DataGraft Platform: RDF Database-as-a-Service

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The document summarizes the DataGraft Platform, an open data platform that provides an RDF database-as-a-service (DBaaS). The platform transforms tabular data into RDF and publishes linked data services instead of static datasets. It uses Amazon Web Services for its cloud architecture with Ontotext GraphDB as the RDF database engine running in Docker containers. The platform is designed to be elastic, highly available, cost efficient, and securely isolate multi-tenant databases. It provides a standards-compliant SPARQL endpoint and linked data interface that can be used with various third-party querying and visualization tools.

Technology

DataGraft Platform: RDF Database-as-a-
Service
Open Data Workshop @ Oslo
July 2nd, 2015
http://dapaas.eu/
Marin Dimitrov, Ontotext (Bulgaria)

The Role of a RDF DBaaS
4
Grafter Grafterizer
RDF DBaaSOpen Data Portal
• Transform tabular data into RDF
• Publish (Linked) data services,
instead of static datasets
• Lower-cost & easier data
publishing process

RDF DBaaS Requirements
• Elastic
– dynamically adapt to growing data & query volumes
• High availability & resilience
– no SPFs, “graceful degradation” upon failures
• Cost efficient
• Host a large number of data services (databases)
– But probably of low/moderate data & query volume
• Security & isolation of the multi-tenant databases
5
Not easy to
achieve all three!

Cloud Architecture (AWS)
• AWS based
– Network storage, compute & auto-scaling, load
balancing, integration services, …
• Ontotext GraphDB as the RDF DB engine
– OpenRDF REST API
• Docker for containerisation
• An RDF DBaaS is…
– A GraphDB instance…
– Running within a Docker container…
– Storing its data on a private NAS (EBS) volume
6

Cloud Architecture (AWS)
7
Elasticity vs
High Availability vs
Cost Efficiency

Dealing with Failures
8
our responsibility
CSP responsibility

Evaluation
• Elastic
– Routing nodes, data nodes + NAS storage grow as
usage grows
• High availability & resilience
– Strategies for dealing with failures in data, routing,
Coordinator nodes
• Cost efficient
– Cloud native architecture -> cost savings
– Multi-tenant model -> cost savings
– Elastic: return under-utilised or unused resources
back to CSP
9

OpenRDF REST API
resource operations comments
/repositories GET Get info on DB repos
/repositories/<REPOSITORY> GET, POST, PUT, DELETE Create*, delete, query a
repository
/repositories/<REPOSITORY>/size GET Gets the number of triples
in a repository
/repositories/<REPOSITORY>/statements GET, POST, PUT, DELETE Add, read, update, delete
statements
repositories/<REPOSITORY>/rdf-graphs/<GRAPH> GET, POST, PUT, DELETE Same as above
/settings GET, PUT Configure the DBaaS*
10

Standards Compliant
• Standard SPARQL endpoint, Linked Data point
• Variety of 3rd party tools can be used to query, explore or
visualise Open (Linked) Data
11

Standards Compliant (3rd Party Tools)
12

Standards Compliant (3rd Party Tools)
13

Benefits
• Enables live data services instead of static data files
• Data publishers don’t need to worry about
infrastructure (databases, availability, cloud)
• Developers get reliable access to data services,
simple APIs, can use various 3rd party tools
14

http://dapaas.eu
@dapaasproject
dapaas-platform@googlegroups.com
Thank you!
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Welcome to UiPath Test Automation using UiPath Test Suite series part 2. In this session, we will cover API test automation along with a web automation demo. Topics covered: Test Automation introduction API Example of API automation Web automation demonstration Speaker Pathrudu Chintakayala, Associate Technical Architect @Yash and UiPath MVP Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP

UiPath Test Automation using UiPath Test Suite series, part 2

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AI for Every Business: Unlocking Your Product's Universal Potential by VP of ...

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This talk focuses on the practical aspects of integrating various telephony systems with Salesforce, drawing on examples from implementations in the Czech scene. It aims to inform attendees about the spectrum of telephony solutions available, from small to large scale, and their compatibility with Salesforce. The presentation will highlight key considerations for selecting a telephony provider that integrates smoothly with Salesforce, including important questions to support the decision-making process. It will also discuss methods for integrating existing telephony systems with Salesforce, aimed at companies contemplating or in the process of adopting this CRM platform. The discussion is designed to provide a straightforward overview of the steps and considerations involved in telephony and Salesforce integration, with an emphasis on functionality, compatibility, and the practical experiences of Czech companies.

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How to differentiate Sales Cloud and CPQ on first glance might be tricky if you do not know where to look and what to look at. You will know :-) Managing the sales process within Salesforce is a common use case that can be managed with standart Sales Cloud. If you want to do entire quoting process you will find out Salesforce CPQ solution exists. What is then the difference if both can handle selling products? You will see comparison of 10 different features, which Sales Cloud and Salesforce CPQ handle differently. Simple question you will always remember if you should consider using Salesforce CPQ will be a cherry on top.

10 Differences between Sales Cloud and CPQ, Blanka Doktorová

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Are you looking to streamline your workflows and boost your projects’ efficiency? Do you find yourself searching for ways to add flexibility and control over your FME workflows? If so, you’re in the right place. Join us for an insightful dive into the world of FME parameters, a critical element in optimizing workflow efficiency. This webinar marks the beginning of our three-part “Essentials of Automation” series. This first webinar is designed to equip you with the knowledge and skills to utilize parameters effectively: enhancing the flexibility, maintainability, and user control of your FME projects. Here’s what you’ll gain: - Essentials of FME Parameters: Understand the pivotal role of parameters, including Reader/Writer, Transformer, User, and FME Flow categories. Discover how they are the key to unlocking automation and optimization within your workflows. - Practical Applications in FME Form: Delve into key user parameter types including choice, connections, and file URLs. Allow users to control how a workflow runs, making your workflows more reusable. Learn to import values and deliver the best user experience for your workflows while enhancing accuracy. - Optimization Strategies in FME Flow: Explore the creation and strategic deployment of parameters in FME Flow, including the use of deployment and geometry parameters, to maximize workflow efficiency. - Pro Tips for Success: Gain insights on parameterizing connections and leveraging new features like Conditional Visibility for clarity and simplicity. We’ll wrap up with a glimpse into future webinars, followed by a Q&A session to address your specific questions surrounding this topic. Don’t miss this opportunity to elevate your FME expertise and drive your projects to new heights of efficiency.

Essentials of Automations: Optimizing FME Workflows with Parameters

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We're living the AI revolution and Salesforce is adapting and bring new value to their customers. Einstein products are evolving rapidly and navigating their limitations, language support, and use cases can be challenging. Let's make review of what Einstein product are available currently, what are the capabilities and what can be used for in CEE region and how Rossie.ai can help to learn Salesforce speak Czech. We will explore the Einstein roadmap and I will make a short live demo (based on your vote) of some Einstein feature.

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💥 Speed, accuracy, and scaling – discover the superpowers of GenAI in action with UiPath Document Understanding and Communications Mining™: See how to accelerate model training and optimize model performance with active learning Learn about the latest enhancements to out-of-the-box document processing – with little to no training required Get an exclusive demo of the new family of UiPath LLMs – GenAI models specialized for processing different types of documents and messages This is a hands-on session specifically designed for automation developers and AI enthusiasts seeking to enhance their knowledge in leveraging the latest intelligent document processing capabilities offered by UiPath. Speakers: 👨‍🏫 Andras Palfi, Senior Product Manager, UiPath 👩‍🏫 Lenka Dulovicova, Product Program Manager, UiPath

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UiPath Test Automation using UiPath Test Suite series, part 3

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You’ve heard good data matters in Machine Learning, but does it matter for Generative AI applications? Corporate data often differs significantly from the general Internet data used to train most foundation models. Join me for a demo on building an open source RAG (Retrieval Augmented Generation) stack using Milvus vector database for Retrieval, LangChain, Llama 3 with Ollama, Ragas RAG Eval, and optional Zilliz cloud, OpenAI.

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UiPath Test Automation using UiPath Test Suite series, part 1

UiPath Test Automation using UiPath Test Suite series, part 2

AI for Every Business: Unlocking Your Product's Universal Potential by VP of ...

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Introduction to Open Source RAG and RAG Evaluation

DataGraft Platform: RDF Database-as-a-Service

1. DataGraft Platform: RDF Database-as-a- Service Open Data Workshop @ Oslo July 2nd, 2015 http://dapaas.eu/ Marin Dimitrov, Ontotext (Bulgaria)

2. DataGraft Open Data Platform 2

3. DataGraft Open Data Platform 3

4. The Role of a RDF DBaaS 4 Grafter Grafterizer RDF DBaaSOpen Data Portal • Transform tabular data into RDF • Publish (Linked) data services, instead of static datasets • Lower-cost & easier data publishing process

5. RDF DBaaS Requirements • Elastic – dynamically adapt to growing data & query volumes • High availability & resilience – no SPFs, “graceful degradation” upon failures • Cost efficient • Host a large number of data services (databases) – But probably of low/moderate data & query volume • Security & isolation of the multi-tenant databases 5 Not easy to achieve all three!

6. Cloud Architecture (AWS) • AWS based – Network storage, compute & auto-scaling, load balancing, integration services, … • Ontotext GraphDB as the RDF DB engine – OpenRDF REST API • Docker for containerisation • An RDF DBaaS is… – A GraphDB instance… – Running within a Docker container… – Storing its data on a private NAS (EBS) volume 6

7. Cloud Architecture (AWS) 7 Elasticity vs High Availability vs Cost Efficiency

8. Dealing with Failures 8 our responsibility CSP responsibility

9. Evaluation • Elastic – Routing nodes, data nodes + NAS storage grow as usage grows • High availability & resilience – Strategies for dealing with failures in data, routing, Coordinator nodes • Cost efficient – Cloud native architecture -> cost savings – Multi-tenant model -> cost savings – Elastic: return under-utilised or unused resources back to CSP 9

10. OpenRDF REST API resource operations comments /repositories GET Get info on DB repos /repositories/<REPOSITORY> GET, POST, PUT, DELETE Create*, delete, query a repository /repositories/<REPOSITORY>/size GET Gets the number of triples in a repository /repositories/<REPOSITORY>/statements GET, POST, PUT, DELETE Add, read, update, delete statements repositories/<REPOSITORY>/rdf-graphs/<GRAPH> GET, POST, PUT, DELETE Same as above /settings GET, PUT Configure the DBaaS* 10

11. Standards Compliant • Standard SPARQL endpoint, Linked Data point • Variety of 3rd party tools can be used to query, explore or visualise Open (Linked) Data 11

12. Standards Compliant (3rd Party Tools) 12

13. Standards Compliant (3rd Party Tools) 13

14. Benefits • Enables live data services instead of static data files • Data publishers don’t need to worry about infrastructure (databases, availability, cloud) • Developers get reliable access to data services, simple APIs, can use various 3rd party tools 14

15. http://dapaas.eu @dapaasproject dapaas-platform@googlegroups.com Thank you! 15

DataGraft Platform: RDF Database-as-a-Service

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