Timea Turdean's presentation from Connected Data London. Timea, who is a Technical Consultant at the Semantic Web Company presented their success stories using Connected Data.
Powerful Information Discovery with Big Knowledge Graphs –The Offshore Leaks ...Connected Data World
Borislav Popov's slides from his lightning talk at Connected Data London. Borislav - a Director of Business Development at Ontotext presented Ontotext's approach to tackling the Panama Papers leak. Using a technology that is a mix between semantic web and graph databases.
How to Reveal Hidden Relationships in Data and Risk AnalyticsOntotext
Imagine risk analysis manager or compliance officer who can discover easily relationships like this: Big Bucks Café out of Seattle controls My Local Café in NYC through an offshore company. Such discovery can be a game changer if My Local Café pretends to be an independent small enterprise, while recently Big Bucks experiences financial difficulties.
Knowledge graphs - it’s what all businesses now are on the lookout for. But what exactly is a knowledge graph and, more importantly, how do you get one? Do you get it as an out-of-the-box solution or do you have to build it (or have someone else build it for you)? With the help of our knowledge graph technology experts, we have created a step-by-step list of how to build a knowledge graph. It will properly expose and enforce the semantics of the semantic data model via inference, consistency checking and validation and thus offer organizations many more opportunities to transform and interlink data into coherent knowledge.
Boost your data analytics with open data and public news contentOntotext
Get guidance through the gigantic sea of freely available Open Data and learn how it can empower you analysis of any kind of sources.
This webinar is a live demo of news and data analytics, based on rich links within big knowledge graphs. It will show you how to:
Build ranking reports (e.g for people and organisations)
View topics linked implicitly (e.g. daughter companies, key personnel, products …)
Draw trend lines
Extend your analytics with additional data sources
II-SDV 2017: Approaches of Web Information Analysis in a Day to Day Work Envi...Dr. Haxel Consult
Web scraping, content filtering, tagging and feeding web data into the day to day work environment takes many different shapes and requires an additional software stack that is blending well with existing big data analysis, text analysis and search technology.
This document discusses using open data and news analytics. It demonstrates how a semantic publishing platform can link text to concepts in knowledge graphs to enable navigation from text to entities and related news. It provides examples of queries over linked data from DBpedia, Geonames, and news metadata to retrieve information about cities, people related to Google, airports near London, and news mentioning companies. Graphs and rankings show the popularity and relationships of entities in the news by industry such as automotive, finance, and banking.
It Don’t Mean a Thing If It Ain’t Got SemanticsOntotext
With the tons of bits of data around enterprises and the challenge to turn these data into knowledge, meaning is arguably in the systems of the best database holder.
Turning data pieces into actionable knowledge and data-driven decisions takes a good and reliable database. The RDF database is one such solution.
It captures and analyzes large volumes of diverse data while at the same time is able to manage and retrieve each and every connection these data ever get to enter in.
In our latest slides, you will find out why we believe RDF graph databases work wonders with serving information needs and handling the growing amounts of diverse data every organization faces today.
Powerful Information Discovery with Big Knowledge Graphs –The Offshore Leaks ...Connected Data World
Borislav Popov's slides from his lightning talk at Connected Data London. Borislav - a Director of Business Development at Ontotext presented Ontotext's approach to tackling the Panama Papers leak. Using a technology that is a mix between semantic web and graph databases.
How to Reveal Hidden Relationships in Data and Risk AnalyticsOntotext
Imagine risk analysis manager or compliance officer who can discover easily relationships like this: Big Bucks Café out of Seattle controls My Local Café in NYC through an offshore company. Such discovery can be a game changer if My Local Café pretends to be an independent small enterprise, while recently Big Bucks experiences financial difficulties.
Knowledge graphs - it’s what all businesses now are on the lookout for. But what exactly is a knowledge graph and, more importantly, how do you get one? Do you get it as an out-of-the-box solution or do you have to build it (or have someone else build it for you)? With the help of our knowledge graph technology experts, we have created a step-by-step list of how to build a knowledge graph. It will properly expose and enforce the semantics of the semantic data model via inference, consistency checking and validation and thus offer organizations many more opportunities to transform and interlink data into coherent knowledge.
Boost your data analytics with open data and public news contentOntotext
Get guidance through the gigantic sea of freely available Open Data and learn how it can empower you analysis of any kind of sources.
This webinar is a live demo of news and data analytics, based on rich links within big knowledge graphs. It will show you how to:
Build ranking reports (e.g for people and organisations)
View topics linked implicitly (e.g. daughter companies, key personnel, products …)
Draw trend lines
Extend your analytics with additional data sources
II-SDV 2017: Approaches of Web Information Analysis in a Day to Day Work Envi...Dr. Haxel Consult
Web scraping, content filtering, tagging and feeding web data into the day to day work environment takes many different shapes and requires an additional software stack that is blending well with existing big data analysis, text analysis and search technology.
This document discusses using open data and news analytics. It demonstrates how a semantic publishing platform can link text to concepts in knowledge graphs to enable navigation from text to entities and related news. It provides examples of queries over linked data from DBpedia, Geonames, and news metadata to retrieve information about cities, people related to Google, airports near London, and news mentioning companies. Graphs and rankings show the popularity and relationships of entities in the news by industry such as automotive, finance, and banking.
It Don’t Mean a Thing If It Ain’t Got SemanticsOntotext
With the tons of bits of data around enterprises and the challenge to turn these data into knowledge, meaning is arguably in the systems of the best database holder.
Turning data pieces into actionable knowledge and data-driven decisions takes a good and reliable database. The RDF database is one such solution.
It captures and analyzes large volumes of diverse data while at the same time is able to manage and retrieve each and every connection these data ever get to enter in.
In our latest slides, you will find out why we believe RDF graph databases work wonders with serving information needs and handling the growing amounts of diverse data every organization faces today.
Webinar: Tagging with Rich Knowledge Graphs
Presenter: Borislav Popov, Director Business Development, UK
Semantic tagging is the driving force behind text analytics used by news and media organizations increasingly often. The service can help publishers target content with pinpoint accuracy.
The webinar revolves around Ontotext's semantic publishing stack and lessons learned from production deployments of GraphDB, Concept Extraction Service and the Dynamic Semantic Publishing Platform, but it does not require prior knowledge of the Ontotext product set. As a result, we hope to give you a wider understanding of the interplay between text analytics and linked data, the importance of machine learning and continuous adaptation based on user feedback.
Besides some of the reasons and benefits for using semantic tagging, its application both through an UI and as SaaS is also discussed. Presented are the data sets compiled in order to support the text analytics and what are the machine learning driven training processes in order to resolve their inherent ambiguity. Other points of discussion include methodology for building new tagging pipelines and how to address different domains, languages and types of content.
To find out more, visit http://ontotext.com/
Diving in Panama Papers and Open Data to Discover Emerging NewsOntotext
Get guidance through the gigantic sea of freely released data from Panama Papers as well as Linked Open Data could. You will learn how it can empower you understanding of today’s news or any other information source.
This paper explores the Consumer Data Management, Consumer Data Management CDM area as the process and framework for collecting, managing, and analyzing consumer data from various sources in order to form a unified view of each client. Customer data management is the way companies keep track of their customer information and ensure proper and relevant data is obtained. Vrinda Bhateja "Consumer Data Management" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-4 | Issue-4 , June 2020, URL: https://www.ijtsrd.com/papers/ijtsrd31555.pdf Paper Url :https://www.ijtsrd.com/management/operations-management/31555/consumer-data-management/vrinda-bhateja
TFF2016, Rudi Studer, Smarte Dienstleistungen mit semantischen TechnologienTourismFastForward
This document discusses using semantic technologies to enable smart services in tourism. It describes two use cases: 1) building agile systems through fast integration of heterogeneous data and programmable interfaces using semantic technologies, and 2) collaborative development of business processes through semantic modeling, analysis, and execution of processes. The document outlines challenges with current approaches and how semantic technologies can help address these challenges through linked data, linked services, and semantic descriptions of processes and APIs.
Technical Deep Dive: Learn more about the most complete Semantic Middleware on the market. See how to integrate semantic services into your Enterprise Information Systems.
Linked data presentation for who umc 21 jan 2015Kerstin Forsberg
This document discusses the semantic web and linked data. It provides an overview of Web 1.0, Web 2.0, and Web 3.0 (semantic web) and how the semantic web uses RDF triples to represent data as a web of linked data. It also discusses how AstraZeneca is engaging with the semantic web through projects involving drug discovery and clinical research standards.
The Bounties of Semantic Data Integration for the Enterprise Ontotext
Semantic data integration allows enterprises to connect heterogeneous data sources through a common language. This creates a unified 360-degree view of enterprise data and facilitates knowledge management and use. Semantic integration aims to enrich existing data with external knowledge and provide a single access point for enterprise assets. It addresses challenges of accessing and storing data from various internal resources by building a well-structured integrated whole to enhance business processes.
Using the Semantic Web Stack to Make Big Data SmarterMatheus Mota
The document discusses using semantic web technologies to make big data smarter. It provides an overview of key concepts in semantic web, including linked data and ontologies. It describes how semantic web can add structure and meaning to unstructured data through modeling data as graphs and defining relationships and properties. The goal is to publish and query interconnected data at scale to enable new types of queries and inferences over big data.
This document discusses new ways of handling old data and unlocking value from unstructured content through cognitive systems. It provides predictions for big data and analytics spending and adoption through 2020. Key points include:
- 90% of digital information is unstructured content stored in separate repositories that don't communicate.
- By 2020, 50% of business analytics software will incorporate prescriptive analytics using cognitive computing.
- Organizations that can analyze all relevant data and provide actionable insights will gain $430 billion in productivity over less analytical peers.
- Cognitive software can support better decision-making by applying broader evidence without bias to situations.
- The cognitive software market is expected to grow rapidly over the next five
Smarter content with a Dynamic Semantic Publishing PlatformOntotext
Personalized content recommendation systems enable users to overcome the information overload associated with rapidly changing deep and wide content streams such as news. This webinar discusses Ontotext’s latest improvements to its Dynamic Semantic Publishing (DSP) platform NOW (News on the Web). The Platform includes social data mining, web usage mining, behavioral and contextual semantic fingerprinting, content typing and rich relationship search.
Linguamatics provides natural language processing (NLP) tools for text mining large amounts of biomedical text. Their software can extract facts and synthesize knowledge to help users find information. Linguamatics works with many pharmaceutical, government, and healthcare organizations. Their tools include terminology databases, rules for matching expressions, and visualization of query results.
This document discusses challenges and opportunities around discovering and using open government data. It notes that simply publishing data as linked data is not enough, and that metadata standards and presentation methods are needed to aid discovery and use. It highlights work done by Tetherless World Constellation to apply metadata standards to describe government datasets and create an aggregated catalog of over 1 million datasets. The use of schema.org and other semantic markup is discussed to enable search engines to more easily parse and index government data catalogs. Federation of catalogs using APIs and standards like DCAT and CKAN is also covered. The document emphasizes that exposing metadata is key to getting government data discovered.
II-SDV 2017: What is Innovation and how can we measure it?Dr. Haxel Consult
Innovation means many different things to many people. Ask five people and you will likely get ten answers. But all agree that it is a key driver behind the success of organizations, the growth of economies and provides major contributions in addressing global problems. This presentation will examine various analytical methods and possible metrics for measuring innovation and determining relative performance of organizations. The challenges involved in assessing innovation and how these can be addressed will be explored. The pros and cons associated with the metrics identified will also be discussed with a view to identifying a practical method for assessing innovation.
Open Research Gateway for the ELIXIR-GR Infrastructure (Part 1)OpenAIRE
The Research Data Alliance (RDA) is an international organization focused on data sharing across disciplines. It has over 8,600 members from 137 countries working to reduce barriers to data sharing through developing infrastructure and community activities. RDA has numerous active interest groups and working groups focused on issues like specific scientific domains, data reference and sharing, community needs, data stewardship, and basic infrastructure. One recent focus is guidelines for data sharing during the COVID-19 pandemic.
Linked Data efforts for data standards in biopharma and healthcareKerstin Forsberg
1) The document discusses efforts to represent biomedical data standards like CDISC, HL7 FHIR, MeSH, ICD-11, and others in semantic web formats like RDF and OWL to make them machine-processable.
2) It describes projects that have converted various standards to RDF through the work of groups like CDISC2RDF and PhUSE, and efforts to engage traditional standards bodies.
3) However, it notes that pushing standards organizations to adopt semantic web approaches requires ongoing knowledge sharing and community building, and that spreadsheets still see significant use.
Digital Science Presentation at ORCID Outreach Meeting (Ashlea Higgs)ORCID, Inc
This document summarizes several tools and platforms that integrate with ORCID profiles to help researchers manage their work and collaborations. It describes how Altmetric, Figshare, Overleaf, ReadCube, Symplectic Elements, and UberResearch integrate with ORCID to allow researchers to link publications and other research outputs to their ORCID profile, track metrics and attention for their work, and facilitate collaboration and information sharing between tools and platforms.
Linking Open, Big Data Using Semantic Web Technologies - An IntroductionRonald Ashri
The Physics Department of the University of Cagliari and the Linkalab Group invited me to talk about the Semantic Web and Linked Data - this is simply an introduction to the technologies involved.
Stephen Buxton | Data Integration - a Multi-Model Approach - Documents and Tr...semanticsconference
This document discusses when to use documents versus triples in a database. It describes the pros and cons of relational databases, document databases, graph databases, and triple stores. It advocates using a hybrid approach that combines documents and triples for the benefits of both. Documents are well-suited for storing heterogeneous data while triples enable modeling relationships and inferring new information. The combination provides a unified platform for querying rich data through semantics.
Understanding voice of the member via text miningChi-Yi Kuan
The 14th Text Analytics Summit - June 15, 2015 in New York
Today, Businesses around the world are increasingly collecting tremendous amount of unstructured data in the form of text – from multiple channels such as product reviews, market research, customer care conversations, and social media. In this talk, we will share how LinkedIn has built a text-mining platform to derive insights and create value for our members from the massive amount of data we have within our ecosystem. We will cover the following topics in our talk:
1) Topic modeling
2) Text categorization using NLP features
3) Topic-based sentiment analysis and attribution
The talk will be appropriate for business leaders, researchers and practitioners.
"Big data" is a broad term that encompasses a wide range of data and contents. Big data offers new approaches to analysis and decision making. At first glance big data and IP may seem to be opposites, but have more in common than one may think. This talk will focus on how big data will impact, and be impacted, by IP. One of the biggest promises in big data is the possibility to re-use data produced via different sources, create new services or predict the future, via the analysis of correlations. In this context, how can companies protect information assets and analytical skills? What are the new skills required to search and analyze in real time a big amount of datasets ? Big data will change not only patents information, but will also generate new types of patents.
See how the Simple Knowledge Organisation System (SKOS) can help to improve information management in various industries. The application scenarios are manifold, learn from real-world use cases.
Learn more about Semantic Web Company and the product. Find typical usage scenarios: Semantic search, concept tagging, topic pages, matchmaking, etc.
Success stories from various industry like pharma, health care, government, or retailing are presented.
Webinar: Tagging with Rich Knowledge Graphs
Presenter: Borislav Popov, Director Business Development, UK
Semantic tagging is the driving force behind text analytics used by news and media organizations increasingly often. The service can help publishers target content with pinpoint accuracy.
The webinar revolves around Ontotext's semantic publishing stack and lessons learned from production deployments of GraphDB, Concept Extraction Service and the Dynamic Semantic Publishing Platform, but it does not require prior knowledge of the Ontotext product set. As a result, we hope to give you a wider understanding of the interplay between text analytics and linked data, the importance of machine learning and continuous adaptation based on user feedback.
Besides some of the reasons and benefits for using semantic tagging, its application both through an UI and as SaaS is also discussed. Presented are the data sets compiled in order to support the text analytics and what are the machine learning driven training processes in order to resolve their inherent ambiguity. Other points of discussion include methodology for building new tagging pipelines and how to address different domains, languages and types of content.
To find out more, visit http://ontotext.com/
Diving in Panama Papers and Open Data to Discover Emerging NewsOntotext
Get guidance through the gigantic sea of freely released data from Panama Papers as well as Linked Open Data could. You will learn how it can empower you understanding of today’s news or any other information source.
This paper explores the Consumer Data Management, Consumer Data Management CDM area as the process and framework for collecting, managing, and analyzing consumer data from various sources in order to form a unified view of each client. Customer data management is the way companies keep track of their customer information and ensure proper and relevant data is obtained. Vrinda Bhateja "Consumer Data Management" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-4 | Issue-4 , June 2020, URL: https://www.ijtsrd.com/papers/ijtsrd31555.pdf Paper Url :https://www.ijtsrd.com/management/operations-management/31555/consumer-data-management/vrinda-bhateja
TFF2016, Rudi Studer, Smarte Dienstleistungen mit semantischen TechnologienTourismFastForward
This document discusses using semantic technologies to enable smart services in tourism. It describes two use cases: 1) building agile systems through fast integration of heterogeneous data and programmable interfaces using semantic technologies, and 2) collaborative development of business processes through semantic modeling, analysis, and execution of processes. The document outlines challenges with current approaches and how semantic technologies can help address these challenges through linked data, linked services, and semantic descriptions of processes and APIs.
Technical Deep Dive: Learn more about the most complete Semantic Middleware on the market. See how to integrate semantic services into your Enterprise Information Systems.
Linked data presentation for who umc 21 jan 2015Kerstin Forsberg
This document discusses the semantic web and linked data. It provides an overview of Web 1.0, Web 2.0, and Web 3.0 (semantic web) and how the semantic web uses RDF triples to represent data as a web of linked data. It also discusses how AstraZeneca is engaging with the semantic web through projects involving drug discovery and clinical research standards.
The Bounties of Semantic Data Integration for the Enterprise Ontotext
Semantic data integration allows enterprises to connect heterogeneous data sources through a common language. This creates a unified 360-degree view of enterprise data and facilitates knowledge management and use. Semantic integration aims to enrich existing data with external knowledge and provide a single access point for enterprise assets. It addresses challenges of accessing and storing data from various internal resources by building a well-structured integrated whole to enhance business processes.
Using the Semantic Web Stack to Make Big Data SmarterMatheus Mota
The document discusses using semantic web technologies to make big data smarter. It provides an overview of key concepts in semantic web, including linked data and ontologies. It describes how semantic web can add structure and meaning to unstructured data through modeling data as graphs and defining relationships and properties. The goal is to publish and query interconnected data at scale to enable new types of queries and inferences over big data.
This document discusses new ways of handling old data and unlocking value from unstructured content through cognitive systems. It provides predictions for big data and analytics spending and adoption through 2020. Key points include:
- 90% of digital information is unstructured content stored in separate repositories that don't communicate.
- By 2020, 50% of business analytics software will incorporate prescriptive analytics using cognitive computing.
- Organizations that can analyze all relevant data and provide actionable insights will gain $430 billion in productivity over less analytical peers.
- Cognitive software can support better decision-making by applying broader evidence without bias to situations.
- The cognitive software market is expected to grow rapidly over the next five
Smarter content with a Dynamic Semantic Publishing PlatformOntotext
Personalized content recommendation systems enable users to overcome the information overload associated with rapidly changing deep and wide content streams such as news. This webinar discusses Ontotext’s latest improvements to its Dynamic Semantic Publishing (DSP) platform NOW (News on the Web). The Platform includes social data mining, web usage mining, behavioral and contextual semantic fingerprinting, content typing and rich relationship search.
Linguamatics provides natural language processing (NLP) tools for text mining large amounts of biomedical text. Their software can extract facts and synthesize knowledge to help users find information. Linguamatics works with many pharmaceutical, government, and healthcare organizations. Their tools include terminology databases, rules for matching expressions, and visualization of query results.
This document discusses challenges and opportunities around discovering and using open government data. It notes that simply publishing data as linked data is not enough, and that metadata standards and presentation methods are needed to aid discovery and use. It highlights work done by Tetherless World Constellation to apply metadata standards to describe government datasets and create an aggregated catalog of over 1 million datasets. The use of schema.org and other semantic markup is discussed to enable search engines to more easily parse and index government data catalogs. Federation of catalogs using APIs and standards like DCAT and CKAN is also covered. The document emphasizes that exposing metadata is key to getting government data discovered.
II-SDV 2017: What is Innovation and how can we measure it?Dr. Haxel Consult
Innovation means many different things to many people. Ask five people and you will likely get ten answers. But all agree that it is a key driver behind the success of organizations, the growth of economies and provides major contributions in addressing global problems. This presentation will examine various analytical methods and possible metrics for measuring innovation and determining relative performance of organizations. The challenges involved in assessing innovation and how these can be addressed will be explored. The pros and cons associated with the metrics identified will also be discussed with a view to identifying a practical method for assessing innovation.
Open Research Gateway for the ELIXIR-GR Infrastructure (Part 1)OpenAIRE
The Research Data Alliance (RDA) is an international organization focused on data sharing across disciplines. It has over 8,600 members from 137 countries working to reduce barriers to data sharing through developing infrastructure and community activities. RDA has numerous active interest groups and working groups focused on issues like specific scientific domains, data reference and sharing, community needs, data stewardship, and basic infrastructure. One recent focus is guidelines for data sharing during the COVID-19 pandemic.
Linked Data efforts for data standards in biopharma and healthcareKerstin Forsberg
1) The document discusses efforts to represent biomedical data standards like CDISC, HL7 FHIR, MeSH, ICD-11, and others in semantic web formats like RDF and OWL to make them machine-processable.
2) It describes projects that have converted various standards to RDF through the work of groups like CDISC2RDF and PhUSE, and efforts to engage traditional standards bodies.
3) However, it notes that pushing standards organizations to adopt semantic web approaches requires ongoing knowledge sharing and community building, and that spreadsheets still see significant use.
Digital Science Presentation at ORCID Outreach Meeting (Ashlea Higgs)ORCID, Inc
This document summarizes several tools and platforms that integrate with ORCID profiles to help researchers manage their work and collaborations. It describes how Altmetric, Figshare, Overleaf, ReadCube, Symplectic Elements, and UberResearch integrate with ORCID to allow researchers to link publications and other research outputs to their ORCID profile, track metrics and attention for their work, and facilitate collaboration and information sharing between tools and platforms.
Linking Open, Big Data Using Semantic Web Technologies - An IntroductionRonald Ashri
The Physics Department of the University of Cagliari and the Linkalab Group invited me to talk about the Semantic Web and Linked Data - this is simply an introduction to the technologies involved.
Stephen Buxton | Data Integration - a Multi-Model Approach - Documents and Tr...semanticsconference
This document discusses when to use documents versus triples in a database. It describes the pros and cons of relational databases, document databases, graph databases, and triple stores. It advocates using a hybrid approach that combines documents and triples for the benefits of both. Documents are well-suited for storing heterogeneous data while triples enable modeling relationships and inferring new information. The combination provides a unified platform for querying rich data through semantics.
Understanding voice of the member via text miningChi-Yi Kuan
The 14th Text Analytics Summit - June 15, 2015 in New York
Today, Businesses around the world are increasingly collecting tremendous amount of unstructured data in the form of text – from multiple channels such as product reviews, market research, customer care conversations, and social media. In this talk, we will share how LinkedIn has built a text-mining platform to derive insights and create value for our members from the massive amount of data we have within our ecosystem. We will cover the following topics in our talk:
1) Topic modeling
2) Text categorization using NLP features
3) Topic-based sentiment analysis and attribution
The talk will be appropriate for business leaders, researchers and practitioners.
"Big data" is a broad term that encompasses a wide range of data and contents. Big data offers new approaches to analysis and decision making. At first glance big data and IP may seem to be opposites, but have more in common than one may think. This talk will focus on how big data will impact, and be impacted, by IP. One of the biggest promises in big data is the possibility to re-use data produced via different sources, create new services or predict the future, via the analysis of correlations. In this context, how can companies protect information assets and analytical skills? What are the new skills required to search and analyze in real time a big amount of datasets ? Big data will change not only patents information, but will also generate new types of patents.
See how the Simple Knowledge Organisation System (SKOS) can help to improve information management in various industries. The application scenarios are manifold, learn from real-world use cases.
Learn more about Semantic Web Company and the product. Find typical usage scenarios: Semantic search, concept tagging, topic pages, matchmaking, etc.
Success stories from various industry like pharma, health care, government, or retailing are presented.
Dudley dolan q-validus_big data_workshop_dcu_event_aqua_smart_march16_ finalAquaSmartData
This document discusses the potential for establishing a CEN Workshop on Big Data. It provides background on Dudley Dolan and his roles relating to standardization. It then discusses the CEN/CENELEC structure and existing CEN Workshop on ICT Skills. The document proposes creating a CEN Workshop for Big Data that focuses on industry sectors like aquaculture. It outlines the Aquasmart project, an EU-funded initiative using big data to improve aquaculture productivity by transforming data into knowledge. The project aims to develop an innovative cloud platform to help aquaculture companies improve performance and sustainability through data analytics. It discusses challenges and questions the approach could help answer. Finally, it outlines an approach to developing standards for
Skapa: International Online Marketing for West Sweden Chamber of Commerce, Ma...Erik Ekholm
This is a presentation about international online marketing I held for a group of CEOs, marketing and sales managers at the West Sweden Chamber of Commerce
Zurich Insurance is implementing the Alation Data Catalog to improve its data management and empower data scientists. Key points:
1) Zurich's previous metadata system was less user-friendly and did not allow dashboard views or efficient searching of objects. Alation automates metadata ingestion and provides improved search capabilities.
2) Users found Alation easier to use than the legacy system, with features like natural language search, data lineage tracing, and collaborative functions like commenting.
3) Zurich aims to integrate Alation with its data engineering tools to enable easier data discovery and reuse by data scientists. The catalog is a critical part of building a more data-driven organization.
1. The document discusses big data and the need to generate actionable insights from large amounts of data. It notes big data can help solve important problems in healthcare, transportation, energy and other industries.
2. Current methods for working with big data are not scalable and take too long to produce insights. More focus is needed on generating insights faster through applications that better leverage data scientists and domain experts.
3. Trident Capital has invested in big data solutions that produce quicker, higher-value insights for specific industries like healthcare, transportation, and energy. These more targeted industry applications provide a faster path to return on investment.
Linked data the next 5 years - From Hype to ActionAndreas Blumauer
How can we shape the future of Linked Data and the Semantic Web, to make it even more widely spread in enterprises and other organizations? Which developments around linked data technologies should we expect, and how can we implement various use cases successfully?
Build vs. Buy a Healthcare Enterprise Data Warehouse: Which is Best for You?Health Catalyst
Debating between building vs. buying your organization’s healthcare data warehouse? This presentation will explore the technical and organizational pros and cons of building vs. buying, as well as a third approach you may not have even considered.
Fair webinar, Ted slater: progress towards commercial fair data products and ...Pistoia Alliance
Elsevier is a global information analytics business that helps institutions and professional’s
advance healthcare and open science to improve performance for the benefit of humanity.
In this webinar, we discuss how Elsevier is increasingly leveraging the FAIR Guiding Principles to improve its products and services to better serve the scientific community.
EMEA Edison™ Accelerator Application Support WebinarWayra UK
The EMEA Edison™ Accelerator is a start-up and scale-up acceleration & healthcare provider collaboration programme designed by GE Healthcare in partnership with Wayra UK. It brings together healthcare providers, start-ups and scale-ups who want to leverage the GE Healthcare environment and mentoring to enhance their value proposition.
In the age of Big Data, filtering mechanisms have to professionalized to increase accessibility to data. This presentation, held at Knowledge Management Academy in Vienna, shows how technologies derived from the Semantic Web can help to establish more efficient means to manage data and information.
See why PoolParty is the most efficient thesaurus management tool on planet earth. See how to integrate PoolParty semantic technologies with SharePoint, Confluence or Drupal. With PoolParty Semantic Integrator complex queries can be executed: Combine text search with the power of knowledge graphs!
mHealth Symposium 2013 Continua Health Alliance3GDR
The Continua Health Alliance is an international non-profit organization with over 200 members from technology, medical device, telecom, health tech service, and healthcare industries. It publishes design guidelines to enable plug-and-play connectivity for personal health devices and services. The guidelines incorporate existing standards like 11073. Continua aims to promote widespread adoption of personal connected health solutions through certification, advocacy, and coordinating various industry partners and regional groups. Its guidelines are on track to become a global health standard adopted by the International Telecommunications Union.
1) Aegon is transforming into a data-driven organization by anchoring data science and building an analytical community.
2) They have made progress in establishing the culture, tools, skills, vision, and approaches needed for data science, but still have work to do in some areas like access to data and advanced analyses.
3) Aegon is building a global analytical committee, center of excellence, and academy to drive strategy, provide expertise and projects, and develop skills across the organization.
Use cases for Dynamic Semantic Publishing, presented at Taxonomy Boot Camp 2015 in Washington DC. DSP is not only about linking documents and analyzing text! It's about Personalization / ‘Connected Customer’: Better User Experience through Personalization. Create Smart Data Lakes through Linked Data: Linking Unstructured to Structured Data.
1) The document discusses how healthcare leaders can use smarter integrated cognitive solutions (SICS), such as IBM Watson, to improve customer satisfaction and business value.
2) IBM Watson allows healthcare organizations to understand large amounts of data, engage with patients in natural language, and make more informed decisions.
3) Adopting cognitive technologies like IBM Watson will help transform patient engagement and help healthcare organizations adapt to changing customer expectations.
While Graph Databases have come of age, Data Warehousing seems to be broken in an increasing dynamic world. Are Graph Databases a smarter version of Data Lakes?
In this webinar, Andreas Blumauer - CEO of Semantic Web Company discusses various approaches of data and information integration and the role knowledge graphs and taxonomies play in this game.
Numerous organizations already discovered Enterprise Linked Data as a powerful solution for a 360-degree view on various business objects. But how do they solve the big challenge of connecting their data pools in heterogeneous and highly dynamic information landscapes?
Learn more about the manifold application scenarios of linked data and semantic technologies. Dive into your data pools to gain new insights and knowledge!
PAREXEL's Matt Neal joins experts from Microsoft and Allergan to discuss how innovations in technology can help patients by reducing the time and expense of bringing life-saving treatments to market.
This document summarizes a panel discussion on building organizational innovation capabilities. It provides an agenda for the event, including introductions from panelists Todd Johnsen from Cushman & Wakefield, John English from Daedalus Consulting Group, and Patrick Crooks from Fusion Labs.
The panelists discussed challenges of building innovation in different types of organizations, from young startups to established incumbents. They addressed how to define search fields to focus innovation efforts, and the minimal requirements for effective innovation in incumbent organizations, including ambidexterity, leadership support, and culture.
Crooks outlined Fusion Lab's concept for building innovation capability, focusing on speed, customer-centric design, and de-ris
Similar to Success stories with Connected Data (20)
After the amazing breakthroughs of machine learning (deep learning or otherwise) in the past decade, the shortcomings of machine learning are also becoming increasingly clear: unexplainable results, data hunger and limited generalisability are all becoming bottlenecks.
In this talk we will look at how the combination with symbolic AI (in the form of very large knowledge graphs) can give us a way forward, towards machine learning systems that can explain their results, that need less data, and that generalise better outside their training set.
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Frank van Harmelen leads the Knowledge Representation & Reasoning group in the CS Department of the VU University Amsterdam. He is also Principal investigator of the Hybrid Intelligence Centre, a 20Μ€, 10 year collaboration between researchers at 6 Dutch universities into AI that collaborates with people instead of replacing them.
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While mathematicians have used graph theory since the 18th century to solve problems, the software patterns for graph data are new to most developers. To enable "mass adoption" of graph technology, we need to establish the right abstractions, access APIs, and data models.
RDF triples, while of paramount importance in establishing RDF graph semantics, are a low-level abstraction, much like using assembly language. For practical and productive “graph programming” we need something different.
Similarly, existing declarative graph query languages (such as SPARQL and Cypher) are not always the best way to access graph data, and sometimes you need a simpler interface (e.g., GraphQL), or even a different approach altogether (e.g., imperative traversals such as with Gremlin).
Ora Lassila is a Principal Graph Technologist in the Amazon Neptune graph database group. He has a long experience with graphs, graph databases, ontologies, and knowledge representation. He was a co-author of the original RDF specification as well as a co-author of the seminal article on the Semantic Web.
Κnowledge Architecture: Combining Strategy, Data Science and Information Arch...Connected Data World
"The most important contribution management needs to make in the 21st Century is to increase the productivity of knowledge work and the knowledge worker", said Peter F. Drucker in 1999, and time has proven him right.
Even NASA is no exception, as it faces a number of challenges. NASA has hundreds of millions of documents, reports, project data, lessons learned, scientific research, medical analysis, geospatial data, IT logs, and all kinds of other data stored nation-wide.
The data is growing in terms of variety, velocity, volume, value and veracity. NASA needs to provide accessibility to engineering data sources, whose visibility is currently limited. To convert data to knowledge a convergence of Knowledge Management, Information Architecture and Data Science is necessary.
This is what David Meza, Acting Branch Chief - People Analytics, Sr. Data Scientist at NASA, calls "Knowledge Architecture": the people, processes, and technology of designing, implementing, and applying the intellectual infrastructure of organizations.
A talk by Aleksa Gordic | Software - Deep Learning engineer, Microsoft | The AI Epiphany
What can you learn about Graph Machine Learning in 2 months?
Aleksa Gordic, Machine Learning engineer @ Microsoft and Founder @ The AI Epiphany, shares his journey in the world of Graph Machine Learning. Aleksa started exploring the basics in the world of Graph Machine Learning, and ended up implementing and open sourcing his own Graph Attention Network on PyTorch.
In this talk, Aleksa will share the fundamentals of Graph Machine Learning, provide real-world examples, resources, and everything his younger self would be grateful for. Aleksa will also be available to answer questions.
What is Graph Machine Learning? Simply put, Graph Machine Learning is a branch of machine learning that deals with graph data.
Graphs consist of nodes, that may have feature vectors associated with them, and edges, which again may or may not have feature vectors attached. The applications are endless. Massive-scale recommender systems, particle physics, computational pharmacology / chemistry / biology, traffic prediction, fake news detection, and the list goes on and on.
In recent years graphs have been increasingly adopted in financial services for everything from fraud detection to Know Your Customer (KYC) to regulatory requirements. At the same time Environmental Social Governance (ESG) investing has become the fastest growing segment of financial services. In this session James discusses how many of these historical graph techniques are now being enhanced for the era of sustainable investing. Going beyond definitions, let's identify use cases, discuss news and trends, and wrap up with an ask me anything session.
What is graph all about, and why should you care? Graphs come in many shapes and forms, and can be used for different applications: Graph Analytics, Graph AI, Knowledge Graphs, and Graph Databases.
Talk by George Anadiotis. Connected Data London Meetup June 29th 2020.
Up until the beginning of the 2010s, the world was mostly running on spreadsheets and relational databases. To a large extent, it still does. But the NoSQL wave of databases has largely succeeded in instilling the “best tool for the job” mindset.
After relational, key-value, document, and columnar, the latest link in this evolutionary proliferation of data structures is graph. Graph analytics, Graph AI, Knowledge Graphs and Graph Databases have been making waves, included in hype cycles for the last couple of years.
The Year of the Graph marked the beginning of it all before the Gartners of the world got in the game. The Year of the Graph is a term coined to convey the fact that the time has come for this technology to flourish.
The eponymous article that set the tone was published in January 2018 on ZDNet by domain expert George Anadiotis. George has been working with, and keeping an eye on, all things Graph since the early 2000s. He was one of the first to note the continuing rise of Graph Databases, and to bring this technology in front of a mainstream audience.
The Year of the Graph has been going strong since 2018. In August 2018, Gartner started including Graph in its hype cycles. Ever since, Graph has been riding the upward slope of the Hype Cycle.
The need for knowledge on these technologies is constantly growing. To respond to that need, the Year of the Graph newsletter was released in April 2018. In addition, a constant flow of graph-related news and resources is being shared on social media.
To help people make educated choices, the Year of the Graph Database Report was released. The report has been hailed as the most comprehensive of its kind in the market, consistently helping people choose the most appropriate solution for their use case since 2018.
The report, articles, news stream, and the newsletter have been reaching thousands of people, helping them understand and navigate this landscape. We’ll talk about the Year of the Graph, the different shapes, forms, and applications for graphs, the latest news and trends, and wrap up with an ask me anything session.
From Taxonomies and Schemas to Knowledge Graphs: Parts 1 & 2Connected Data World
Do you have experience in data modeling, or using taxonomies to classify things, and want to upgrade to modeling knowledge graphs? This hands-on workshop with one of the leading knowledge graph practitioners will help you get started.
Parts 1 & 2
Do you have experience in data modeling, or using taxonomies to classify things, and want to upgrade to modeling knowledge graphs? This hands-on workshop with one of the leading knowledge graph practitioners will help you get started.
Part 3
For as long as people have been thinking about thinking, we have imagined that somewhere in the inner reaches of our minds there are ghostly, intangible things called ideas which can be linked together to create representations of the world around us — a world that has a certain structure, conforms to certain rules, and to a certain extent, can be predicted and manipulated on the basis of our ideas.
Rationalist philosophers have struggled for centuries to make a solid case for this intuitive, almost inborn view of human experience, but it is only with the advent of modern computing that we have the opportunity to build machines which truly think the way we think we think.
For the first time, we can give concrete form to our mental representations as graphs or hypergraphs, explicitly specify our mental schemas as ontologies, and formally define the rules by which we reason and act on new information. If we so choose, we can even use these human-like building blocks to construct systems that carry far more information than any single human brain, and that connect and serve millions of people in real time.
As enterprise knowledge graphs become increasingly mainstream, we appear to be headed in that direction, although there is no guarantee that the momentum will continue unless actively sustained. Where knowledge graphs are likely to be the most essential, in the long run, is at the interface between human and machine; mental representation versus formal knowledge representation.
In this talk, we will take a step back from the many practical and social challenges of building large-scale knowledge graphs, which at this point are well-known. Instead, we will take up the quest for an ideal data model for knowledge representation and data integration, seeking common ground among the most popular data models used in industry and open source software, surveying what we suspect to be true of our own inner models, and previewing structure and process in Apache TinkerPop, version 4. We will also take a tentative step forward into the world of augmented perception via graph stream processing.
Graph in Apache Cassandra. The World’s Most Scalable Graph DatabaseConnected Data World
1. Building a graph database requires modeling the data, choosing a query language, and providing storage.
2. Existing distributed databases like Cassandra can be used for storage due to their scalability and reliability, though a native graph database provides more functionality.
3. Solving complex graph problems requires capabilities beyond basic queries, including search, analytics, and integration with machine learning, which graph databases are designed to support at scale.
Enterprise Data Governance: Leveraging Knowledge Graph & AI in support of a d...Connected Data World
As one of the largest financial institutions worldwide, JP Morgan is reliant on data to drive its day-to-day operations, against an ever evolving regulatory regime. Our global data landscape possesses particular challenges of effectively maintaining data governance and metadata management.
The Data strategy at JP Morgan intends to:
a) generate business value
b) adhere to regulatory & compliance requirements
c) reduce barriers to access
d) democratize access to data
In this talk, we show how JP Morgan leverages semantic technologies to drive the implementation of our data strategy. We demonstrate how we exploit knowledge graph capabilities to answer:
1) What Data do I need?
2) What Data do we have?
3) Where does my Data come from?
4) Where should my Data come from?
5) What Data should be shared most?
Graph applications were once considered “exotic” and expensive. Until recently, few software engineers had much experience putting graphs to work. However, the use cases are now becoming more commonplace.
This talk explores a practical use case, one which addresses key issues of data governance and reproducible research, and depends on sophisticated use of graph technology.
Consider: some academic disciplines such as astronomy enjoy a wealth of data — mostly open data. Popular machine learning algorithms, open source Python libraries, and distributed systems all owe much to those disciplines and their history of big data.
Other disciplines require strong guarantees for privacy and security. Datasets used in social science research involve confidential details about human subjects: medical histories, wages, home addresses for family members, police records, etc.
Those cannot be shared openly, which impedes researchers from learning about related work by others. Reproducibility of research and the pace of science in general are limited. Nonetheless, social science research is vital for civil governance, especially for evidence-based policymaking (US federal law since 2018).
Even when data may be too sensitive to share openly, often the metadata can be shared. Constructing knowledge graphs of metadata about datasets — along with metadata about authors, their published research, methods used, data providers, data stewards, and so on — that provides effective means to tackle hard problems in data governance.
Knowledge graph work supports use cases such as entity linking, discovery and recommendations, axioms to infer about compliance, etc. This talk reviews the Rich Context AI competition and the related ADRF framework used now by more than 15 federal agencies in the US.
We’ll explore knowledge graph use cases, use of open standards and open source, and how this enhances reproducible research. Social science research for the public sector has much in common with data use in industry.
Issues of privacy, security, and compliance overlap, pointing toward what will be required of banks, media channels, etc., and what technologies apply. We’ll look at comparable work emerging in other parts of industry: open source projects, open standards emerging, and in particular a new set of features in Project Jupyter that support knowledge graphs about data governance.
Powering Question-Driven Problem Solving to Improve the Chances of Finding Ne...Connected Data World
Samiul Hasan discusses using question-driven problem solving and data analytics to improve drug discovery at GSK. He outlines aspirations to efficiently organize hypotheses and ensure scientists have access to relevant data and knowledge. Inconsistent language use can cause problems, so self-learning questionnaires could help tag metadata and search literature to improve consistency. Examples of possible algorithms include named entity recognition to determine context, document classification to present similar content, and trigger event detection to alert authors. A pilot found the approach uncovered missed evidence and hypotheses. Hasan concludes technology can help questions drive problem solving if applied persistently and patiently.
Semantic similarity for faster Knowledge Graph delivery at scaleConnected Data World
Knowledge graphs promise a novel platform for better holistic decision making and analytics. Many projects fail to reach their full potential because of the prohibitively high cost of integrating new knowledge from the required information sources.
The talk explains the concept of semantic similarity as a tool for efficient entity clustering and matching based on graph and text embeddings. It will demonstrate the underlying scalable and easy to understand algorithm of Random Indexing.
This work is part of the Ontotext Platform, which increases productivity in developing and maintaining large scale knowledge graphs. The platform enables enterprises to develop and operate on top of such mission-critical systems for decision support, information discovery and metadata management.
Knowledge Graphs and AI to Hyper-Personalise the Fashion Retail Experience at...Connected Data World
What is the key to the holistic success of the fastest growing and most successful companies of our time globally? Well, often the key is the rapid increase in collected and analysed data. Graph databases provide a way to organise semantically by classes, not tables, are web-aware, and are superior for handling deep, complex relationships than traditional relational or NoSQL data stores.
It is these deep, complex relationships that can provide the rich context for hyper-personalising your product offering, inspiring consumers to purchase. In this talk, we describe how we are using artificial intelligence at Farfetch to not only help build a knowledge graph but also to evolve our insights with state-of-the-art graph-based AI.
A world of structured data promises us an incredible future. But most websites struggle to even implement basic schema.org markup. Fewer still represent and connect their pages and content in sophisticated, structured graphs. We can’t reach that incredible future without increasing and improving adoption.
To move forward, we need to make constructing rich structured data as easy as writing a recipe. This isn’t a pipe dream: at Yoast, we think we’ve solved schema for everybody, everywhere. We’d love to share our story.
The relationships between data sets matter. Discovering, analyzing, and learning those relationships is a central part to expanding our understand, and is a critical step to being able to predict and act upon the data. Unfortunately, these are not always simple or quick tasks.
To help the analyst we introduce RAPIDS, a collection of open-source libraries, incubated by NVIDIA and focused on accelerating the complete end-to-end data science ecosystem. Graph analytics is a critical piece of the data science ecosystem for processing linked data, and RAPIDS is pleased to offer cuGraph as our accelerated graph library.
Simply accelerating algorithms only addressed a portion of the problem. To address the full problem space, RAPIDS cuGraph strives to be feature-rich, easy to use, and intuitive. Rather than limiting the solution to a single graph technology, cuGraph supports Property Graphs, Knowledge Graphs, Hyper-Graphs, Bipartite graphs, and the basic directed and undirected graph.
A Python API allows the data to be manipulated as a DataFrame, similar and compatible with Pandas, with inputs and outputs being shared across the full RAPIDS suite, for example with the RAPIDS machine learning package, cuML.
This talk will present an overview of RAPIDS and cuGraph. Discuss and show examples of how to manipulate and analyze bipartite and property graph, plus show how data can be shared with machine learning algorithms. The talk will include some performance and scalability metrics. Then conclude with a preview of upcoming features, like graph query language support, and the general RAPIDS roadmap.
Elegant and Scalable Code Querying with Code Property GraphsConnected Data World
Programming is an unforgiving art form in which even minor flaws can cause rockets to explode, data to be stolen, and systems to be compromised. Today, a system tasked to automatically identify these flaws not only faces the intrinsic difficulties and theoretical limits of the task itself, it must also account for the many different forms in which programs can be formulated and account for the awe-inspiring speed at which developers push new code into CI/CD pipelines. So much code, so little time.
The code property graph – a multi-layered graph representation of code that captures properties of code across different abstractions – (application code, libraries and frameworks) – has been developed over the last six years to provide a foundation for the challenging problem of identifying flaws in program code at scale, whether it is high-level dynamically-typed Javascript, statically-typed Scala in its bytecode form, the syntax trees generated by Roslyn C# compiler, or the bitcode that flows through LLVM.
Based on this graph, we define a common query language based on formal code property graph specification to elegantly analyze code regardless of the source language. Paired with the formulation of a state-of-the-art data flow tracker based on code property graphs, we arrive at a distributed cloud native powerful code analysis. This talk provides an introduction to the technology.
From Knowledge Graphs to AI-powered SEO: Using taxonomies, schemas and knowle...Connected Data World
Do you want to learn how to use the low-hanging fruit of knowledge graphs — schema.org and JSON-LD — to annotate content and improve your SEO with semantics and entities? This hands-on workshop with one of the leading Semantic SEO practitioners will help you get started.
This document discusses empowering NGOs with graph technology. It describes a pilot project between Action Against Hunger Spain and Graphs for Good to use graph databases and analytics. The goals are to improve knowledge management by modeling complex relationships between data, enable qualitative analysis, and democratize data access to enhance decision making, accountability, and stakeholder engagement while addressing challenges around resources, security, and long-term planning.
AI 101: An Introduction to the Basics and Impact of Artificial IntelligenceIndexBug
Imagine a world where machines not only perform tasks but also learn, adapt, and make decisions. This is the promise of Artificial Intelligence (AI), a technology that's not just enhancing our lives but revolutionizing entire industries.
HCL Notes und Domino Lizenzkostenreduzierung in der Welt von DLAUpanagenda
Webinar Recording: https://www.panagenda.com/webinars/hcl-notes-und-domino-lizenzkostenreduzierung-in-der-welt-von-dlau/
DLAU und die Lizenzen nach dem CCB- und CCX-Modell sind für viele in der HCL-Community seit letztem Jahr ein heißes Thema. Als Notes- oder Domino-Kunde haben Sie vielleicht mit unerwartet hohen Benutzerzahlen und Lizenzgebühren zu kämpfen. Sie fragen sich vielleicht, wie diese neue Art der Lizenzierung funktioniert und welchen Nutzen sie Ihnen bringt. Vor allem wollen Sie sicherlich Ihr Budget einhalten und Kosten sparen, wo immer möglich. Das verstehen wir und wir möchten Ihnen dabei helfen!
Wir erklären Ihnen, wie Sie häufige Konfigurationsprobleme lösen können, die dazu führen können, dass mehr Benutzer gezählt werden als nötig, und wie Sie überflüssige oder ungenutzte Konten identifizieren und entfernen können, um Geld zu sparen. Es gibt auch einige Ansätze, die zu unnötigen Ausgaben führen können, z. B. wenn ein Personendokument anstelle eines Mail-Ins für geteilte Mailboxen verwendet wird. Wir zeigen Ihnen solche Fälle und deren Lösungen. Und natürlich erklären wir Ihnen das neue Lizenzmodell.
Nehmen Sie an diesem Webinar teil, bei dem HCL-Ambassador Marc Thomas und Gastredner Franz Walder Ihnen diese neue Welt näherbringen. Es vermittelt Ihnen die Tools und das Know-how, um den Überblick zu bewahren. Sie werden in der Lage sein, Ihre Kosten durch eine optimierte Domino-Konfiguration zu reduzieren und auch in Zukunft gering zu halten.
Diese Themen werden behandelt
- Reduzierung der Lizenzkosten durch Auffinden und Beheben von Fehlkonfigurationen und überflüssigen Konten
- Wie funktionieren CCB- und CCX-Lizenzen wirklich?
- Verstehen des DLAU-Tools und wie man es am besten nutzt
- Tipps für häufige Problembereiche, wie z. B. Team-Postfächer, Funktions-/Testbenutzer usw.
- Praxisbeispiele und Best Practices zum sofortigen Umsetzen
Introduction of Cybersecurity with OSS at Code Europe 2024Hiroshi SHIBATA
I develop the Ruby programming language, RubyGems, and Bundler, which are package managers for Ruby. Today, I will introduce how to enhance the security of your application using open-source software (OSS) examples from Ruby and RubyGems.
The first topic is CVE (Common Vulnerabilities and Exposures). I have published CVEs many times. But what exactly is a CVE? I'll provide a basic understanding of CVEs and explain how to detect and handle vulnerabilities in OSS.
Next, let's discuss package managers. Package managers play a critical role in the OSS ecosystem. I'll explain how to manage library dependencies in your application.
I'll share insights into how the Ruby and RubyGems core team works to keep our ecosystem safe. By the end of this talk, you'll have a better understanding of how to safeguard your code.
Webinar: Designing a schema for a Data WarehouseFederico Razzoli
Are you new to data warehouses (DWH)? Do you need to check whether your data warehouse follows the best practices for a good design? In both cases, this webinar is for you.
A data warehouse is a central relational database that contains all measurements about a business or an organisation. This data comes from a variety of heterogeneous data sources, which includes databases of any type that back the applications used by the company, data files exported by some applications, or APIs provided by internal or external services.
But designing a data warehouse correctly is a hard task, which requires gathering information about the business processes that need to be analysed in the first place. These processes must be translated into so-called star schemas, which means, denormalised databases where each table represents a dimension or facts.
We will discuss these topics:
- How to gather information about a business;
- Understanding dictionaries and how to identify business entities;
- Dimensions and facts;
- Setting a table granularity;
- Types of facts;
- Types of dimensions;
- Snowflakes and how to avoid them;
- Expanding existing dimensions and facts.
5th LF Energy Power Grid Model Meet-up SlidesDanBrown980551
5th Power Grid Model Meet-up
It is with great pleasure that we extend to you an invitation to the 5th Power Grid Model Meet-up, scheduled for 6th June 2024. This event will adopt a hybrid format, allowing participants to join us either through an online Mircosoft Teams session or in person at TU/e located at Den Dolech 2, Eindhoven, Netherlands. The meet-up will be hosted by Eindhoven University of Technology (TU/e), a research university specializing in engineering science & technology.
Power Grid Model
The global energy transition is placing new and unprecedented demands on Distribution System Operators (DSOs). Alongside upgrades to grid capacity, processes such as digitization, capacity optimization, and congestion management are becoming vital for delivering reliable services.
Power Grid Model is an open source project from Linux Foundation Energy and provides a calculation engine that is increasingly essential for DSOs. It offers a standards-based foundation enabling real-time power systems analysis, simulations of electrical power grids, and sophisticated what-if analysis. In addition, it enables in-depth studies and analysis of the electrical power grid’s behavior and performance. This comprehensive model incorporates essential factors such as power generation capacity, electrical losses, voltage levels, power flows, and system stability.
Power Grid Model is currently being applied in a wide variety of use cases, including grid planning, expansion, reliability, and congestion studies. It can also help in analyzing the impact of renewable energy integration, assessing the effects of disturbances or faults, and developing strategies for grid control and optimization.
What to expect
For the upcoming meetup we are organizing, we have an exciting lineup of activities planned:
-Insightful presentations covering two practical applications of the Power Grid Model.
-An update on the latest advancements in Power Grid -Model technology during the first and second quarters of 2024.
-An interactive brainstorming session to discuss and propose new feature requests.
-An opportunity to connect with fellow Power Grid Model enthusiasts and users.
Monitoring and Managing Anomaly Detection on OpenShift.pdfTosin Akinosho
Monitoring and Managing Anomaly Detection on OpenShift
Overview
Dive into the world of anomaly detection on edge devices with our comprehensive hands-on tutorial. This SlideShare presentation will guide you through the entire process, from data collection and model training to edge deployment and real-time monitoring. Perfect for those looking to implement robust anomaly detection systems on resource-constrained IoT/edge devices.
Key Topics Covered
1. Introduction to Anomaly Detection
- Understand the fundamentals of anomaly detection and its importance in identifying unusual behavior or failures in systems.
2. Understanding Edge (IoT)
- Learn about edge computing and IoT, and how they enable real-time data processing and decision-making at the source.
3. What is ArgoCD?
- Discover ArgoCD, a declarative, GitOps continuous delivery tool for Kubernetes, and its role in deploying applications on edge devices.
4. Deployment Using ArgoCD for Edge Devices
- Step-by-step guide on deploying anomaly detection models on edge devices using ArgoCD.
5. Introduction to Apache Kafka and S3
- Explore Apache Kafka for real-time data streaming and Amazon S3 for scalable storage solutions.
6. Viewing Kafka Messages in the Data Lake
- Learn how to view and analyze Kafka messages stored in a data lake for better insights.
7. What is Prometheus?
- Get to know Prometheus, an open-source monitoring and alerting toolkit, and its application in monitoring edge devices.
8. Monitoring Application Metrics with Prometheus
- Detailed instructions on setting up Prometheus to monitor the performance and health of your anomaly detection system.
9. What is Camel K?
- Introduction to Camel K, a lightweight integration framework built on Apache Camel, designed for Kubernetes.
10. Configuring Camel K Integrations for Data Pipelines
- Learn how to configure Camel K for seamless data pipeline integrations in your anomaly detection workflow.
11. What is a Jupyter Notebook?
- Overview of Jupyter Notebooks, an open-source web application for creating and sharing documents with live code, equations, visualizations, and narrative text.
12. Jupyter Notebooks with Code Examples
- Hands-on examples and code snippets in Jupyter Notebooks to help you implement and test anomaly detection models.
Have you ever been confused by the myriad of choices offered by AWS for hosting a website or an API?
Lambda, Elastic Beanstalk, Lightsail, Amplify, S3 (and more!) can each host websites + APIs. But which one should we choose?
Which one is cheapest? Which one is fastest? Which one will scale to meet our needs?
Join me in this session as we dive into each AWS hosting service to determine which one is best for your scenario and explain why!
Let's Integrate MuleSoft RPA, COMPOSER, APM with AWS IDP along with Slackshyamraj55
Discover the seamless integration of RPA (Robotic Process Automation), COMPOSER, and APM with AWS IDP enhanced with Slack notifications. Explore how these technologies converge to streamline workflows, optimize performance, and ensure secure access, all while leveraging the power of AWS IDP and real-time communication via Slack notifications.
UiPath Test Automation using UiPath Test Suite series, part 6DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 6. In this session, we will cover Test Automation with generative AI and Open AI.
UiPath Test Automation with generative AI and Open AI webinar offers an in-depth exploration of leveraging cutting-edge technologies for test automation within the UiPath platform. Attendees will delve into the integration of generative AI, a test automation solution, with Open AI advanced natural language processing capabilities.
Throughout the session, participants will discover how this synergy empowers testers to automate repetitive tasks, enhance testing accuracy, and expedite the software testing life cycle. Topics covered include the seamless integration process, practical use cases, and the benefits of harnessing AI-driven automation for UiPath testing initiatives. By attending this webinar, testers, and automation professionals can gain valuable insights into harnessing the power of AI to optimize their test automation workflows within the UiPath ecosystem, ultimately driving efficiency and quality in software development processes.
What will you get from this session?
1. Insights into integrating generative AI.
2. Understanding how this integration enhances test automation within the UiPath platform
3. Practical demonstrations
4. Exploration of real-world use cases illustrating the benefits of AI-driven test automation for UiPath
Topics covered:
What is generative AI
Test Automation with generative AI and Open AI.
UiPath integration with generative AI
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
Digital Marketing Trends in 2024 | Guide for Staying AheadWask
https://www.wask.co/ebooks/digital-marketing-trends-in-2024
Feeling lost in the digital marketing whirlwind of 2024? Technology is changing, consumer habits are evolving, and staying ahead of the curve feels like a never-ending pursuit. This e-book is your compass. Dive into actionable insights to handle the complexities of modern marketing. From hyper-personalization to the power of user-generated content, learn how to build long-term relationships with your audience and unlock the secrets to success in the ever-shifting digital landscape.
Ivanti’s Patch Tuesday breakdown goes beyond patching your applications and brings you the intelligence and guidance needed to prioritize where to focus your attention first. Catch early analysis on our Ivanti blog, then join industry expert Chris Goettl for the Patch Tuesday Webinar Event. There we’ll do a deep dive into each of the bulletins and give guidance on the risks associated with the newly-identified vulnerabilities.
Skybuffer SAM4U tool for SAP license adoptionTatiana Kojar
Manage and optimize your license adoption and consumption with SAM4U, an SAP free customer software asset management tool.
SAM4U, an SAP complimentary software asset management tool for customers, delivers a detailed and well-structured overview of license inventory and usage with a user-friendly interface. We offer a hosted, cost-effective, and performance-optimized SAM4U setup in the Skybuffer Cloud environment. You retain ownership of the system and data, while we manage the ABAP 7.58 infrastructure, ensuring fixed Total Cost of Ownership (TCO) and exceptional services through the SAP Fiori interface.
Cosa hanno in comune un mattoncino Lego e la backdoor XZ?Speck&Tech
ABSTRACT: A prima vista, un mattoncino Lego e la backdoor XZ potrebbero avere in comune il fatto di essere entrambi blocchi di costruzione, o dipendenze di progetti creativi e software. La realtà è che un mattoncino Lego e il caso della backdoor XZ hanno molto di più di tutto ciò in comune.
Partecipate alla presentazione per immergervi in una storia di interoperabilità, standard e formati aperti, per poi discutere del ruolo importante che i contributori hanno in una comunità open source sostenibile.
BIO: Sostenitrice del software libero e dei formati standard e aperti. È stata un membro attivo dei progetti Fedora e openSUSE e ha co-fondato l'Associazione LibreItalia dove è stata coinvolta in diversi eventi, migrazioni e formazione relativi a LibreOffice. In precedenza ha lavorato a migrazioni e corsi di formazione su LibreOffice per diverse amministrazioni pubbliche e privati. Da gennaio 2020 lavora in SUSE come Software Release Engineer per Uyuni e SUSE Manager e quando non segue la sua passione per i computer e per Geeko coltiva la sua curiosità per l'astronomia (da cui deriva il suo nickname deneb_alpha).
Main news related to the CCS TSI 2023 (2023/1695)Jakub Marek
An English 🇬🇧 translation of a presentation to the speech I gave about the main changes brought by CCS TSI 2023 at the biggest Czech conference on Communications and signalling systems on Railways, which was held in Clarion Hotel Olomouc from 7th to 9th November 2023 (konferenceszt.cz). Attended by around 500 participants and 200 on-line followers.
The original Czech 🇨🇿 version of the presentation can be found here: https://www.slideshare.net/slideshow/hlavni-novinky-souvisejici-s-ccs-tsi-2023-2023-1695/269688092 .
The videorecording (in Czech) from the presentation is available here: https://youtu.be/WzjJWm4IyPk?si=SImb06tuXGb30BEH .
Generating privacy-protected synthetic data using Secludy and MilvusZilliz
During this demo, the founders of Secludy will demonstrate how their system utilizes Milvus to store and manipulate embeddings for generating privacy-protected synthetic data. Their approach not only maintains the confidentiality of the original data but also enhances the utility and scalability of LLMs under privacy constraints. Attendees, including machine learning engineers, data scientists, and data managers, will witness first-hand how Secludy's integration with Milvus empowers organizations to harness the power of LLMs securely and efficiently.
Threats to mobile devices are more prevalent and increasing in scope and complexity. Users of mobile devices desire to take full advantage of the features
available on those devices, but many of the features provide convenience and capability but sacrifice security. This best practices guide outlines steps the users can take to better protect personal devices and information.
2. SELECTED
CUSTOMER
REFERENCES
AND PARTNERS
SWC head-
quarters
2
Customer References
● Credit Suisse
● Boehringer Ingelheim
● Roche
● adidas
● The Pokémon Company
● Canadian Broadcasting Corporation
● Red Bull Media House
● Wolters Kluwer
● Bank of America
● HealthStream
● TC Media
● Techtarget
● BMJ Publishing Group
● CafePress
● Pearson - Always Learning
● Education Services Australia
● American Physical Society
● Healthdirect Australia
● World Bank Group
● Inter-American Development Bank
● Renewable Energy Partnership
● Wood MacKenzie
● Oxford University Press
● International Atomic Energy Agency
● Norwegian Directorate of Immigration
● Ministry of Finance (AT)
● Council of the E.U.
● Australian National Data Service
Partners
● Accenture
● EPAM Systems
● Enterprise Knowledge
● Tellura
● MarkLogic
● Solnet Solutions
● Wolters Kluwer
● Mekon
● Data to Value
● Ontotext
US
East
US
West
AUS/
NZL
UK
5. Selected
Success
Stories
▸ healthdirect Australia
Semantic features based on the Australian Health Thesaurus
▸ Climate Tagger
Streamline and catalogue data and information resources
▸ Boehringer Ingelheim
Scientific Information Tracking Service
5
6. Place your screenshot here
6healthdirect
Australia
Integrated views and
semantic search over more
than 100 trusted sources.
Harmonization of various
metadata systems through
the use of a central
vocabulary hub:
Australian Health Thesaurus.
http://www.healthdirect.gov.au
7. Place your screenshot here
7Climate Tagger
Help organizations in the
climate and development
arenas catalogue, categorize,
contextualize, and connect
data and information
resources.
Climate Tagger is backed by
the expansive Climate Smart
Development Thesaurus.
http://www.climatetagger.net
8. Place your screenshot here
8Boehringer
Ingelheim
A single point of access application
helps the head of science to track
the publication activities of the
company’s global workforce.
The data normalization is managed
in the PoolParty Thesaurus Server.
Scientific Information Tracking Service
9. More
Usage Scenarios
▸ Topic Pages
Creating landing pages on-the-fly from different content sources
▸ Matchmaking
Accurate recommender services based on semantic ‘fingerprinting’
▸ Data Publishing
Making available 5* Linked Data
▸ Personalisation
Personalising user experience with brands and products in a data
driven task
Find more: https://www.poolparty.biz/download-zone/
10. PoolParty
Semantic
Integrator -
at a glance
https://youtu.be/l_LppfS3wxk
10
Deep Data
Analytics
Semantic
Search
Semantic
Integrator
Unstructured
Data
Structured
Data
ETL / Monitoring / Scheduling