An Algebraic Data Model for Graphs and Hypergraphs (Category Theory meetup, N...Joshua Shinavier
A presentation for the Category Theory meetup at Uber in San Francisco, November 21, 2019. A combination of previous slide shows motivating and presenting the Algebraic Property Graphs data model.
Property graph vs. RDF Triplestore comparison in 2020Ontotext
This presentation goes all the way from intro "what graph databases are" to table comparing the RDF vs. PG plus two different diagrams presenting the market circa 2020
An Algebraic Data Model for Graphs and Hypergraphs (Category Theory meetup, N...Joshua Shinavier
A presentation for the Category Theory meetup at Uber in San Francisco, November 21, 2019. A combination of previous slide shows motivating and presenting the Algebraic Property Graphs data model.
Property graph vs. RDF Triplestore comparison in 2020Ontotext
This presentation goes all the way from intro "what graph databases are" to table comparing the RDF vs. PG plus two different diagrams presenting the market circa 2020
Intro to MongoDB
Get a jumpstart on MongoDB, use cases, and next steps for building your first app with Buzz Moschetti, MongoDB Enterprise Architect.
@BuzzMoschetti
Visualize some of Austin's open source data using Elasticsearch with Kibana. ObjectRocket's Steve Croce presented this talk on 10/13/17 at the DBaaS event in Austin, TX.
Towards Digital Twin standards following an open source approachFIWARE
Digital Twins are gaining momentum when designing smart solutions in different application domains. However, there is a lack of open standards that warrant interoperability and portability of solutions, avoiding vendor lock-in.
During the presentation, we will review major developments in this area, focused on the adoption of a standard API for accessing Digital Twin Data and Smart Data Models. We will review how a Digital Twin approach enables data integration at different levels: architecting vertical smart solutions, within smart organizations and across organizations. At all levels interfacing with IoT, BigData, AI/ML, Blockchain, or Robotics technologies.
Neo4j Morpheus: Interweaving Table and Graph Data with SQL and Cypher in Apac...Databricks
Graph data and graph analytics are increasingly important in data science and engineering. Cypher is an open language used for querying and updating graph databases and analytics platforms, which is now available in the Apache Spark environment. Neo4j Morpheus leverages the open source graph language project to integrate data from Neo4j operational graph databases with Hive and JDBC SQL data sources, using new Cypher features like the Property Graph Catalog, named graphs, graph projection, parameterized graph view functions, and graph/table views. Input and output graphs can be loaded and stored as structured collections of DataFrames with strong graph schemas to ensure data consistency and graph query optimization. Property graphs can also be analyzed and transformed using graph algorithms such as those in the GraphFrames project. Besides describing and demonstrating these capabilities, this talk also discusses the Spark Project Improvement Proposal to bring Cypher into Spark 3.0, and outlines current work to unify Cypher with other graph query languages to form a new ISO standard Graph Query Language.
Speakers: Alastair Green, Martin Junghanns
Intro to MongoDB
Get a jumpstart on MongoDB, use cases, and next steps for building your first app with Buzz Moschetti, MongoDB Enterprise Architect.
@BuzzMoschetti
Visualize some of Austin's open source data using Elasticsearch with Kibana. ObjectRocket's Steve Croce presented this talk on 10/13/17 at the DBaaS event in Austin, TX.
Towards Digital Twin standards following an open source approachFIWARE
Digital Twins are gaining momentum when designing smart solutions in different application domains. However, there is a lack of open standards that warrant interoperability and portability of solutions, avoiding vendor lock-in.
During the presentation, we will review major developments in this area, focused on the adoption of a standard API for accessing Digital Twin Data and Smart Data Models. We will review how a Digital Twin approach enables data integration at different levels: architecting vertical smart solutions, within smart organizations and across organizations. At all levels interfacing with IoT, BigData, AI/ML, Blockchain, or Robotics technologies.
Neo4j Morpheus: Interweaving Table and Graph Data with SQL and Cypher in Apac...Databricks
Graph data and graph analytics are increasingly important in data science and engineering. Cypher is an open language used for querying and updating graph databases and analytics platforms, which is now available in the Apache Spark environment. Neo4j Morpheus leverages the open source graph language project to integrate data from Neo4j operational graph databases with Hive and JDBC SQL data sources, using new Cypher features like the Property Graph Catalog, named graphs, graph projection, parameterized graph view functions, and graph/table views. Input and output graphs can be loaded and stored as structured collections of DataFrames with strong graph schemas to ensure data consistency and graph query optimization. Property graphs can also be analyzed and transformed using graph algorithms such as those in the GraphFrames project. Besides describing and demonstrating these capabilities, this talk also discusses the Spark Project Improvement Proposal to bring Cypher into Spark 3.0, and outlines current work to unify Cypher with other graph query languages to form a new ISO standard Graph Query Language.
Speakers: Alastair Green, Martin Junghanns
Composable Parallel Processing in Apache Spark and WeldDatabricks
The main reason people are productive writing software is composability -- engineers can take libraries and functions written by other developers and easily combine them into a program. However, composability has taken a back seat in early parallel processing APIs. For example, composing MapReduce jobs required writing the output of every job to a file, which is both slow and error-prone. Apache Spark helped simplify cluster programming largely because it enabled efficient composition of parallel functions, leading to a large standard library and high-level APIs in various languages. In this talk, I'll explain how composability has evolved in Spark's newer APIs, and also present a new research project I'm leading at Stanford called Weld to enable much more efficient composition of software on emerging parallel hardware (multicores, GPUs, etc).
Speaker: Matei Zaharia
This course is a quick overview of the fundamentals of graph databases and graph queries, with a focus on RDF and SPARQL. It includes both simple and challenging hands-on exercises to practice and test your understanding.
The material for this course can be downloaded form the following link: https://github.com/paolo7/Introduction-to-Graph-Databases
Neo4j Morpheus: Interweaving Documents, Tables and and Graph Data in Spark wi...Databricks
Fuse graph, document and relational data from transactional and analytic data sources, into a property graph “bird’s eye view”. The property graph data model is Chen’s “entity relationship” model, without clutter. Use “ASCII Art” visual property graph schemas to define “graph data lifts”, mapping from data lake, RDBMS, RDF or graph data cloud services into Spark. Graphs in Spark draw on multiple data sources. Leverage the Cypher query language to combine, split, and project graphs in Spark memory. Graph data is “woven” in Spark without altering or copying the original source. The results of graph workloads can be written back into HDFS or other file systems. Graphs can be read from, stored and merged into a Neo4j transactional database. And tabular datasets can be extracted from graphs. Data scientists and engineers load, wrangle and analyze mixed model data through Morpheus transformations. Enterprises use graphs to catalogue their disparate data assets and processes. They store graph datasets in the data lake. In a world of concern about data protection, see how graph data lifts allow tailored, canonical data views to be realized, in Spark, without remodeling and moving data. Morpheus combines SparkSQL and Cypher queries, and table/graph functions.Choose the right language for the job: eliminate cumbersome multi-joins for connected-data traversals by using super-concise Cypher patterns for sub-graph detection and graph projection; use the power of table projection, grouping, aggregation in SparkSQL, all in one application. Feel free to “dismantle your graph”: expose your graph nodes or relationships as dataframes, or as Hive tables. Key Takeaways Graph technology meets Big Data and Spark Analytics Property graphs: the superset data model Graph, relational and document data, interwoven Lift, split, combine, and create new graphs, from any data source Get your data fit to exploit graph compute, without losing any of your existing tools undefined undefined undefined undefined undefined
Agenda:
MongoDB Overview/History
Workshop
1. How to perform operations to MongoDB – Workshop
2. Using MongoDB in your Java application
Advance usage of MongoDB
1. Performance measurement comparison – real life use cases
3. Doing Cluster setup
4. Cons of MongoDB with other document oriented DB
5. Map-reduce/ Aggregation overview
Workshop prerequisite
1. All participants must bring their laptops.
2. https://github.com/geek007/mongdb-examples
3. Software prerequisite
a. Java version 1.6+
b. Your favorite IDE, Preferred http://www.jetbrains.com/idea/download/
c. MongoDB server version – 2.6.3 (http://www.mongodb.org/downloads - 64 bit version)
d. Participants can install MongoDB client – http://robomongo.org/
About Speaker:
Akbar Gadhiya is working with Ishi Systems as Programmer Analyst. Previously he worked with PMC, Baroda and HCL Technologies.
Presented on 10/11/12 at the Boston Elasticsearch meetup held at the Microsoft New England Research & Development Center. This talk gave a very high-level overview of Elasticsearch to newcomers and explained why ES is a good fit for Traackr's use case.
This slides I've used on talk about Semantic Web use-case. Not all know what exactly Semantic Web is about. So I've created set of slides showing this in a simple and correct way. Use-case slides are removed on this public available slides. Animated version here goo.gl/qKoF6k . Contact me for sources!
Applying large scale text analytics with graph databasesData Ninja API
Data Ninja Services collaborated with Oracle to reach a major milestone in the integration of text analytics with Oracle Spatial and Graph. The Data Ninja Services client in Java can be used to analyze free texts, extract entities, generate RDF semantic graphs, and choose from a number of graph analytics to infer entity relationships. We demonstrated two case studies involving mining health news and detecting anomalies in product reviews.
Formal Verification of Data Provenance RecordsSzymon Klarman
Szymon Klarman, Stefan Schlobach and Luciano Serafini. Formal Verification of Data Provenance Records. In Proceedings of the 11th International Semantic Web Conference (ISWC-12), 2012
Presentation for paper:
Szymon Klarman, Ulle Endriss and Stefan Schlobach. ABox Abduction in the Description Logic ALC. In Journal of Automated Reasoning, 46(1), pp. 43-80, 2011.
Judgment Aggregation as Maximization of Epistemic and Social UtilitySzymon Klarman
Presentation for paper:
Szymon Klarman. Judgment Aggregation as Maximization of Epistemic and Social Utility. In Proceedings of the 2nd International Workshop on Computational Social Choice (COMSOC-08), 2008.
Prediction and Explanation over DL-Lite Data StreamsSzymon Klarman
Presentation for the paper:
Szymon Klarman and Thomas Meyer. Prediction and Explanation over DL-Lite Data Streams. In Proceedings of the 19th International Conference on Logic for Programming, Artificial Intelligence and Reasoning (LPAR-19), 2013.
Presentation of the paper:
Szymon Klarman and Thomas Meyer. Querying Temporal Databases via OWL 2 QL (with appendix). In Proceedings of the 8th International Conference on Web Reasoning and Rule Systems (RR-14), 2014.
Ontology learning from interpretations in lightweight description logicsSzymon Klarman
Presentation of the paper:
Szymon Klarman and Katarina Britz. Ontology Learning from Interpretations in Lightweight Description Logics. In Proceedings of the 25th International Conference on Inductive Logic Programming (ILP-15), 2015
What makes a linked data pattern interesting?Szymon Klarman
A short talk on the problem of mining linked data (RDF) patterns, introducing a few preliminary notions towards the definition of generic linked data mining algorithms.
SKOS: Building taxonomies with minimum ontological commitmentSzymon Klarman
A short introduction to Simple Knowledge Organisation System (SKOS) - a W3C standard for representing taxonomies, thesuari, and other classification systems. Presented at the Semantic Web London meetup (April, 2017)
Modern design is crucial in today's digital environment, and this is especially true for SharePoint intranets. The design of these digital hubs is critical to user engagement and productivity enhancement. They are the cornerstone of internal collaboration and interaction within enterprises.
Quarkus Hidden and Forbidden ExtensionsMax Andersen
Quarkus has a vast extension ecosystem and is known for its subsonic and subatomic feature set. Some of these features are not as well known, and some extensions are less talked about, but that does not make them less interesting - quite the opposite.
Come join this talk to see some tips and tricks for using Quarkus and some of the lesser known features, extensions and development techniques.
Enhancing Research Orchestration Capabilities at ORNL.pdfGlobus
Cross-facility research orchestration comes with ever-changing constraints regarding the availability and suitability of various compute and data resources. In short, a flexible data and processing fabric is needed to enable the dynamic redirection of data and compute tasks throughout the lifecycle of an experiment. In this talk, we illustrate how we easily leveraged Globus services to instrument the ACE research testbed at the Oak Ridge Leadership Computing Facility with flexible data and task orchestration capabilities.
OpenFOAM solver for Helmholtz equation, helmholtzFoam / helmholtzBubbleFoamtakuyayamamoto1800
In this slide, we show the simulation example and the way to compile this solver.
In this solver, the Helmholtz equation can be solved by helmholtzFoam. Also, the Helmholtz equation with uniformly dispersed bubbles can be simulated by helmholtzBubbleFoam.
Code reviews are vital for ensuring good code quality. They serve as one of our last lines of defense against bugs and subpar code reaching production.
Yet, they often turn into annoying tasks riddled with frustration, hostility, unclear feedback and lack of standards. How can we improve this crucial process?
In this session we will cover:
- The Art of Effective Code Reviews
- Streamlining the Review Process
- Elevating Reviews with Automated Tools
By the end of this presentation, you'll have the knowledge on how to organize and improve your code review proces
TROUBLESHOOTING 9 TYPES OF OUTOFMEMORYERRORTier1 app
Even though at surface level ‘java.lang.OutOfMemoryError’ appears as one single error; underlyingly there are 9 types of OutOfMemoryError. Each type of OutOfMemoryError has different causes, diagnosis approaches and solutions. This session equips you with the knowledge, tools, and techniques needed to troubleshoot and conquer OutOfMemoryError in all its forms, ensuring smoother, more efficient Java applications.
How Does XfilesPro Ensure Security While Sharing Documents in Salesforce?XfilesPro
Worried about document security while sharing them in Salesforce? Fret no more! Here are the top-notch security standards XfilesPro upholds to ensure strong security for your Salesforce documents while sharing with internal or external people.
To learn more, read the blog: https://www.xfilespro.com/how-does-xfilespro-make-document-sharing-secure-and-seamless-in-salesforce/
Field Employee Tracking System| MiTrack App| Best Employee Tracking Solution|...informapgpstrackings
Keep tabs on your field staff effortlessly with Informap Technology Centre LLC. Real-time tracking, task assignment, and smart features for efficient management. Request a live demo today!
For more details, visit us : https://informapuae.com/field-staff-tracking/
In 2015, I used to write extensions for Joomla, WordPress, phpBB3, etc and I ...Juraj Vysvader
In 2015, I used to write extensions for Joomla, WordPress, phpBB3, etc and I didn't get rich from it but it did have 63K downloads (powered possible tens of thousands of websites).
Accelerate Enterprise Software Engineering with PlatformlessWSO2
Key takeaways:
Challenges of building platforms and the benefits of platformless.
Key principles of platformless, including API-first, cloud-native middleware, platform engineering, and developer experience.
How Choreo enables the platformless experience.
How key concepts like application architecture, domain-driven design, zero trust, and cell-based architecture are inherently a part of Choreo.
Demo of an end-to-end app built and deployed on Choreo.
Developing Distributed High-performance Computing Capabilities of an Open Sci...Globus
COVID-19 had an unprecedented impact on scientific collaboration. The pandemic and its broad response from the scientific community has forged new relationships among public health practitioners, mathematical modelers, and scientific computing specialists, while revealing critical gaps in exploiting advanced computing systems to support urgent decision making. Informed by our team’s work in applying high-performance computing in support of public health decision makers during the COVID-19 pandemic, we present how Globus technologies are enabling the development of an open science platform for robust epidemic analysis, with the goal of collaborative, secure, distributed, on-demand, and fast time-to-solution analyses to support public health.
Providing Globus Services to Users of JASMIN for Environmental Data AnalysisGlobus
JASMIN is the UK’s high-performance data analysis platform for environmental science, operated by STFC on behalf of the UK Natural Environment Research Council (NERC). In addition to its role in hosting the CEDA Archive (NERC’s long-term repository for climate, atmospheric science & Earth observation data in the UK), JASMIN provides a collaborative platform to a community of around 2,000 scientists in the UK and beyond, providing nearly 400 environmental science projects with working space, compute resources and tools to facilitate their work. High-performance data transfer into and out of JASMIN has always been a key feature, with many scientists bringing model outputs from supercomputers elsewhere in the UK, to analyse against observational or other model data in the CEDA Archive. A growing number of JASMIN users are now realising the benefits of using the Globus service to provide reliable and efficient data movement and other tasks in this and other contexts. Further use cases involve long-distance (intercontinental) transfers to and from JASMIN, and collecting results from a mobile atmospheric radar system, pushing data to JASMIN via a lightweight Globus deployment. We provide details of how Globus fits into our current infrastructure, our experience of the recent migration to GCSv5.4, and of our interest in developing use of the wider ecosystem of Globus services for the benefit of our user community.
Innovating Inference - Remote Triggering of Large Language Models on HPC Clus...Globus
Large Language Models (LLMs) are currently the center of attention in the tech world, particularly for their potential to advance research. In this presentation, we'll explore a straightforward and effective method for quickly initiating inference runs on supercomputers using the vLLM tool with Globus Compute, specifically on the Polaris system at ALCF. We'll begin by briefly discussing the popularity and applications of LLMs in various fields. Following this, we will introduce the vLLM tool, and explain how it integrates with Globus Compute to efficiently manage LLM operations on Polaris. Attendees will learn the practical aspects of setting up and remotely triggering LLMs from local machines, focusing on ease of use and efficiency. This talk is ideal for researchers and practitioners looking to leverage the power of LLMs in their work, offering a clear guide to harnessing supercomputing resources for quick and effective LLM inference.
Strategies for Successful Data Migration Tools.pptxvarshanayak241
Data migration is a complex but essential task for organizations aiming to modernize their IT infrastructure and leverage new technologies. By understanding common challenges and implementing these strategies, businesses can achieve a successful migration with minimal disruption. Data Migration Tool like Ask On Data play a pivotal role in this journey, offering features that streamline the process, ensure data integrity, and maintain security. With the right approach and tools, organizations can turn the challenge of data migration into an opportunity for growth and innovation.
Why React Native as a Strategic Advantage for Startup Innovation.pdfayushiqss
Do you know that React Native is being increasingly adopted by startups as well as big companies in the mobile app development industry? Big names like Facebook, Instagram, and Pinterest have already integrated this robust open-source framework.
In fact, according to a report by Statista, the number of React Native developers has been steadily increasing over the years, reaching an estimated 1.9 million by the end of 2024. This means that the demand for this framework in the job market has been growing making it a valuable skill.
But what makes React Native so popular for mobile application development? It offers excellent cross-platform capabilities among other benefits. This way, with React Native, developers can write code once and run it on both iOS and Android devices thus saving time and resources leading to shorter development cycles hence faster time-to-market for your app.
Let’s take the example of a startup, which wanted to release their app on both iOS and Android at once. Through the use of React Native they managed to create an app and bring it into the market within a very short period. This helped them gain an advantage over their competitors because they had access to a large user base who were able to generate revenue quickly for them.
We describe the deployment and use of Globus Compute for remote computation. This content is aimed at researchers who wish to compute on remote resources using a unified programming interface, as well as system administrators who will deploy and operate Globus Compute services on their research computing infrastructure.
Exploring Innovations in Data Repository Solutions - Insights from the U.S. G...Globus
The U.S. Geological Survey (USGS) has made substantial investments in meeting evolving scientific, technical, and policy driven demands on storing, managing, and delivering data. As these demands continue to grow in complexity and scale, the USGS must continue to explore innovative solutions to improve its management, curation, sharing, delivering, and preservation approaches for large-scale research data. Supporting these needs, the USGS has partnered with the University of Chicago-Globus to research and develop advanced repository components and workflows leveraging its current investment in Globus. The primary outcome of this partnership includes the development of a prototype enterprise repository, driven by USGS Data Release requirements, through exploration and implementation of the entire suite of the Globus platform offerings, including Globus Flow, Globus Auth, Globus Transfer, and Globus Search. This presentation will provide insights into this research partnership, introduce the unique requirements and challenges being addressed and provide relevant project progress.
Advanced Flow Concepts Every Developer Should KnowPeter Caitens
Tim Combridge from Sensible Giraffe and Salesforce Ben presents some important tips that all developers should know when dealing with Flows in Salesforce.
2. HyperGraphQL = linked data + GraphQL
Linked Data:
- A set of specifications and good practices
developed and recommended by W3C for
publishing (connected) data on the Web.
- In a narrow sense, a graph data model (RDF)
based on the use of URIs for identifying
resources and describing them with
subject-predicate-object triples.
GraphQL:
- A query language for APIs and a runtime
environment for fulfilling data requests.
- Originally developed by Facebook and
released in 2015.
- Predicted one of the most promising web
development technologies for 2018.
3. Linked data
Pros:
- Very flexible and expressive open-world,
schema-on-read, graph data model.
- Accompanied by highly expressive query
language SPARQL, along with a range of
other dedicated tools and standards (OWL,
SHACL, JSON-LD, RDFa).
Cons:
- The flexibility and the expressiveness of the
stack makes it sometimes demanding to
work with for developers (esp. front-end).
- Querying data from multiple sources
(federated querying) might easily get
complex and unreliable.
5. Objectives
- hiding the complexities of the Semantic Web
stack behind GraphQL interface
- enforcing a uniform, strict view over
heterogeneous linked data sources residing
in disconnected services
- restricting access to RDF stores down to
simple yet expressive (tree-shaped) GraphQL
queries
- facilitating construction of
microservice-based linked data
architectures in a “plug-and-play” fashion
11. Querying SPARQL endpoint
Live demo (http://bit.ly/2Dd8rVa)
- Queries are rewritten to SPARQL and
delegated to the remote endpoint, from where
the relevant portion of data is fetched.
- Configuration:
{
"id": "dbpedia-sparql",
"type": "SPARQLEndpointService",
"url": "http://dbpedia.org/sparql/",
"graph": "http://dbpedia.org",
"user": "",
"password": ""
}
12. Exposing data from local file
Live demo (http://bit.ly/2DdeKIq)
- Queries are rewritten to SPARQL and
executed at the local in-memory triple store
where the RDF data from the file resides.
- Configuration:
{
"id": "agrovoc-local",
"type": "LocalModelSPARQLService",
"filepath": "agrovoc.ttl",
"filetype": "TTL"
}
13. Federated querying
Live demo (http://bit.ly/2mx04si)
- Query is partitioned into largest possible
subqueries that can be handled via single
request by each individual service within the
federation.
- Whenever possible such subqueries are
executed concurrently.
14. Summary & outlook
- HyperGraphQL is a lightweight, extensible
GraphQL query interface for linked data
services.
- Currently, it supports access to and
federation of SPARQL endpoints, local RDF
data, other HyperGraphQL endpoints.
- Setting up an instance requires providing a
simple configuration and a schema.
- Schema must be defined manually, but could
be automated under certain data modelling
assumptions.
- It supports a number of response formats,
including JSON-LD, RDF/XML, TURTLE,
N-TRIPLE.
Docs / demo / tutorial: http://hypergraphql.org
Twitter: @HyperGraphQL