functional Requirements

Strategic Non-Functional Requirements for the Semantic Enterprise are defined at a overarching level in this activity. For this Offering to be effective, there must a significant focus on understanding, role, performance and ability to scale to meet future business volume growth requirements. Users will expect the solution to be easy to use from their experience with sites on the public Internet and a quick capturing of requirements at this time will help shape the design in later stages. Note that these requirements should be done quickly – getting a working system in front of users and re-working through prototyping is a much more effective method for meeting usability requirements.

Future-State Logical Architecture and Gap Analysis

The Future-State Logical Architecture and Gap Analysis builds on the conceptual architecture that is already defined and takes it to the level of detail required to make strategic technology decisions. A gap analysis can then be conducted between the current-state and future-state to determine which technologies can be re-used.

Phase 3 - Information Development Roadmap and Foundation Activities

Phase 3 tends to emphasize definitions of business requirements and architecture, plus budgets and schedules. Initial prototypes are generally rolled out in Phase 3. Within Phase 3, the scope of the solution for a specific increment is defined and the overall content model begins to take shape.

Detailed Business Requirements

When developing the Detailed Business Requirements for this Offering, the focus is on the scope and priority of information deserving interoperability attention, and the collaborative means by which the semantics for this federation occurs. Outcome measures appropriate to the enterprise need to be defined.

Transition of Legacy to Semantic Data

The essence of the Semantic Enterprise Offering is to provide an interoperability layer over existing information assets. The Semantic Data Conversion Roadmap provides the plan for which sources are to be converted, how they are to be translated, and with what tools. The roster of sources to be transitioned depends on the specific increment at hand.

Prototype the Solution Framework

The activity to Prototype the Solution Framework helps to rapidly develop the solution. The prototype progressively builds out the overall functionality of the solution and the semantic layer, with all component parts linked and operating. If the prototype is done effectively some of the formalisation of the design activities in Phase 4 may be unnecessary.

Phase 4 - Design Increment

Phase 4 tends to emphasize integration and enterprise-wide implications, more fully developed framework designs, and deployment-grade interfaces and performance.

Information Security Design

Information Security Design defines which information can be seen by users within the collaborative environment. The most important aspects of security design relate to how information is accessed and who can edit content. Group-based access control is typically used to implement security rules. For initial prototypes or in first increments, interaction here may be minor.

Data Integration Logical Design

Data Integration Logical Design is extended in this Offering to include the schema and instance logic splits recommended to implement the semantic layer. This activity provides the ontology(ies) definitions, contributing datastores, and the specific mapping framework to expose that information at the interoperability layer.

Design for User Collaboration

User Collaboration Design provides the mechanisms by which users and communities of interest can provide input into the logic layer (ontologies plus instances and attributes) desired to meet interoperability objectives. It is the activity that defines how users will interact with one another, how internal and external assets will be brought together in the collaborative environment and how users may specifically classify content.

User Interface Design

The User Interface Design activity defines the front-end interface in which a user will interact with the applications layer in the architecture. Certain new capabilities in information navigation and discovery need to be accommodated. For a successful Semantic Enterprise Offering, these interfaces must be intuitive, simple to use, and conforming to modern Web practice.

Phase 5 - Develop, Test & Deploy Increment

Phase 5 tends to emphasize the first meaningful full increment deployment, with subsequent testing and refinement for later interactions or continued scale-up.Through development, testing and deployment activities, the prototype solution is hardened and implemented into production.

Technology Backplane Modifications

The Technology Backplane Development activity covers the development of integration and information management components for the semantics layer. This includes development of interfaces, Web components and security technologies.

Testing Activities

Depending on the complexity of the solution, different testing activities will be required although testing is generally not complex. Functional Testing and some level of System Integration Testing will be required at a minimum; Stress and Volume Testing (SVT) and User Acceptance Testing (UAT) are also important. Integration to the outside world may also require some specialized testing focused on security, interoperability, performance and usability.

Updates to the Implementation Guide

While the Overall Implementation Guide provides many of the key activites for this Semantic Enterprise Offering, it is also clear that many gaps and unknowns remain. As these are tackled and refined in specific engagements, this guide needs to be updated and refined on an ongoing basis. The updated guide and related Offering documents will be expanded both respect to specifics and scope.

A continuing challenge -- because of its newness, use of RDF data model, basis in the open world approach, and perhaps past misconceptions -- is to explain the nature and benefits of the semantic enterprise to key decisionmakers. As an enhancement to existing information assets, adopting the semantic layer is a strategic decision for the enterprise, and one that may require different explanatory documents and methods.

Mapping to the SAFE Architecture Framework

Given its layered role, this Offering tends to act more as a subsequent set of functions or middleware with respect to the standard SAFE Architecture. This is reflected in the Layered Semantic Enterprise Architecture, as the diagram shows. Most of the existing SAFE architecture resides in the "Existing Assets" layer. The specific aspects of the Semantic Enterprise Offering is then sandwiched in the so-called "Access/Conversion" and "Ontologies" layers in the diagram. These capabilities do, however, also potentially greatly affect the applications layer, as is more specifically discussed below.

Mapping to the Information Governance Framework

The starting basis here is the Networked Information Governance framework, which brings a collaborative aspect to a traditional Information Governance approach. This extension (Composite Solution) makes it easier to collaborate on the definition and implementation of common standards, methods and architecture. It was designed to combine the standard Information Governance offering with Enterprise 2.0.

One of the keys to a successful Semantic Enterprise implementation is that governance can be in place, without it feeling restrictive. This Offering is enhanced via a number of behaviors not usually encouraged in the context of more traditional models; limiting some of these behaviors with governance controls that are unnecessarily restrictive will result in a diminished solution.

However, more than this composite understanding, there are still further challenges with a Semantic Enterprise Offering, not fully met in any other offering. For example, there are governance challenges shared with offerings in Information Management Strategy, Information Sharing, Metadata, Taxonomy, Cataloging and Classification, and Reference and Master Data Management. As the next-to-concluding section to this Offering notes, there may perhaps be a different threshold of governance that may appear with this specific Offering.

Mapping to Supporting Assets

As an emerging Offering, the Semantic Enterprise solution has a relative paucity of Supporting Assets at present. Notes regarding existing or proposed ones are provided via Asset category below.

Architecture, Design and Development

The relationship with Guiding Principles for the Open Semantic Enterprise was noted above. Here are some of the other existing MIKE2.0 design assets related to this offering:

• Current-State External Data Sources Assessment
• Guidelines for Using an Off-the-Shelf Data Model
• Prototype the Solution Architecture
• Contrasting Styles for the Semantic Enterprise
• Conceptual Framework for Enterprise Data Management
• Information Standards (with necessary expansion).

Also the information on Related Concepts (above) should be consulted.

Implementation Frameworks

At present, aside from the guidelines in this Offering and its related documents, the only developed implementation framework is the open source methodology Open SEAS Framework. Open SEAS (Semantic Enterprise Adoption and Solutions) provides guidance to existing tools (most open source, though some proprietary) and a generalized architecture and adoption framework based on this Offering. It follows the same Guiding Principles for the Open Semantic Enterprise and the Layered Semantic Enterprise Architecture.

Products and Tools

These supporting assets are still being documented. See further the section on Assets Under Development below.

Selected External Assets

See the Related Links Semantic Enterprise.

Assets Under Development

As a new Offering in an emerging area, considerable further assets are presently under development.

Kinds of Assets

There are many aspects that make for a complete offering, some of which are somewhat in process for the Semantic Enterprise Offering, while others need more attention and experience. These various additional assets include methods and papers, templates, capabilities, software, plans, and project examples.

Revisions to Existing Assets

A number of existing MIKE2.0 component documents need to be reviewed and updated as appropriate. These include the:

• Return on Investment of Information Assets, which needs to be expanded with benefits from interoperability, information connectivity (graph structures), and ontology-driven applications.
• Data Integration Logical Design, which needs to be extended include the schema and instance logic splits recommended to implement the semantic layer.
• User Collaboration Design, which should be extended to include mechanisms by which users and communities of interest can provide input into the logic and ontologies
• Technology Backplane Development, which needs to be extended to reflect semantic technologies such as triplestores, RDFizers, information extraction, and ontology managers/editors.

Priority New Assets Under Development

There are also some missing components that need to be added to MIKE2.0:

• The Layered Semantic Enterprise Architecture, which provides the guidance and technology requirements for the semantic layer, as defined in relation to the existing SAFE Architecture and Technology Backplane, and in relation to the goals of Information Development and Infrastructure Development.
• The Ontology and Vocabulary Design, which acts to replace/supplant the Metadata Driven Architecture.
• The Technology Requirements for the Semantic Layer.
• The Semantic Data Conversion Roadmap component, which provides the guidance for exposing information assets at the semantic layer.

Other Specific Work Products in-Progress

There are existing background papers and development projects that are leading to a suite of new MIKE2.0 works for this Offering. The topics underway include (with final titles to be decided); Adaptive Ontologies; Benefits of the Semantic Enterprise; a variety of Case Studies; some product descriptions; Dataset Authoring Using Spreadsheets; Description Logics and Data Organization; Domain Ontologies; Executive Overview of Ontologies; Executive Overview of RDF; Executive Overview of the Semantic Enterprise; Integration of Semantics in Metadata Management; Ontology Building Tools; Ontology-driven Applications; Open World Assumption; RDF as a Canonical Data Federation Model; Semantic Web Tools Listing; Organizing Upper Level Ontologies; and Web-oriented Architecture.

These are tentative, and will be prepared in MIKE2.0-compliant modes.

Relationships to Other Solution Offerings

This Offering may be interpreted as potentially affecting virtually all aspects and offerings of MIKE2.0. For example, in the Access, Monitoring and Control Solution Offering, the Semantic Enterprise Offering could be used to develop the access methods themselves or could add to the scope of what needs to be controlled.

Given this potential, a more useful way to relate the Offering to the various MIKE2.0 solutions is to assess a current implication or interaction or one that is quite significant in scope or degree. These interaction levels are denoted as 'Relevant' and 'Major Relevancy' (major), respectively, as shown on this mapping to the Core and Composite Solutions presently in MIKE2.0. So, while perhaps, interactions could be shown with every box, only those with the stronger interactions are shown:

The specific solutions and their interaction relationships follow.

Composite Offerings

The Semantic Enterprise Offering has interactions with these Composite Offerings, with all of the interactions being major.

• Information Management Strategy - provides an integrated strategy for all types of data and content across the orgnanisation. It effectively brings together the Enterprise Data Management and Enterprise Content Management Strategy Solution Offerings into a single offering.
• Data Driven IT Transformation - a meaningful, cost-effective Business and Technology change process can be achieved much more effectively by taking an Information Development approach and that the MIKE2.0 methodology can be an integral part in a successful transformation.
• Information Sharing - enables the sharing of information across departmental, organisational and even national boundaries.
• Enterprise 2.0 - brings the collaborative and social computing concepts associated with Web 2.0 into the enterprise; it has an emphasis on collaboratively built content and easily classified information as users find it.
• Networked Information Governance - brings a collaborative aspect to the traditional Information Governance approach; it makes it easier to collaborate on the definition and implementation of common standards, methods and architecture.

Core Offerings

Interactions with Core Solutions follow. Relationships with major relevancy are marked as [major].

Business Intelligence

• Operational Business Intelligence - a mechanism to be able to accurately manage the business to make fact-based analytical decisions.

Information Asset Management

• Information Lifecycle Management - the storage, archiving, recovery and destruction of data and content.
• Metadata, Taxonomy, Cataloging and Classification - the necessary descriptors to turn data and content into information. [major]
• Information Management Workflow- tracks, manages and optimizes the flow of information across the federated enterprise (but, mostly a stub in its current write-up).
• Information System Usability- a mechanism to make our information systems better from a user perspective. Improved Information System Usability is achieved through better semantic understanding, ease of access and manipulation and delivery of a system that is simple for the end user (but, mostly a stub in its current write-up). [major]

Access, Search and Content Delivery

• Enterprise Portals and Information Delivery- a mechanism to deliver integrated information to users in an easy-to-understand format (mostly a stub).
• Enterprise Search - an approach for accessing information held in a variety of sources across the enterprise through a simple text query and easy-to-use web interface.

Enterprise Data Management

• Data Warehousing - an approach for delivering a Data Mart, an Enterprise Data Warehouse or variants of these systems that are more departmentally-focused, operational in nature or application-specific.
• Reference and Master Data Management - an approach for managing master data such as customer, product, employee, locality and partner data and its complementary reference data such as product codes, country codes and foreign exchange rates. [major]
• Customer Data Integration - an approach for integrating customer data across a highly federated environment where it may be stored in dozens or even hundreds of systems. This Offering is a subset of Master Data Management
• Data Quality Improvement- an approach for addressing Data Quality issues across a number of dimensions, such as data accuracy, integrity and completeness.
• Data Migration - techniques for handling different types of Data Migration scenarios, from simple migrations to complex application co-existence scenarios.

Enterprise Content Management

• Knowledge Management (collaboration, knowledge capture, communities of interest) - an approach for building and maintaining content that is developed in a collaborative, user-driven fashion. [major]
• Web Content Management- techniques for building, managing and delivering web-based content to the internet. [major]

IM Strategy, Architecture and Governance

• Information Management Center of Excellence - defines varying organizational structures that can most effectively handle the complexities of integration and information management across the whole of the organization.
• SOA, EII and Model Driven Architecture - an approach for implementing advanced architecture techniques to increase reuse, reduce complexity and improve software quality across the Information Management environment (stub; may not be best to be conjoined). [major]
• Enterprise Data Management Strategy - a method for an organization to define its strategic approach to EDM and how it will be implemented. [major]
• Enterprise Content Management Strategy- provides a method for an organization to define its strategic approach to ECM and how it will be implemented.
• Enterprise Information Assessment - provides an approach for measuring information quality and corresponding information value. It is primarily an assessment of the current-state but also provides recommendations on the benefits of moving to an improved future state. [major]

Extending the Open Methodology

By their nature, Composite Solutions cut across boundaries and may represent new thinking or new boundaries. As they are tested and deployed, such Offerings may raise challenges to existing ways of doing business, suggest or require new Offerings, or otherwise raise risks or unknowns.

Relation to Solution Offerings

Of course, this Semantic Enterprise Offering extends the methodology to a considerable extent and has potential systemic effects across MIKE2.0. In this section, these possible extensions are noted by solution area.

Composite Offerings

In general, all of the Composite Solutions for which there are interactions need to be investigated closely and appropriately annotated. In some cases, this might mean the addition of an entirely new Composite offering.

For example, while there are close overlaps for ontology-driven applications and adaptive ontologies with the Data Driven IT Transformation offering, it may be preferable to not commingle the two. Data-driven IT transformation does not depend on semantic technologies, though is likely a strongly supporting offering for how ontologies may themselves transform the organization.

Core Offerings

The implications of the Semantic Enterprise Offering has both direct effects on existing Core solutions, and may also warrant a few additional Core offerings. These potential extensions include:

• Operational Business Intelligence - this offering may benefit from adding connections and facts from semi- and unstructured sources.
• Optionally, it may be desirable to add a new Core solution in the specific area of narratives and unstructured content, and the role and use of information extraction.
• Information Lifecycle Management - this offering may need to be expanded to accommodate triplestores (RDF data storage systems), ontologies and versioning.
• Metadata, Taxonomy, Cataloging and Classification - this entire area has major overlap and interactions with semantic technologies and the Semantic Enterprise Offering. Again, because of the similar arguments in the BI arena, this may warrant preparation of a separate Core offering.
• Information Management Workflow- this offering would benefit from the addition of considerations related to ontology development, input from COIs and knowledge workers, and the means to collect and convert internal and external information assets.
• Information System Usability - semantic technologies will produce new options and opportunities in information visualization, ontology-driven applications, and navigation of information spaces.
• Enterprise Portals and Information Delivery- a much higher degree of information interconnection and graph-based information models may have a transformative effect on traditional enterprise portals, as well as to present unique information presentation mechanisms.
• Enterprise Search - early forays into faceted search have shown some of the potentials and impacts from semantic approaches on search, but inferencing and the potential of graph models takes the concept to an entirely new plane. Moreover, there will be significant new augmentations in browsing and navigation emerging. As with some of the other Core offerings, it may be best to develop a separate Core solution for this particular area
• Data Warehousing - there are clearly overlaps in function from the composite Semantic Enterprise Offering on the data warehousing function. However, given the precise understanding of data warehousing and its legacy, it is likely best to formulate an alternative Core solution specific to semantic information federation.
• Reference and Master Data Management - the continued trend to multi-domain MDM strongly suggests semantic approaches as a next enterprise-wide option in this transition.
• Data Quality Improvement- semantic capabilities offer entirely new ways to view the data quality challenge via the application of iInference tests, ability to identify inconsistencies and data/conceptual gaps, and other unique approaches to quality assurance/quality control (QA/QC).
• Data Migration - the sense and scope of this current offering may benefit from the use of minor, simpler approaches based on RDF, the inclusion of RDFizers, and the more extensive incorporation of external datasets.
• Knowledge Management- the possible extensions in the KM offering are major, particularly in regard to the impact and implications of ontologies and open-world approaches. Indeed, relations with KM appear to be especially problematic in the sense of a Core offering similar to other core offerings.
• Web Content Management- the greater use of external content/information and the possible ingest and/or publishing of linked data and use of Web-based endpoints have major potential interactions and extensions with this offering.
• Information Management Center of Excellence - extensions to this offering are relatively minor, and mostly relate to ontology/vocabulary development and management.
• SOA, EII and Model Driven Architecture - the extensions here could be major, and may warrant a separate Core offering related to REST and Web-oriented architectures (WOA).
• Enterprise Data Management Strategy - it would seem that adoption of the RDF data model and the implications of graph structures would affect this Core offering greatly. Unlike some of the other major interactions, it may not be appropriate to establish a parallel offering to this one, but with a semantic emphasis. Rather, this Core offering likely requires extension and modification to continue its role as an integrative focus.
• Enterprise Content Management Strategy- the interactions with this offering appear mostly minor, and involve the incorporation of semantics and related with ECM strategy.
• Enterprise Information Assessment - the relation of this offering to the Semantic Enterprise Offering may range from minor to major. A separate offering with a semantic thrust may be warranted for where semantics are being seriously considered for adoption and they are also being employed in the assessment function.

Other Assets

See the section on Assets Under Development above for a listing of other assets slated to extend the MIKE2.0 methodology.

Possible Effects on Governance or Policy

The adoption of semantics and embracing the Semantic Enterprise Offering is basically a people issue. More fundamentally, as adopted, the process of information development can shift radically. Adaptive ontologies and ontology-driven applications will see a shift in roles and responsibilities away from IT to knowledge workers themselves. This shift acts to democratize the information development and KM function and flatten the organization.

The skills needed to create these adaptive ontologies are logic, coherent thinking and domain knowledge. That is, any subject matter expert or knowledge worker worth keeping on the payroll has, by definition, the necessary skills to contribute to useful ontology development and refinement. The possible effects on governance or policy from these changes are, frankly, unknown. But, they are likely to be far-reaching and perhaps of a qualitatively different nature than past approaches.

The interaction of these potential changes with social technologies and emerging collaboration mechanisms and techniques promises still further far-reaching changes. This entire area likely warrants new thrusts within the MIKE2.0 methodology itself.

Key Unknowns, Uncertainties or Information Gaps

The Semantic Enterprise Offering provides some important new benefits not obtainable from prior approaches and technologies. And, the best news is that these advantages can be obtained incrementally and at low risk and cost while leveraging prior investments and information assets.

However, much, much is unknown regarding key aspects of this Offering:

• What are the priority application areas which promise the greatest return on investment?
• What are best practices for adoption and technologies across the entire Offering stack?
• Many tools and techniques are still legacies and outgrowths of the research and academic communities. How can these be adopted and modified to meet enterprise standards and expectations?
• What are the "best" ontology and vocabulary building blocks upon which to model and help frame the enterprise's interoperability needs?
• What are the most cost-effective strategies for leveraging existing information and infrastructure assets, while transitioning away from them where appropriate?

Despite these questions, emergence is the way complex systems arise out of a multiple of relatively simple interactions, exhibiting new and unforeseen properties in the process. RDF is an emergent model. It begins as simple “fact” statements of triples, that may then be combined and expanded into ever-more complex structures and stories. As an internal, canonical data model, RDF has advantages for information federation and development over any other approach. It can represent, describe, combine, extend and adapt data and their organizational schema flexibly and at will. Applications built upon RDF can explore and analyze in ways not easily available with other models.

Combined with an open-world approach, new information can be brought in and incorporated to the framework step-by-step. Perhaps the greatest unknown in an ongoing transition to become a semantic enterprise is how an inherently incremental and building-block approach might alter prior practices and risks across the entire information management spectrum.