Ariadne harvester and validator - technical overview

•Download as KEY, PDF•

0 likes•787 views

The document describes a metadata validation framework that includes a validateMetadata() method that validates metadata using different validation schemes. It supports adding new validation schemas by configuring components and schemas. Validation components extend an interface and are configured by name and properties. The framework can be integrated as a Java library or REST service. It has been implemented and configured in the ARIADNE metadata harvesting system to validate harvested metadata against different standards.

API

Method name : validateMetadata()

Return type : void
Parameters : Name Datatype
metadata String
validationScheme String

Fault : validationException

empty attribute core schematron Legend
ﬁelds vocabulary bank IMS ILOX
rules uses
recommended extends
schematron rules
MACEv1.0 validationScheme

vcard validator validation component
ASPECTv1.0/ ASPECTv1.0/
recommended core - empty attribute ﬁelds rules
- empty ﬁelds

MELTv1.0/
minimal LOM loose lomloose.xsd

classiﬁcation
vocab service
melt.xsd

MACEv1.0/
vcard validator MACEv1.0/strict
loose
MELTv1.0/full

maceLoose maceStrict
mace.xsd
Schematron.xml Schematron.xml
conditional LRE taxon ﬁeld
ﬁelds check numerical - empty attribute ﬁelds - add. mandatory ﬁelds
- empty ﬁelds - conditional ﬁelds
- mandatory ﬁelds - mace namespace ﬁelds

Integration

• Java library (see integration with harvester)
• REST web-service
• web application

Maintenance

• Adding a new schema
• conﬁguration
• Adding a new custom component
• implementation
• conﬁguration
• Deploying

• New Validation Schema :
• add id
• properties : URI, components, (type)
• component
• properties
• Create the schemas
• structure
• vocabulary
• additional rules

• New custom component
• Extend ValidationComponent
void validate(String metadata) throws ValidationException;

void init(String name, Hashtable<String,String> table) throws
InitialisationException;

• config :

• componentType

• schemaLocation

Metadata
Provider Harvester
OAI-PMH

LOM
LOM Validation
XML

Mapping

Storage
SPI Target
File System
Lucene
...

Installation

• Java 5 or higher
• Tomcat 5 or higher
• build using apache ant
• drop in tomcat and done

Conﬁguration

• http://ariadne.cs.kuleuven.be/nateur-
harvester/
• Init
• OAI Targets
• Scheduling

Mapping

• Extend GenericMapper
• public abstract Element map(Record record);

• config :

• mapper.mapperClassName.<identifier> =
org.ariadne.mapping.BSOMapper

Validation

• Integrated ARIADNE validator
• Default scheme
• Target speciﬁc scheme
• Validation Reports

Maintenance
• Checking if • Installations :
harvesting still • GLOBE
running • MACE
• Follow up validation • MELT
reports • ASPECT
• Contact content • Organic Edunet
providers if target is • Natural Europe
down
• ICOPER
• Assist in solving • ARIADNE
validation errors • ...
• ...

Information

• http://ariadne.cs.kuleuven.be/lomi/
index.php/Harvesting_Metadata
• http://ariadne.cs.kuleuven.be/lomi/
index.php/Setting_Up_OAI-PMH

This document discusses Clojure's software transactional memory (STM) which allows coordinated changes to shared state without locking. STM transactions are atomic, consistent, and isolated like database transactions. An example shows threads A-E changing shared state atomically using STM functions like dosync, set-ref, and alter instead of atoms which are not transactional. STM uses MVCC and snapshot isolation under the hood to enable parallel changes without blocking.

Ruby Internals

Burke Libbey

Android session notes

Mostafa Sharkaoui

Android Crash Course Lunch and Learn

Paul Irwin

Android presentation

Pablo Alejandre del Rio

My android

Prince Bhanwra

Android is an open source operating system developed by Google and the Open Handset Alliance for use in mobile devices. It uses a modified Linux kernel and other open source software, allowing developers to write managed code using Java-like languages. Applications are compiled into Dalvik bytecode to run on Android's optimized virtual machine. This makes it easier for developers to build rich apps that can reuse components and share data across applications using intents and services.

Android presentation

jitendra k Singh

H.R. Institute Of Technology. The document discusses the Android platform and provides details in four main sections: 1. An introduction to Android, including what it is, its origins from Google and the Open Handset Alliance, and its open source licensing. 2. The Android platform, covering hardware requirements, the operating system which is based on Linux, network connectivity support, security features, and future possibilities for growth. 3. Software development for Android, including requirements like Java and the Android SDK, the Eclipse IDE, and supported programming languages like Java. 4. An overall evaluation of Android's advantages like customization but also limitations currently like some Bluetooth and Firefox support as well as conclusions

This document discusses strategies for aggregating educational content including key technologies like metadata standards, harvesting protocols, federated search, and publishing interfaces. It describes technologies like IEEE LOM for metadata, OAI-PMH for harvesting metadata, SQI for federated search across repositories, and SPI for publishing content. Examples are given of implementing these standards and protocols in systems like the ARIADNE harvester and registry.

Multi-touch introduction

Bram Vandeputte

Android intro 2010

Bram Vandeputte

Android is an open source software stack for mobile devices that includes an operating system, middleware and key applications. It allows developers to write managed code in Java and offers tools for application development including an emulator, SDK and Eclipse plugin. The Android framework supports components like activities, services and content providers that communicate via intents. It uses the Dalvik VM, supports common media formats and hardware like the camera and GPS.

Exploring the research world

Bram Vandeputte

In this short talk I will give an overview on ideas for using new technologies such as multi touch, tabletops and more to assist researchers in various tasks. We think of it as a research suite, where we go from very small devices and displays, such as a research pod and research pad, to extremely large displays, such as research on a tabletop, wall projections or even a projection dome. Specifically in this talk I will give an example of a researchpod app and a tabletop app. More! is a mobile application that has been developed for getting more information of a researcher during a presentation at a conference. This information includes all the papers, various contact information and even the slides of the presentation currently going on. Science table, a tabletop vizualisation, is a first attempt of providing easy access to publication data in a research field by showing connections between papers and its authors in various ways.

Research20

Bram Vandeputte

This document summarizes and discusses several research projects focused on openness, sharing, and collaboration in scientific research using web 2.0 technologies. It describes projects that aim to make scientific literature and data more openly accessible and connect researchers. This includes tools for finding additional information about researchers and conference presentations, visually browsing and clustering related research papers, and a proposed open collaborative platform for sharing research data, services, and applications. The document discusses challenges and opportunities for further developing these Research 2.0 ideas.

Metadata Harvesting And Validationv2

Bram Vandeputte

This document discusses metadata harvesting and validation. It describes a validation service that checks metadata against an application profile using XML schema and Schematron rules. The validation service is modular and reusable. Metadata can be validated during harvesting or mapping. An online validation service demo is also presented. The harvesting component harvests metadata from external repositories using OAI-PMH, validates the metadata, and stores valid metadata in a repository while logging invalid records. Validation reports are generated after harvesting.

Ariadne Overview

Bram Vandeputte

This document provides information about ARIADNE, a federation of online learning repositories. It discusses ARIADNE's centers located in various countries, its new members, and its relationship to other projects like GLOBE and MACE. Diagrams show how ARIADNE harvests and indexes content using open standards and interfaces with other systems through its federated search engine. The document outlines technologies used for communication, collaboration, content delivery, and more that enable online and blended learning applications.

Multi Touch Introduction

Bram Vandeputte

This document discusses large multi-touch displays and their technical details. It covers various touch input technologies like touchscreens, touchpads, and Wacom tablets. It also discusses multi-touch technologies like FTIR, DI, LLP, and DSI. Examples of multi-touch displays are given, including The Box, The Tabletop, and MTMini. Common multi-touch gestures like tap, drag, rotate, scale, and zoom are also listed. The document provides information on software protocols, trackers, and libraries for processing multi-touch input.

Multi Touch Hands On

Bram Vandeputte

Processing is an open-source programming language and integrated development environment (IDE) that is used for multimedia and graphical applications like animation, visual art, and interactive design. It supports multitouch input through the TUIO protocol, which allows for tracking objects on a multitouch surface. Examples are provided to demonstrate how to use TUIO for multitouch input in Processing code and in Java code that interfaces with Processing.

Oai Workshop Extended

Bram Vandeputte

Metadata Harvesting And Validation

Bram Vandeputte

The document discusses metadata harvesting and validation. It describes a validation service that checks metadata against an application profile using XML schema and Schematron rules. An online validation demo is also presented. The harvesting infrastructure uses the OAI-PMH protocol and includes components for harvesting from multiple targets, validating metadata, and generating validation reports. An ARIADNE Harvester manages the harvesting process and interfaces with repositories, validation services, and other systems.

IEEE LOM

Bram Vandeputte

The document provides an overview of the IEEE Learning Object Metadata standard (LOM) in three sections. It introduces LOM as a conceptual schema for describing digital and non-digital learning resources to enable interoperability across systems. The general overview section describes the standard's structure, data types, and vocabularies. The detailed structure section lists and explains the 9 categories and associated metadata elements that make up the LOM schema.

Android Presentation

Bram Vandeputte

Android is a software stack for mobile devices that includes an operating system, middleware and key applications. It allows developers to write managed code in Java for the Dalvik virtual machine. The Android SDK provides tools and APIs to develop applications that use features like its application framework, SQLite database, media support and hardware integration. Developers can create Android applications by defining activities, services and content providers and connecting them with intents in the AndroidManifest file.

Ariadne Harvesting

Bram Vandeputte

This document discusses metadata harvesting in repository networks. It provides an overview of the Open Archives Initiative Protocol for Metadata Harvesting (OAI-PMH) and the ARIADNE validation service. It then describes the ARIADNE harvesting infrastructure and projects that use it like MACE, MELT, and GLOBE. These harvest metadata from multiple repositories and enrich it. The document concludes with information on implementing an OAI-PMH target to expose a repository's metadata.

Introducing Milvus Lite: Easy-to-Install, Easy-to-Use vector database for you...

Zilliz

Data structures and Algorithms in Python.pdf

TIPNGVN2

Essentials of Automations: The Art of Triggers and Actions in FME

Safe Software

In this second installment of our Essentials of Automations webinar series, we’ll explore the landscape of triggers and actions, guiding you through the nuances of authoring and adapting workspaces for seamless automations. Gain an understanding of the full spectrum of triggers and actions available in FME, empowering you to enhance your workspaces for efficient automation. We’ll kick things off by showcasing the most commonly used event-based triggers, introducing you to various automation workflows like manual triggers, schedules, directory watchers, and more. Plus, see how these elements play out in real scenarios. Whether you’re tweaking your current setup or building from the ground up, this session will arm you with the tools and insights needed to transform your FME usage into a powerhouse of productivity. Join us to discover effective strategies that simplify complex processes, enhancing your productivity and transforming your data management practices with FME. Let’s turn complexity into clarity and make your workspaces work wonders!

UiPath Test Automation using UiPath Test Suite series, part 6

DianaGray10

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

“I’m still / I’m still / Chaining from the Block”

Claudio Di Ciccio

How to Get CNIC Information System with Paksim Ga.pptx

danishmna97

Let's Integrate MuleSoft RPA, COMPOSER, APM with AWS IDP along with Slack

shyamraj55

Recently uploaded

Introducing Milvus Lite: Easy-to-Install, Easy-to-Use vector database for you...

Zilliz

Data structures and Algorithms in Python.pdf

TIPNGVN2

Essentials of Automations: The Art of Triggers and Actions in FME

Safe Software

UiPath Test Automation using UiPath Test Suite series, part 6

DianaGray10

“I’m still / I’m still / Chaining from the Block”

Claudio Di Ciccio

How to Get CNIC Information System with Paksim Ga.pptx

danishmna97

Let's Integrate MuleSoft RPA, COMPOSER, APM with AWS IDP along with Slack

shyamraj55

A tale of scale & speed: How the US Navy is enabling software delivery from l...

sonjaschweigert1

Rapid and secure feature delivery is a goal across every application team and every branch of the DoD. The Navy’s DevSecOps platform, Party Barge, has achieved: - Reduction in onboarding time from 5 weeks to 1 day - Improved developer experience and productivity through actionable findings and reduction of false positives - Maintenance of superior security standards and inherent policy enforcement with Authorization to Operate (ATO) Development teams can ship efficiently and ensure applications are cyber ready for Navy Authorizing Officials (AOs). In this webinar, Sigma Defense and Anchore will give attendees a look behind the scenes and demo secure pipeline automation and security artifacts that speed up application ATO and time to production. We will cover: - How to remove silos in DevSecOps - How to build efficient development pipeline roles and component templates - How to deliver security artifacts that matter for ATO’s (SBOMs, vulnerability reports, and policy evidence) - How to streamline operations with automated policy checks on container images

National Security Agency - NSA mobile device best practices

Quotidiano Piemontese

Microsoft - Power Platform_G.Aspiotis.pdf

Uni Systems S.M.S.A.

GraphSummit Singapore | The Future of Agility: Supercharging Digital Transfor...

Neo4j

Leonard Jayamohan, Partner & Generative AI Lead, Deloitte This keynote will reveal how Deloitte leverages Neo4j’s graph power for groundbreaking digital twin solutions, achieving a staggering 100x performance boost. Discover the essential role knowledge graphs play in successful generative AI implementations. Plus, get an exclusive look at an innovative Neo4j + Generative AI solution Deloitte is developing in-house.

Full-RAG: A modern architecture for hyper-personalization

Zilliz

Mike Del Balso, CEO & Co-Founder at Tecton, presents "Full RAG," a novel approach to AI recommendation systems, aiming to push beyond the limitations of traditional models through a deep integration of contextual insights and real-time data, leveraging the Retrieval-Augmented Generation architecture. This talk will outline Full RAG's potential to significantly enhance personalization, address engineering challenges such as data management and model training, and introduce data enrichment with reranking as a key solution. Attendees will gain crucial insights into the importance of hyperpersonalization in AI, the capabilities of Full RAG for advanced personalization, and strategies for managing complex data integrations for deploying cutting-edge AI solutions.

Building RAG with self-deployed Milvus vector database and Snowpark Container...

Zilliz

20240605 QFM017 Machine Intelligence Reading List May 2024

Matthew Sinclair

Goodbye Windows 11: Make Way for Nitrux Linux 3.5.0!

SOFTTECHHUB

As the digital landscape continually evolves, operating systems play a critical role in shaping user experiences and productivity. The launch of Nitrux Linux 3.5.0 marks a significant milestone, offering a robust alternative to traditional systems such as Windows 11. This article delves into the essence of Nitrux Linux 3.5.0, exploring its unique features, advantages, and how it stands as a compelling choice for both casual users and tech enthusiasts.

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).

Climate Impact of Software Testing at Nordic Testing Days

Kari Kakkonen

My slides at Nordic Testing Days 6.6.2024 Climate impact / sustainability of software testing discussed on the talk. ICT and testing must carry their part of global responsibility to help with the climat warming. We can minimize the carbon footprint but we can also have a carbon handprint, a positive impact on the climate. Quality characteristics can be added with sustainability, and then measured continuously. Test environments can be used less, and in smaller scale and on demand. Test techniques can be used in optimizing or minimizing number of tests. Test automation can be used to speed up testing.

GraphSummit Singapore | Neo4j Product Vision & Roadmap - Q2 2024

Neo4j

RESUME BUILDER APPLICATION Project for students

KAMESHS29

Generative AI Deep Dive: Advancing from Proof of Concept to Production

Aggregage

Recently uploaded (20)

Introducing Milvus Lite: Easy-to-Install, Easy-to-Use vector database for you...

Data structures and Algorithms in Python.pdf

Essentials of Automations: The Art of Triggers and Actions in FME

UiPath Test Automation using UiPath Test Suite series, part 6

“I’m still / I’m still / Chaining from the Block”

How to Get CNIC Information System with Paksim Ga.pptx

Let's Integrate MuleSoft RPA, COMPOSER, APM with AWS IDP along with Slack

A tale of scale & speed: How the US Navy is enabling software delivery from l...

National Security Agency - NSA mobile device best practices

Microsoft - Power Platform_G.Aspiotis.pdf

GraphSummit Singapore | The Future of Agility: Supercharging Digital Transfor...

Full-RAG: A modern architecture for hyper-personalization

Building RAG with self-deployed Milvus vector database and Snowpark Container...

20240605 QFM017 Machine Intelligence Reading List May 2024

Goodbye Windows 11: Make Way for Nitrux Linux 3.5.0!

Cosa hanno in comune un mattoncino Lego e la backdoor XZ?

Climate Impact of Software Testing at Nordic Testing Days

GraphSummit Singapore | Neo4j Product Vision & Roadmap - Q2 2024

RESUME BUILDER APPLICATION Project for students

Generative AI Deep Dive: Advancing from Proof of Concept to Production

Ariadne harvester and validator - technical overview

1. Validation Framework

2. API Method name : validateMetadata() Return type : void Parameters : Name Datatype metadata String validationScheme String Fault : validationException

3. empty attribute core schematron Legend fields vocabulary bank IMS ILOX rules uses recommended extends schematron rules MACEv1.0 validationScheme vcard validator validation component ASPECTv1.0/ ASPECTv1.0/ recommended core - empty attribute fields rules - empty fields MELTv1.0/ minimal LOM loose lomloose.xsd classification vocab service melt.xsd MACEv1.0/ vcard validator MACEv1.0/strict loose MELTv1.0/full maceLoose maceStrict mace.xsd Schematron.xml Schematron.xml conditional LRE taxon field fields check numerical - empty attribute fields - add. mandatory fields - empty fields - conditional fields - mandatory fields - mace namespace fields

4. empty attribute core schematron Legend fields vocabulary bank IMS ILOX rules uses recommended extends schematron rules MACEv1.0 validationScheme vcard validator validation component ASPECTv1.0/ ASPECTv1.0/ recommended core - empty attribute fields rules - empty fields MELTv1.0/ minimal LOM loose lomloose.xsd classification vocab service melt.xsd MACEv1.0/ vcard validator MACEv1.0/strict loose MELTv1.0/full maceLoose maceStrict mace.xsd Schematron.xml Schematron.xml conditional LRE taxon field fields check numerical - empty attribute fields - add. mandatory fields - empty fields - conditional fields - mandatory fields - mace namespace fields

5. Integration • Java library (see integration with harvester) • REST web-service • web application

6. Maintenance • Adding a new schema • conﬁguration • Adding a new custom component • implementation • conﬁguration • Deploying

7. • New Validation Schema : • add id • properties : URI, components, (type) • component • properties • Create the schemas • structure • vocabulary • additional rules

8. • New custom component • Extend ValidationComponent void validate(String metadata) throws ValidationException; void init(String name, Hashtable<String,String> table) throws InitialisationException; • config : • componentType • schemaLocation

9. ARIADNE Harvester

10. Metadata Provider Harvester OAI-PMH LOM LOM Validation XML Mapping Storage SPI Target File System Lucene ...

11. Installation • Java 5 or higher • Tomcat 5 or higher • build using apache ant • drop in tomcat and done

12. Conﬁguration • http://ariadne.cs.kuleuven.be/nateur- harvester/ • Init • OAI Targets • Scheduling

13. Mapping • Extend GenericMapper • public abstract Element map(Record record); • config : • mapper.mapperClassName.<identifier> = org.ariadne.mapping.BSOMapper

14. Mapping

15. Validation • Integrated ARIADNE validator • Default scheme • Target speciﬁc scheme • Validation Reports

16. Maintenance • Checking if • Installations : harvesting still • GLOBE running • MACE • Follow up validation • MELT reports • ASPECT • Contact content • Organic Edunet providers if target is • Natural Europe down • ICOPER • Assist in solving • ARIADNE validation errors • ... • ...

17. Information • http://ariadne.cs.kuleuven.be/lomi/ index.php/Harvesting_Metadata • http://ariadne.cs.kuleuven.be/lomi/ index.php/Setting_Up_OAI-PMH

Ariadne harvester and validator - technical overview

Recommended

Recommended

More Related Content

More from Bram Vandeputte

More from Bram Vandeputte (15)

Recently uploaded

Recently uploaded (20)

Ariadne harvester and validator - technical overview

Editor's Notes