Pricing model

Michael Kaschesky

Fusepool USPsfrom legacy data to Linked Data● e.g. extraction, entity recognition, interlinking

visualization of Linked Data● e.g. GUI, facets, graph browser

user feedback to Linked Data● e.g. user classification, user labeling, label prediction

OptionsSoftware as a Service (SaaS)

Platform as a Service (PaaS)

Data as a Service (DaaS)

Pricing Free - Freemium - Premium

Organizations

Documents SaaS

PaaSStorage

System

GUI

Utilities

Sourcing

PREFIX foaf: <http://xmlns.com/foaf/0.1/>SELECT *WHERE { ?person foaf:name ?name . ?person foaf:mbox ?email .}

DaaS

Cost driversCPU clock usage hours

Persistent storage levels

I/O requests, API requests

Data transfer (outbound)

CostsCost of storing a document?

Cost of one entity extraction?

Cost of one entity interlinking?

Cost of supporting one user?...

Cost of interlinking?

January February March April May June

800

400

Controlled testingFunctions & usage (e.g. interlinking)

Components/services (e.g. SILK, ECS)

Track cost factors (e.g. CPU, datastore)

Link resource use to cost factors

Calculation exampleOperation CPU use Storage Queries

Input 0.2 second 235 KB 10 SELECT

SILK engine 1.3 second

Output 0.1 second 4 KB 2 INSERT

ProblemNot there yet (e.g. FundingFinder)

Testing willingness to pay unrealistic

Identifying cost drivers unrealistic

> uncertainty about income & costs

ConclusionExploit technology, not end product

● pipeline to enhance legacy data● landscape viewer, graph browser● learn, update, predict framework

Business model

Michael Kaschesky

Patents analytics

positioned between Google Patents and patent consulting services

Technology intelligence

positioned between Google Trends and technology consulting services

Market intelligence

positioned between Facebook/ Criteo/ etc and marketing consulting services

Expertise intelligencepositioned across Facebook (private), LinkedIn/Technorati (private/work) and tools such as Science Citation Index/Arnetminer/biomedexperts

Content distributor

positioned between off-the-shelf data services (e.g. Factual) and ‘manual’ data curation services

Content/data distribution

Linked Data?Attribution ... is key to provenance … making all contributors to the data value chain visible.

Kingsley Idehen (OpenLink)

Attribution?No economy without attribution

Example: Creative Commons

Creativity wants to be recognized, then people exchange ideas

Data publisher

Data modeler

Data enrichment

Data user

Value

Value

Value Value€$¥

€$¥€$¥

Mission & strategyMission: communicate more effectively and efficiently

Strategy: open, integrated, and viable data infrastructure

Products

turn communication use cases into intuitively usable applications (apps)

Customers & partnersCustomers publish connected data

● communicate, inform, enable

Partners along the data value chain

● data providers, developers, users

Product featuresFusepool mobile app framework for displaying/entering data per facet

● facet is a particular aspect of the data relevant to the use case

Organizations

Documents

FacetsEntities

Product featuresFacet = basic core functions to display/enter data for use cases

App = combination of multiple facets to meet specific use case

Facets

Entities

Generic mobile app framework

Product accessCustomized solutions for Fusepool mobile app data framework

Online configurator for data sources, facets, display parameters

Swissdat's roleReuse/extend Fusepool (e.g. RDFizer, faceted/graph browsing, DLC)

Fusepool mobile app framework

Support open, integrated, and viable data infrastructure

ProfitabilityOrganic growth until proven

● customization > consulting fees● online configurator > service fees● own apps > sales income

Investors extend successful format