Exploring legacy ware with rdf and survol.17 july 2018Remi Chateauneu
Lab49 Semantic Web London meetup on July 17th.
Survol is Primhill Computer's Software Intelligence tool to analyse and investigate running applications and legacy information systems in-situ. It is based on RDF and CIM.
Need for Systems Analysis & Design-19Jul2016Conrad Sebego
The document discusses the need for systems analysis and design to properly plan and implement computerized information systems. It notes that systems analysis seeks to understand user needs to analyze, process, store, and output data in the context of an organization. Proper planning through systems analysis and design structures the analysis and design process to improve businesses through information systems and prevent user dissatisfaction. The document emphasizes the importance of user involvement throughout the systems development process. It also discusses how new technologies like Ajax are driving additional needs for systems analysis.
The document discusses spreadsheet composition, which involves linking Excel spreadsheets together to enable collaborative data analysis. It introduces the concept of a "spreadsheet space" that allows spreadsheets to be linked across the internet similar to how web pages are linked on the world wide web. The key aspects covered include:
- Defining base services as Excel spreadsheets that can publish or collect data from other spreadsheets.
- Composite services that involve distributed spreadsheets belonging to different users that are linked together.
- The spreadsheet space software platform that provides persistence and synchronization of linked spreadsheets using a server.
- How information systems can expose data through the spreadsheet space to allow users to integrate and analyze corporate data.
This document discusses reading structured data into R from various sources. It covers reading delimited files such as CSV files using read.csv() and read.table(), reading Excel files using packages like XLConnect, reading from databases using RODBC, and extracting data from websites using XML and regular expressions. Packages are available for importing data from other statistical programs as well.
Slideshow component of a presentation I gave at a GRASAC conference on June 13th, 2014. Outlines my thought process and design solutions I implemented through a spreadsheet that enabled effective museum records data transfer to GRASAC's online database.
The document provides an overview of a presentation on web development submitted to the Head of Department (HOD) at Naraina College of Engineering & Technology. It discusses key topics like database design, creating tables in MS Access, writing queries, developing forms, and creating and printing reports. The presentation covers what MS Access is, its advantages and disadvantages, how to create tables and write queries, and how Access can be used to develop the front end and print reports from a database.
This document outlines information extraction tasks. It discusses information integration, generating extractors, and different types of extractors including unsupervised and supervised. It describes how God uses unsupervised and supervised extractors to integrate information from multiple sources with only a few clicks without programming ability. The document also discusses real-time and background phases of information integration tasks.
Exploring legacy ware with rdf and survol.17 july 2018Remi Chateauneu
Lab49 Semantic Web London meetup on July 17th.
Survol is Primhill Computer's Software Intelligence tool to analyse and investigate running applications and legacy information systems in-situ. It is based on RDF and CIM.
Need for Systems Analysis & Design-19Jul2016Conrad Sebego
The document discusses the need for systems analysis and design to properly plan and implement computerized information systems. It notes that systems analysis seeks to understand user needs to analyze, process, store, and output data in the context of an organization. Proper planning through systems analysis and design structures the analysis and design process to improve businesses through information systems and prevent user dissatisfaction. The document emphasizes the importance of user involvement throughout the systems development process. It also discusses how new technologies like Ajax are driving additional needs for systems analysis.
The document discusses spreadsheet composition, which involves linking Excel spreadsheets together to enable collaborative data analysis. It introduces the concept of a "spreadsheet space" that allows spreadsheets to be linked across the internet similar to how web pages are linked on the world wide web. The key aspects covered include:
- Defining base services as Excel spreadsheets that can publish or collect data from other spreadsheets.
- Composite services that involve distributed spreadsheets belonging to different users that are linked together.
- The spreadsheet space software platform that provides persistence and synchronization of linked spreadsheets using a server.
- How information systems can expose data through the spreadsheet space to allow users to integrate and analyze corporate data.
This document discusses reading structured data into R from various sources. It covers reading delimited files such as CSV files using read.csv() and read.table(), reading Excel files using packages like XLConnect, reading from databases using RODBC, and extracting data from websites using XML and regular expressions. Packages are available for importing data from other statistical programs as well.
Slideshow component of a presentation I gave at a GRASAC conference on June 13th, 2014. Outlines my thought process and design solutions I implemented through a spreadsheet that enabled effective museum records data transfer to GRASAC's online database.
The document provides an overview of a presentation on web development submitted to the Head of Department (HOD) at Naraina College of Engineering & Technology. It discusses key topics like database design, creating tables in MS Access, writing queries, developing forms, and creating and printing reports. The presentation covers what MS Access is, its advantages and disadvantages, how to create tables and write queries, and how Access can be used to develop the front end and print reports from a database.
This document outlines information extraction tasks. It discusses information integration, generating extractors, and different types of extractors including unsupervised and supervised. It describes how God uses unsupervised and supervised extractors to integrate information from multiple sources with only a few clicks without programming ability. The document also discusses real-time and background phases of information integration tasks.
This document discusses troubleshooting complex layer 2 issues in networking. It introduces the topic and defines the two layers involved - the physical layer and data link layer. The physical layer is responsible for the actual transmission of data through network interfaces. It encodes and signals data, defines the network topology and devices. The data link layer contains frames with MAC addresses and packets, and checks frames for errors by comparing values in the frame and FCS.
FP7 OpenCube project presentation at NTTS 2015 conferenceEfthimios Tambouris
FP7 OpenCube project presentation at New Techniques and Technologies for Statistics (NTTS) conference. The conference took plance at Brussels between 10 and 12 March 2015.
The Very Model of a Modern MetamodelerEd Seidewitz
Philosophers have been talking about metaphysics since Aristotle. Logicians have used metalanguages for 80 years. And, in the last 50 years, computer scientists have produced metaobjects, metaclasses and metamodels. “Going meta” is now even part of the popular culture. What is this all about?
It is about the incredibly powerful human ability to reflect on what we are doing. Bringing this capability to our modeling languages, we can create languages able to express their own definitions. But, with real semantic formalization, we also open up the possibility of creating tools that can reflect on the very models they are being used to create. What might this mean for the next generation of modeling languages and tools?
This presentations goes meta, to reflect on reflection and try to figure it out.
Analytics of Performance and Data Quality for Mobile Edge Cloud ApplicationsHong-Linh Truong
The document discusses performance and data quality analytics for mobile edge cloud applications. It presents MECCA, a mobile edge cloud application for providing cornering recommendations to cars. MECCA has a complex architecture using microservices and third party services. Analyzing MECCA's performance and data quality across different edge and cloud deployments is challenging due to dependencies between application parameters, streaming processing, and third party services. Future work aims to develop toolsets and datasets to better evaluate performance and data quality metrics for mobile edge cloud applications.
This document outlines a project to develop a mathematical model for continuous simulation. The aims are to create a library that processes physical and virtual inputs to continuously update a bicycle simulation. Objectives include classes, commenting, manuals and testing. The methodology involves task decomposition, research, evaluation and problem solving. Sources of information include journals, books and websites on modelling. Resources like software, literature and design tools are listed. A work plan with timelines, decomposition and design documents is provided. Technical considerations of the bicycle simulation are identified. A concept diagram shows the 'Brain' handling input/output and a physics user interface.
Convert BIM/ IFC models into graph database (Neo4j) based on IFCWebServer.orgAli Ismail
Application of graph databases and graph theory
concepts for advanced analysing of BIM models based
on IFC standard
=============================================
Utilizing graph theory concepts to explore, manage
and analyse all information inside BIM models
AEC Hackathon -London (06-08/10/2017) Team Conenctivity- BIM and smart city c...Ali Ismail
BIM and Smart City Graph Connected Data
Big Challenges in AEC Industry:
Complex and discrete data models – huge files, heavy to work with or exchange, e.g. BIM models
Difficult interoperability among various proprietary software formats
Expensive interrogation tools with partial capability
Project information are not connected and synchronized over time
Difficulties to track changes and collect reliable quantities from all stakeholders
Compromised continuity between project stages due to change of consultants
Different types of repositories for different types of documents
Limited access to precedent solutions
Solution:
Standard formats based connected database with limitless scalability
Get all related models connected to each other in one centralized graph data base
Connect data on one project level or on higher level (connected smart city)
Implement a platform to target specific problems (web based micro service platform)
The document discusses the Durable Architectural Knowledge project which aims to develop sustainable methods and practices for preserving digital architectural data. The project is developing techniques for geometrically and semantically enriching 3D models through tasks like data synchronization, difference analysis, and semantic indexing. It is also working on approaches for the long-term preservation of architectural data to ensure its future availability and understandability. Prototypes have been created of the DURAARK workbench and its components for geometric enrichment, semantic enrichment, and preservation.
1) The document discusses how MATLAB can be used for big data analytics, machine learning, and deploying analytic applications.
2) It presents an agenda covering introduction to MATLAB for data analytics, big data, machine learning/deep learning, and deploying analytics.
3) MATLAB allows domain experts to perform tasks like data cleaning, exploration, machine learning using familiar MATLAB functions and interfaces while handling large datasets.
The document proposes two frameworks for developing mashups:
1. A framework architecture that supports dynamic data integration mashups through a script-based definition and multiple query strategies to access external data sources.
2. A presentation integration framework that facilitates creating composite applications from reusable components using a composition language (XPIL) and middleware for event automation and component invocation. It was implemented in ASP.NET with adapters for Flickr.NET and AJAX components.
The document proposes a bottom-up approach to defining services in decentralized environments. It involves stakeholders using blackboards - wiki-like artifacts - to externally represent their distinct semantics. Blackboards adopt a network structure where they can link to each other and evolve over time through practices like versioning. The goal is to empower stakeholders to collaboratively define services in a decentralized way while promoting heterogeneity, traceability, and emergent semantics.
The ENES Climate Analytics Service (ECAS) provides a server-side environment for data analysis of large climate datasets using the Ophidia analytics framework and Jupyter notebooks. Users can access ECAS through instances hosted by CMCC and DKRZ, developing and sharing analytics workflows. ECAS aims to enable data sharing and reuse for climate research while reducing data downloads through cloud-based analysis.
DSD-INT 2020 Computational Framework - Part of the BlueEarth-EngineDeltares
Presentation by Peter Gijsbers, Deltares, at the BlueEarth User Day: Explain the past, explore the future, during Delft Software Days - Edition 2020. Monday, 16 November 2020.
The EOSC Compute Platform with the EGI-ACE project EGI Federation
EGI-ACE’s main goal is to implement the compute platform of the European Open Science Cloud and contribute to the EOSC Data Commons by delivering integrated computing platforms, data spaces and tools as an integrated solution that is aligned with major European cloud federation projects and HPC initiatives.
This presentation introduces you to the architecture and composition of the EOSC Compute Platform, which delivers capabilities at the IaaS, PaaS and SaaS level.
A brief report on the work of the DCMI/IEEE Task Force on interoperability between the IEEE Learning Object Metadata standard and Dublin Core.
Presentation given to meeting of JISC CETIS Metadata & Digital Repositories Special Interest Group, held in Manchester on 16 April 2007
The document proposes a new paradigm called Spreadsheet Composition for collaborative data analysis and sharing. It involves linking Excel spreadsheets together to form distributed spreadsheets. This is enabled by a software platform called SpreadSheet Space, which provides services like publishing views of data and collecting data through forms. The platform uses a publish/subscribe model to keep the linked spreadsheets in sync. This allows for real-time collaborative analysis and easy access to dynamic data sources like open data and information systems.
Scott creates and automates reporting processes by linking data from various sources into a single reporting system. He writes complex queries and builds user-friendly Excel and Access reports to analyze data and find answers to difficult business questions. As an example, Scott developed a Material Planning database using Microsoft Access and Excel with VBA that linked planning data from multiple systems into a coherent reporting and decision support tool. The database provided graphical MRP reporting and analysis through various reports, forms, and an Excel interface for scenario planning. Scott is skilled at data management, report development, and building decision support systems to help manage business processes.
Learn how to make data accessible to your end users and stakeholders. See how to build FME workflows for integrating disparate data sources and sharing it via reports, interactive visualizations, web portals, mobile devices, and more.
Conference: 23rd ICE/IEEE ITMC Conference
(ICE2017).
Madeira, Portugal – June 27-30, 2017
Title of the paper: Configuring and Visualizing The
Data Resources in a Cloud-based Data Collection
Framework
Authors: Wael M. Mohammed, David Aleixo, Borja
Ramis Ferrer, Carlos Agostinho, Jose L. Martinez
Lastra
if you would like to receive a reprint of the
original paper, please contact us.
This document outlines DBpedia's strategy to become a global open knowledge graph by facilitating collaboration on data. It discusses establishing governance and curation processes to improve data quality and enable organizations to incubate their knowledge graphs. The goals are to have millions of users and contributors collaborating on data through services like GitHub for data. Technologies like identifiers, schema mapping, and test-driven development help integrate data. The vision is for DBpedia to connect many decentralized data sources so data becomes freely available and easier to work with.
20141030 LinDA Workshop echallenges2014 - LinDA project overviewLinDa_FP7
The LinDA project aims to provide tools for small and medium enterprises to access and analyze public sector information. The project will develop a transformation engine to convert data into semantic formats, a repository for linked data vocabularies, a linked data API, visualization tools, and analytics applications. These tools will help SMEs integrate public and private data sources to discover new patterns and develop innovative business models. The goal is to motivate more publication and use of open government data using semantic web standards.
This document discusses troubleshooting complex layer 2 issues in networking. It introduces the topic and defines the two layers involved - the physical layer and data link layer. The physical layer is responsible for the actual transmission of data through network interfaces. It encodes and signals data, defines the network topology and devices. The data link layer contains frames with MAC addresses and packets, and checks frames for errors by comparing values in the frame and FCS.
FP7 OpenCube project presentation at NTTS 2015 conferenceEfthimios Tambouris
FP7 OpenCube project presentation at New Techniques and Technologies for Statistics (NTTS) conference. The conference took plance at Brussels between 10 and 12 March 2015.
The Very Model of a Modern MetamodelerEd Seidewitz
Philosophers have been talking about metaphysics since Aristotle. Logicians have used metalanguages for 80 years. And, in the last 50 years, computer scientists have produced metaobjects, metaclasses and metamodels. “Going meta” is now even part of the popular culture. What is this all about?
It is about the incredibly powerful human ability to reflect on what we are doing. Bringing this capability to our modeling languages, we can create languages able to express their own definitions. But, with real semantic formalization, we also open up the possibility of creating tools that can reflect on the very models they are being used to create. What might this mean for the next generation of modeling languages and tools?
This presentations goes meta, to reflect on reflection and try to figure it out.
Analytics of Performance and Data Quality for Mobile Edge Cloud ApplicationsHong-Linh Truong
The document discusses performance and data quality analytics for mobile edge cloud applications. It presents MECCA, a mobile edge cloud application for providing cornering recommendations to cars. MECCA has a complex architecture using microservices and third party services. Analyzing MECCA's performance and data quality across different edge and cloud deployments is challenging due to dependencies between application parameters, streaming processing, and third party services. Future work aims to develop toolsets and datasets to better evaluate performance and data quality metrics for mobile edge cloud applications.
This document outlines a project to develop a mathematical model for continuous simulation. The aims are to create a library that processes physical and virtual inputs to continuously update a bicycle simulation. Objectives include classes, commenting, manuals and testing. The methodology involves task decomposition, research, evaluation and problem solving. Sources of information include journals, books and websites on modelling. Resources like software, literature and design tools are listed. A work plan with timelines, decomposition and design documents is provided. Technical considerations of the bicycle simulation are identified. A concept diagram shows the 'Brain' handling input/output and a physics user interface.
Convert BIM/ IFC models into graph database (Neo4j) based on IFCWebServer.orgAli Ismail
Application of graph databases and graph theory
concepts for advanced analysing of BIM models based
on IFC standard
=============================================
Utilizing graph theory concepts to explore, manage
and analyse all information inside BIM models
AEC Hackathon -London (06-08/10/2017) Team Conenctivity- BIM and smart city c...Ali Ismail
BIM and Smart City Graph Connected Data
Big Challenges in AEC Industry:
Complex and discrete data models – huge files, heavy to work with or exchange, e.g. BIM models
Difficult interoperability among various proprietary software formats
Expensive interrogation tools with partial capability
Project information are not connected and synchronized over time
Difficulties to track changes and collect reliable quantities from all stakeholders
Compromised continuity between project stages due to change of consultants
Different types of repositories for different types of documents
Limited access to precedent solutions
Solution:
Standard formats based connected database with limitless scalability
Get all related models connected to each other in one centralized graph data base
Connect data on one project level or on higher level (connected smart city)
Implement a platform to target specific problems (web based micro service platform)
The document discusses the Durable Architectural Knowledge project which aims to develop sustainable methods and practices for preserving digital architectural data. The project is developing techniques for geometrically and semantically enriching 3D models through tasks like data synchronization, difference analysis, and semantic indexing. It is also working on approaches for the long-term preservation of architectural data to ensure its future availability and understandability. Prototypes have been created of the DURAARK workbench and its components for geometric enrichment, semantic enrichment, and preservation.
1) The document discusses how MATLAB can be used for big data analytics, machine learning, and deploying analytic applications.
2) It presents an agenda covering introduction to MATLAB for data analytics, big data, machine learning/deep learning, and deploying analytics.
3) MATLAB allows domain experts to perform tasks like data cleaning, exploration, machine learning using familiar MATLAB functions and interfaces while handling large datasets.
The document proposes two frameworks for developing mashups:
1. A framework architecture that supports dynamic data integration mashups through a script-based definition and multiple query strategies to access external data sources.
2. A presentation integration framework that facilitates creating composite applications from reusable components using a composition language (XPIL) and middleware for event automation and component invocation. It was implemented in ASP.NET with adapters for Flickr.NET and AJAX components.
The document proposes a bottom-up approach to defining services in decentralized environments. It involves stakeholders using blackboards - wiki-like artifacts - to externally represent their distinct semantics. Blackboards adopt a network structure where they can link to each other and evolve over time through practices like versioning. The goal is to empower stakeholders to collaboratively define services in a decentralized way while promoting heterogeneity, traceability, and emergent semantics.
The ENES Climate Analytics Service (ECAS) provides a server-side environment for data analysis of large climate datasets using the Ophidia analytics framework and Jupyter notebooks. Users can access ECAS through instances hosted by CMCC and DKRZ, developing and sharing analytics workflows. ECAS aims to enable data sharing and reuse for climate research while reducing data downloads through cloud-based analysis.
DSD-INT 2020 Computational Framework - Part of the BlueEarth-EngineDeltares
Presentation by Peter Gijsbers, Deltares, at the BlueEarth User Day: Explain the past, explore the future, during Delft Software Days - Edition 2020. Monday, 16 November 2020.
The EOSC Compute Platform with the EGI-ACE project EGI Federation
EGI-ACE’s main goal is to implement the compute platform of the European Open Science Cloud and contribute to the EOSC Data Commons by delivering integrated computing platforms, data spaces and tools as an integrated solution that is aligned with major European cloud federation projects and HPC initiatives.
This presentation introduces you to the architecture and composition of the EOSC Compute Platform, which delivers capabilities at the IaaS, PaaS and SaaS level.
A brief report on the work of the DCMI/IEEE Task Force on interoperability between the IEEE Learning Object Metadata standard and Dublin Core.
Presentation given to meeting of JISC CETIS Metadata & Digital Repositories Special Interest Group, held in Manchester on 16 April 2007
The document proposes a new paradigm called Spreadsheet Composition for collaborative data analysis and sharing. It involves linking Excel spreadsheets together to form distributed spreadsheets. This is enabled by a software platform called SpreadSheet Space, which provides services like publishing views of data and collecting data through forms. The platform uses a publish/subscribe model to keep the linked spreadsheets in sync. This allows for real-time collaborative analysis and easy access to dynamic data sources like open data and information systems.
Scott creates and automates reporting processes by linking data from various sources into a single reporting system. He writes complex queries and builds user-friendly Excel and Access reports to analyze data and find answers to difficult business questions. As an example, Scott developed a Material Planning database using Microsoft Access and Excel with VBA that linked planning data from multiple systems into a coherent reporting and decision support tool. The database provided graphical MRP reporting and analysis through various reports, forms, and an Excel interface for scenario planning. Scott is skilled at data management, report development, and building decision support systems to help manage business processes.
Learn how to make data accessible to your end users and stakeholders. See how to build FME workflows for integrating disparate data sources and sharing it via reports, interactive visualizations, web portals, mobile devices, and more.
Conference: 23rd ICE/IEEE ITMC Conference
(ICE2017).
Madeira, Portugal – June 27-30, 2017
Title of the paper: Configuring and Visualizing The
Data Resources in a Cloud-based Data Collection
Framework
Authors: Wael M. Mohammed, David Aleixo, Borja
Ramis Ferrer, Carlos Agostinho, Jose L. Martinez
Lastra
if you would like to receive a reprint of the
original paper, please contact us.
This document outlines DBpedia's strategy to become a global open knowledge graph by facilitating collaboration on data. It discusses establishing governance and curation processes to improve data quality and enable organizations to incubate their knowledge graphs. The goals are to have millions of users and contributors collaborating on data through services like GitHub for data. Technologies like identifiers, schema mapping, and test-driven development help integrate data. The vision is for DBpedia to connect many decentralized data sources so data becomes freely available and easier to work with.
20141030 LinDA Workshop echallenges2014 - LinDA project overviewLinDa_FP7
The LinDA project aims to provide tools for small and medium enterprises to access and analyze public sector information. The project will develop a transformation engine to convert data into semantic formats, a repository for linked data vocabularies, a linked data API, visualization tools, and analytics applications. These tools will help SMEs integrate public and private data sources to discover new patterns and develop innovative business models. The goal is to motivate more publication and use of open government data using semantic web standards.
(http://lod2.eu/BlogPost/webinar-series) In this Webinar Michael Martin presents CubeViz - a facetted browser for statistical data utilizing the RDF Data Cube vocabulary which is the state-of-the-art in representing statistical data in RDF. This vocabulary is compatible with SDMX and increasingly being adopted. Based on the vocabulary and the encoded Data Cube, CubeViz is generating a facetted browsing widget that can be used to filter interactively observations to be visualized in charts. Based on the selected structure, CubeViz offer beneficiary chart types and options which can be selected by users.
If you are interested in Linked (Open) Data principles and mechanisms, LOD tools & services and concrete use cases that can be realised using LOD then join us in the free LOD2 webinar series!
FIWARE Wednesday Webinars - Cities as Enablers of the Data Economy: Smart Dat...FIWARE
Cities as Enablers of the Data Economy: Smart Data Models for Cities - 21 October 2020
Corresponding webinar recording: https://youtu.be/b0EWq5E5jAc
Speaker: Alberto Abella (Data Modeling Expert and Technical Evangelist, FIWARE Foundation)
Chapter: Smart Cities
Difficulty: 2
Audience: Technical Domain Specific
This document discusses interaction with linked data, focusing on visualization techniques. It begins with an overview of the linked data visualization process, including extracting data analytically, applying visualization transformations, and generating views. It then covers challenges like scalability, handling heterogeneous data, and enabling user interaction. Various visualization techniques are classified and examples are provided, including bar charts, graphs, timelines, and maps. Finally, linked data visualization tools and examples using tools like Sigma, Sindice, and Information Workbench are described.
Creating and Utilizing Linked Open Statistical Data for the Development of Ad...Evangelos Kalampokis
The document discusses the OpenCube approach for working with linked data cubes. OpenCube develops components to support the full lifecycle of linked statistical data, from publishing raw data cubes to consuming them through analytics, visualizations, and other applications. It presents several components that have been implemented, including tools for publishing statistical data in various formats, browsing and visualizing data cubes, and integrating with R for advanced analytics. Initial evaluations of the components have provided insights around publishing and working with large linked statistical datasets.
Data Harvesting, Curation and Fusion Model to Support Public Service Recommen...Citadelh2020
CITADEL is a H2020 European project that is creating an ecosystem of best practices, tools, and recommendations to transform Public Administrations (PAs) via an inclusive approach in order to provide stakeholders with more efficient, inclusive and citizen-centric services. The CITADEL ecosystem will allow PAs to use what they already know plus new data to implement what really matters to citizens in order to shape and co-create more efficient and inclusive public services. CITADEL innovates by using ICTs to find out why citizens stop using public services, and use this information to re-adjust provision to bring them back in. Also, it identifies why citizens are not using a given public service (due to affordability, accessibility, lack of knowledge, embarrassment, lack of interest, etc.) and, where appropriate, use this information to make public services more attractive, so they start using the services.
The DataTank, a tool designed and developed by IMEC’s IDLab, will be extended to provide the Data Harvesting/Curation/Fusion (DHCF) component of the platform. The DataTank provides an open source, open data platform which not only allows publishing datasets according to standardised guidelines and taxonomies (DCAT-AP), but also transforms the data into a variety of reusable formats. The extension will include an intelligent way of harvesting and fusion of different data sources using semantics and Linked Data mapping technologies developed by IDLab. In the context of CITADEL the new HCF component will enable the visualization and analysis of trends for the usage of public services in European cities, playing a key role in generating personalized recommendations to the citizens as well as to PAs in terms of suggesting improvements to the current suite of public services.
https://twitter.com/Citadelh2020
https://twitter.com/gayane_sedraky
https://twitter.com/imec_int
https://twitter.com/IDLabResearch
Data Harvesting, Curation and Fusion Model to Support Public Service Recommen...Gayane Sedrakyan
CITADEL is a H2020 European project that is creating an ecosystem of best practices, tools, and recommendations to transform Public Administrations (PAs) via an inclusive approach in order to provide stakeholders with more efficient, inclusive and citizen-centric services. The CITADEL ecosystem will allow PAs to use what they already know plus new data to implement what really matters to citizens in order to shape and co-create more efficient and inclusive public services. CITADEL innovates by using ICTs to find out why citizens stop using public services, and use this information to re-adjust provision to bring them back in. Also, it identifies why citizens are not using a given public service (due to affordability, accessibility, lack of knowledge, embarrassment, lack of interest, etc.) and, where appropriate, use this information to make public services more attractive, so they start using the services.
The DataTank, a tool designed and developed by IMEC’s IDLab, will be extended to provide the Data Harvesting/Curation/Fusion (DHCF) component of the platform. The DataTank provides an open source, open data platform which not only allows publishing datasets according to standardised guidelines and taxonomies (DCAT-AP), but also transforms the data into a variety of reusable formats. The extension will include an intelligent way of harvesting and fusion of different data sources using semantics and Linked Data mapping technologies developed by IDLab. In the context of CITADEL the new HCF component will enable the visualization and analysis of trends for the usage of public services in European cities, playing a key role in generating personalized recommendations to the citizens as well as to PAs in terms of suggesting improvements to the current suite of public services.
The document summarizes a presentation on data visualization with D3.js given by Brian Greig to the Charlotte Front-End Developers group. The presentation covered data visualization concepts, accessing data via APIs, basic D3 components like binding data, building visualizations, and making visualizations interactive. It provided examples of good data visualizations and discussed key terms. It also outlined the steps to structure a D3 application, including initializing scales and domains, entering and updating data, and cleaning up.
The document summarizes a presentation on data visualization with D3.js given by Brian Greig to the Charlotte Front-End Developers group. The presentation introduced data visualization concepts and the D3 library, covered accessing data via APIs, building basic visualization components like scales and axes, binding data, and making visualizations interactive. It provided examples of effective data visualizations and discussed best practices for structuring visualizations and giving proper context to data.
This presentation gives details on technologies and approaches towards exploiting Linked Data by building LD applications. In particular, it gives an overview of popular existing applications and introduces the main technologies that support implementation and development. Furthermore, it illustrates how data exposed through common Web APIs can be integrated with Linked Data in order to create mashups.
IRJET- Recommendation System based on Graph Database TechniquesIRJET Journal
This document proposes a recommendation system based on graph database techniques. It uses Neo4j to develop a recommendation approach using content-based filtering, collaborative filtering, and hybrid filtering. The system recommends restaurants and meals to customers based on reviews and friend recommendations. It stores data about restaurants, meals, customers and their reviews in a graph database to allow for complex queries and recommendations. The implementation and results of the proposed recommendation system are also discussed.
Logical Data Fabric and Data Mesh – Driving Business OutcomesDenodo
Watch full webinar here: https://buff.ly/3qgGjtA
Presented at TDWI VIRTUAL SUMMIT - Modernizing Data Management
While the technological advances of the past decade have addressed the scale of data processing and data storage, they have failed to address scale in other dimensions: proliferation of sources of data, diversity of data types and user persona, and speed of response to change. The essence of the data mesh and data fabric approaches is that it puts the customer first and focuses on outcomes instead of outputs.
In this session, Saptarshi Sengupta, Senior Director of Product Marketing at Denodo, will address key considerations and provide his insights on why some companies are succeeding with these approaches while others are not.
Watch On-Demand and Learn:
- Why a logical approach is necessary and how it aligns with data fabric and data mesh
- How some of the large enterprises are using logical data fabric and data mesh for their data and analytics needs
- Tips to create a good data management modernization roadmap for your organization
CRISP is an inter-university research center in Italy that focuses on public services. It uses R and open source software throughout its statistical information system (SIS) for business intelligence. R is integrated into the data transformation, preparation and presentation layers of the SIS. It runs statistical models and generates visualizations during ETL processing and for dashboards. This allows CRISP to perform advanced analysis not supported by typical tools and present results to users.
Mobile Offline First for inclusive data that spans the data divideRob Worthington
This presentation - given at the 2016 GovTech conference in South Africa - provides an overview of a new mobile offline first architecture for government applications
This document discusses data modeling and different data models. It covers the evolution of data models from hierarchical to network to relational models. It also discusses object-oriented and XML data models. Key aspects of data modeling include entities, attributes, relationships, and constraints. Different abstraction levels for data modeling include external, conceptual, and internal views.
PlanetData project was presented by Elena Simperl and Barry Norton from Karlsruhe Institute of Technology at the 1st International Symposium on Data-driven Process Discovery and Analysis on June 30, 2011 in Campione d’Italia, Italy
The document summarizes the PlanetData project, which aims to establish an interdisciplinary community for managing large-scale structured data on the web. Its objectives include addressing challenges through integrated research, providing data and technology through a lab, and having impact through training, standards, and networking. The work plan highlights include publishing and managing streaming data, assessing linked data quality, and developing applications using linked services and processes.
Agile Data Warehouse Modeling: Introduction to Data Vault Data ModelingKent Graziano
The document introduces Data Vault modeling as an agile approach to data warehousing. It discusses how Data Vault addresses some limitations of traditional dimensional modeling by allowing for more flexible, adaptable designs. The Data Vault model consists of three simple structures - hubs, links, and satellites. Hubs contain unique business keys, links represent relationships between keys, and satellites hold descriptive attributes. This structure supports incremental development and rapid changes to meet evolving business needs in an agile manner.
Removing barriers to transparency: a case study on the use of semantic techno...giuseppe_futia
This document discusses using semantic technologies to improve consistency in Italian public procurement data and remove barriers to transparency. It identifies several types of inconsistencies, such as business entities with multiple names and contracts identified by the same code number. The authors developed an ontology and linked the data to address these issues. Their approach generated a unique identifier for each entity and contract to improve consistency. The results demonstrated their method can help achieve the goal of transparent and consistent open government data.
From unstructured data to structured journalismgiuseppe_futia
This document discusses moving from unstructured to structured data in journalism. It provides examples of tools and projects that use machine learning and data processing to help journalists report the news more efficiently. These include tools from the New York Times, BBC, and Washington Post that help with tasks like entity extraction and knowledge mapping. One example discussed in more detail is the processing of the Panama Papers leak, which involved sorting, indexing, and analyzing over 11 million documents to build a structured database for investigative reporting.
Exploiting Linked Open Data and Natural Language Processing for Classificati...giuseppe_futia
This document discusses using the TellMeFirst topic extraction tool to automatically categorize political speeches from the White House website. TellMeFirst leverages the DBpedia knowledge base and natural language processing techniques to identify topics in text. It was able to accurately categorize US president profiles and extract topics from White House videos, providing insight into what First Lady Michelle Obama discusses in her speeches. Integrating this tool could help citizens more easily understand the content of political speeches.
Visualizing Internet-Measurements Data for Research Purposes: the NeuViz Data...giuseppe_futia
NeuViz, a data processing and visualization architecture for network measurement experiments.
Presented at "50° Congresso Nazionale AICA" - Fisciano (SA), 19th September 2013
ViewShift: Hassle-free Dynamic Policy Enforcement for Every Data LakeWalaa Eldin Moustafa
Dynamic policy enforcement is becoming an increasingly important topic in today’s world where data privacy and compliance is a top priority for companies, individuals, and regulators alike. In these slides, we discuss how LinkedIn implements a powerful dynamic policy enforcement engine, called ViewShift, and integrates it within its data lake. We show the query engine architecture and how catalog implementations can automatically route table resolutions to compliance-enforcing SQL views. Such views have a set of very interesting properties: (1) They are auto-generated from declarative data annotations. (2) They respect user-level consent and preferences (3) They are context-aware, encoding a different set of transformations for different use cases (4) They are portable; while the SQL logic is only implemented in one SQL dialect, it is accessible in all engines.
#SQL #Views #Privacy #Compliance #DataLake
Analysis insight about a Flyball dog competition team's performanceroli9797
Insight of my analysis about a Flyball dog competition team's last year performance. Find more: https://github.com/rolandnagy-ds/flyball_race_analysis/tree/main
4th Modern Marketing Reckoner by MMA Global India & Group M: 60+ experts on W...Social Samosa
The Modern Marketing Reckoner (MMR) is a comprehensive resource packed with POVs from 60+ industry leaders on how AI is transforming the 4 key pillars of marketing – product, place, price and promotions.
Predictably Improve Your B2B Tech Company's Performance by Leveraging DataKiwi Creative
Harness the power of AI-backed reports, benchmarking and data analysis to predict trends and detect anomalies in your marketing efforts.
Peter Caputa, CEO at Databox, reveals how you can discover the strategies and tools to increase your growth rate (and margins!).
From metrics to track to data habits to pick up, enhance your reporting for powerful insights to improve your B2B tech company's marketing.
- - -
This is the webinar recording from the June 2024 HubSpot User Group (HUG) for B2B Technology USA.
Watch the video recording at https://youtu.be/5vjwGfPN9lw
Sign up for future HUG events at https://events.hubspot.com/b2b-technology-usa/
STATATHON: Unleashing the Power of Statistics in a 48-Hour Knowledge Extravag...sameer shah
"Join us for STATATHON, a dynamic 2-day event dedicated to exploring statistical knowledge and its real-world applications. From theory to practice, participants engage in intensive learning sessions, workshops, and challenges, fostering a deeper understanding of statistical methodologies and their significance in various fields."
End-to-end pipeline agility - Berlin Buzzwords 2024Lars Albertsson
We describe how we achieve high change agility in data engineering by eliminating the fear of breaking downstream data pipelines through end-to-end pipeline testing, and by using schema metaprogramming to safely eliminate boilerplate involved in changes that affect whole pipelines.
A quick poll on agility in changing pipelines from end to end indicated a huge span in capabilities. For the question "How long time does it take for all downstream pipelines to be adapted to an upstream change," the median response was 6 months, but some respondents could do it in less than a day. When quantitative data engineering differences between the best and worst are measured, the span is often 100x-1000x, sometimes even more.
A long time ago, we suffered at Spotify from fear of changing pipelines due to not knowing what the impact might be downstream. We made plans for a technical solution to test pipelines end-to-end to mitigate that fear, but the effort failed for cultural reasons. We eventually solved this challenge, but in a different context. In this presentation we will describe how we test full pipelines effectively by manipulating workflow orchestration, which enables us to make changes in pipelines without fear of breaking downstream.
Making schema changes that affect many jobs also involves a lot of toil and boilerplate. Using schema-on-read mitigates some of it, but has drawbacks since it makes it more difficult to detect errors early. We will describe how we have rejected this tradeoff by applying schema metaprogramming, eliminating boilerplate but keeping the protection of static typing, thereby further improving agility to quickly modify data pipelines without fear.
The Building Blocks of QuestDB, a Time Series Databasejavier ramirez
Talk Delivered at Valencia Codes Meetup 2024-06.
Traditionally, databases have treated timestamps just as another data type. However, when performing real-time analytics, timestamps should be first class citizens and we need rich time semantics to get the most out of our data. We also need to deal with ever growing datasets while keeping performant, which is as fun as it sounds.
It is no wonder time-series databases are now more popular than ever before. Join me in this session to learn about the internal architecture and building blocks of QuestDB, an open source time-series database designed for speed. We will also review a history of some of the changes we have gone over the past two years to deal with late and unordered data, non-blocking writes, read-replicas, or faster batch ingestion.
Codeless Generative AI Pipelines
(GenAI with Milvus)
https://ml.dssconf.pl/user.html#!/lecture/DSSML24-041a/rate
Discover the potential of real-time streaming in the context of GenAI as we delve into the intricacies of Apache NiFi and its capabilities. Learn how this tool can significantly simplify the data engineering workflow for GenAI applications, allowing you to focus on the creative aspects rather than the technical complexities. I will guide you through practical examples and use cases, showing the impact of automation on prompt building. From data ingestion to transformation and delivery, witness how Apache NiFi streamlines the entire pipeline, ensuring a smooth and hassle-free experience.
Timothy Spann
https://www.youtube.com/@FLaNK-Stack
https://medium.com/@tspann
https://www.datainmotion.dev/
milvus, unstructured data, vector database, zilliz, cloud, vectors, python, deep learning, generative ai, genai, nifi, kafka, flink, streaming, iot, edge
06-04-2024 - NYC Tech Week - Discussion on Vector Databases, Unstructured Data and AI
Discussion on Vector Databases, Unstructured Data and AI
https://www.meetup.com/unstructured-data-meetup-new-york/
This meetup is for people working in unstructured data. Speakers will come present about related topics such as vector databases, LLMs, and managing data at scale. The intended audience of this group includes roles like machine learning engineers, data scientists, data engineers, software engineers, and PMs.This meetup was formerly Milvus Meetup, and is sponsored by Zilliz maintainers of Milvus.
Global Situational Awareness of A.I. and where its headedvikram sood
You can see the future first in San Francisco.
Over the past year, the talk of the town has shifted from $10 billion compute clusters to $100 billion clusters to trillion-dollar clusters. Every six months another zero is added to the boardroom plans. Behind the scenes, there’s a fierce scramble to secure every power contract still available for the rest of the decade, every voltage transformer that can possibly be procured. American big business is gearing up to pour trillions of dollars into a long-unseen mobilization of American industrial might. By the end of the decade, American electricity production will have grown tens of percent; from the shale fields of Pennsylvania to the solar farms of Nevada, hundreds of millions of GPUs will hum.
The AGI race has begun. We are building machines that can think and reason. By 2025/26, these machines will outpace college graduates. By the end of the decade, they will be smarter than you or I; we will have superintelligence, in the true sense of the word. Along the way, national security forces not seen in half a century will be un-leashed, and before long, The Project will be on. If we’re lucky, we’ll be in an all-out race with the CCP; if we’re unlucky, an all-out war.
Everyone is now talking about AI, but few have the faintest glimmer of what is about to hit them. Nvidia analysts still think 2024 might be close to the peak. Mainstream pundits are stuck on the wilful blindness of “it’s just predicting the next word”. They see only hype and business-as-usual; at most they entertain another internet-scale technological change.
Before long, the world will wake up. But right now, there are perhaps a few hundred people, most of them in San Francisco and the AI labs, that have situational awareness. Through whatever peculiar forces of fate, I have found myself amongst them. A few years ago, these people were derided as crazy—but they trusted the trendlines, which allowed them to correctly predict the AI advances of the past few years. Whether these people are also right about the next few years remains to be seen. But these are very smart people—the smartest people I have ever met—and they are the ones building this technology. Perhaps they will be an odd footnote in history, or perhaps they will go down in history like Szilard and Oppenheimer and Teller. If they are seeing the future even close to correctly, we are in for a wild ride.
Let me tell you what we see.
Population Growth in Bataan: The effects of population growth around rural pl...
Visualization of Linked Data
1. Visualization
of Linked Data
Giuseppe Futia
Nexa Center for Internet and Society, Politecnico di Torino
(DAUIN), Italy
International Summer School On Open and
Collaborative Governance – July 2015
2. Agenda
15/07/15 Visualization of Linked Data 2
• Linked Data (LD) principles
• LD User Interface (UI) creation process
• Uduvudu: a graph-aware and adaptive UI engine
• Different approaches to visualization (with examples)
3. Linked Data principles
1. Use URIs as names for things
2. Use HTTP URIs so that people can look up those
names
3. When someone looks up a URI, provide useful
information, using the standards (RDF, SPARQL)
4. Include links to other URIs, so that they can
discover more things
15/07/15 Visualization of Linked Data 3
5. Linked Data Cloud Diagram
1014 datasets
Government: 183
(18.05%)
15/07/15 Visualization of Linked Data 5
6. Complementary Approaches
• Building interfaces to easily navigate or
summarize large quantities of data
• Selecting and individually rendering key
values from the data
15/07/15 Visualization of Linked Data 6
7. Complementary Approaches
• Building interfaces to easily navigate or
summarize large quantities of data
• Selecting and individually rendering key
values from the data
15/07/15 Visualization of Linked Data 7
8. Why rendering key values? (IMHO)
•We have to exploit the intelligence of the graph
in the backend of our applications (e.g., in a
search engine)
•Any kind of visualization should support the
understanding and the dimension of data
(not the dimension of the graph)
15/07/15 Visualization of Linked Data 8
9. London 2012 Olympics
from the BBC
«The interrelation
between the concepts
drives the navigation of the
website»
10. LD Visualization is a
complex task
The UI creation process is
split in multiple roles
15/07/15 Visualization of Linked Data 10
11. Advantages (i)
• Clear separation of roles: better repartition of
work and increased autonomy for the experts
• Iterative development process: new elements
can be added to each task without blocking
the other tasks
15/07/15 Visualization of Linke Data 11
12. Advantages (ii)
• Highly reusable outcome: structures and
templates can be reused and adapted later to
another context, data, or application
• Zero-input fallback: any valid Linked Data
provided can be rendered without any
additional processing
15/07/15 Visualization of Linke Data 12
13. Tree Vs Graph
«When you show a typical
developer RDF, where they
have previously been used to
simple JSON or XML structures,
they find the format confusing,
and hard to code with. This is
primarily because the data is a
graph, and graphs don’t fit well
with the tree structures of JSON
and XML»
- David Rogers, Senior Technical
Architect in BBC Future Media
15/07/15 Visualization of Linked Data 13
14. Uduvudu
• A flexible and open-source engine to visualize LD
developed in the context of Fusepool P3 project
• It is written in JavaScript and run in the browser
natively (https://github.com/uduvudu/uduvudu)
15/07/15 Visualization of Linked Data 14
15. Main components (i)
• Data Selector:
– It takes a superset of information that need to be
shown as input
– It trims data to a graph containing exactly the
data that needs to be rendered
– Tipically carried out by a LD specialist
15/07/15 Visualization of Linked Data 15
17. Main components (ii)
• Structure Matcher:
– It takes a graph and one or several corresponding
known structures (matchers) from a catalogue as
input and returns a tree structure as output
– This new tree structure has at least one point to a
template from the Renderer component
15/07/15 Visualization of Linked Data 17
21. Main components (iii)
• Adaptative Renderer:
– It takes as input the tree structure given by the
matcher and the provided template to finally
render the output
– The templates are written in HTML/JavaScript
and access the tree structure through escaped
variable definitions
15/07/15 Visualization of Linked Data 21
22. Provided template for
Adaptative Renderer
Data structured in a tree
object are accessed inside
the variable blocks <%- %>
15/07/15 Visualization of Linked Data 22
23. UI Creation Process with
Uduvudu
Overview of the
architecture with the
main components
15/07/15 Visualization of Linked Data 23