Platforms can be abstract, workbench-based, or dedicated. Abstract platforms support ideas and conceptual modeling. Workbench platforms provide tools and materials to build applications. Dedicated platforms focus on specific tasks. A case study showed how conceptual graphs and an analogy engine helped analyze legacy software and documentation by identifying files, variables, similarities, and discrepancies. Semantic web technologies could contribute to platform interoperability.
An overview of existing solutions for link discovery and looked into some of the state-of-art algorithms for the rapid execution of link discovery tasks focusing on algorithms which guarantee result completeness.
(HOBBIT project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 688227.)
An overview of existing solutions for link discovery and looked into some of the state-of-art algorithms for the rapid execution of link discovery tasks focusing on algorithms which guarantee result completeness.
(HOBBIT project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 688227.)
An overview of existing solutions for link discovery and looked into some of the state-of-art algorithms for the rapid execution of link discovery tasks focusing on algorithms which guarantee result completeness.
(HOBBIT project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 688227.)
Two Webs! : combining the best of Web 1.0, Web 2.0 and the Semantic WebDanny Ayers
Slides from invited talk at Scripting for the Semantic Web SFSW2007 Workshop at ESW2007. Considering how the old Agent abstraction might be applied to reduce the conceptual complexity of modern Web systems (especially semweb systems).
Biology, medicine, physics, astrophysics, chemistry: all these scientific domains need to process large amount of data with more and more complex software systems. For achieving reproducible science, there are several challenges ahead involving multidisciplinary collaboration and socio-technical innovation with software at the center of the problem. Despite the availability of data and code, several studies report that the same data analyzed with different software can lead to different results. I am seeing this problem as a manifestation of deep software variability: many factors (operating system, third-party libraries, versions, workloads, compile-time options and flags, etc.) themselves subject to variability can alter the results, up to the point it can dramatically change the conclusions of some scientific studies. In this keynote, I argue that deep software variability is a threat and also an opportunity for reproducible science. I first outline some works about (deep) software variability, reporting on preliminary evidence of complex interactions between variability layers. I then link the ongoing works on variability modelling and deep software variability in the quest for reproducible science.
An overview of existing solutions for link discovery and looked into some of the state-of-art algorithms for the rapid execution of link discovery tasks focusing on algorithms which guarantee result completeness.
(HOBBIT project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 688227.)
An overview of existing solutions for link discovery and looked into some of the state-of-art algorithms for the rapid execution of link discovery tasks focusing on algorithms which guarantee result completeness.
(HOBBIT project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 688227.)
An overview of existing solutions for link discovery and looked into some of the state-of-art algorithms for the rapid execution of link discovery tasks focusing on algorithms which guarantee result completeness.
(HOBBIT project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 688227.)
Two Webs! : combining the best of Web 1.0, Web 2.0 and the Semantic WebDanny Ayers
Slides from invited talk at Scripting for the Semantic Web SFSW2007 Workshop at ESW2007. Considering how the old Agent abstraction might be applied to reduce the conceptual complexity of modern Web systems (especially semweb systems).
Biology, medicine, physics, astrophysics, chemistry: all these scientific domains need to process large amount of data with more and more complex software systems. For achieving reproducible science, there are several challenges ahead involving multidisciplinary collaboration and socio-technical innovation with software at the center of the problem. Despite the availability of data and code, several studies report that the same data analyzed with different software can lead to different results. I am seeing this problem as a manifestation of deep software variability: many factors (operating system, third-party libraries, versions, workloads, compile-time options and flags, etc.) themselves subject to variability can alter the results, up to the point it can dramatically change the conclusions of some scientific studies. In this keynote, I argue that deep software variability is a threat and also an opportunity for reproducible science. I first outline some works about (deep) software variability, reporting on preliminary evidence of complex interactions between variability layers. I then link the ongoing works on variability modelling and deep software variability in the quest for reproducible science.
INTERFACE, by apidays - APIs of the Future: Are you Ready? by Mike Amundsenapidays
INTERFACE, by apidays 2021 - It’s APIs all the way down
June 30, July 1 & 2, 2021
APIs of the Future: Are you Ready?
Mike Amundsen, Author of "Design and Build Great APIs"
I summarize requirements for an "Open Analytics Environment" (aka "the Cauldron"), and some work being performed at the University of Chicago and Argonne National Laboratory towards its realization.
Introduction to Big Data Analytics: Batch, Real-Time, and the Best of Both Wo...WSO2
In this webinar, Srinath Perera, director of research at WSO2, will discuss
Big data landscape: concepts, use cases, and technologies
Real-time analytics with WSO2 CEP
Batch analytics with WSO2 BAM
Combining batch and real-time analytics
Introducing WSO2 Machine Learner
Building and deploying LLM applications with Apache AirflowKaxil Naik
Behind the growing interest in Generate AI and LLM-based enterprise applications lies an expanded set of requirements for data integrations and ML orchestration. Enterprises want to use proprietary data to power LLM-based applications that create new business value, but they face challenges in moving beyond experimentation. The pipelines that power these models need to run reliably at scale, bringing together data from many sources and reacting continuously to changing conditions.
This talk focuses on the design patterns for using Apache Airflow to support LLM applications created using private enterprise data. We’ll go through a real-world example of what this looks like, as well as a proposal to improve Airflow and to add additional Airflow Providers to make it easier to interact with LLMs such as the ones from OpenAI (such as GPT4) and the ones on HuggingFace, while working with both structured and unstructured data.
In short, this shows how these Airflow patterns enable reliable, traceable, and scalable LLM applications within the enterprise.
https://airflowsummit.org/sessions/2023/keynote-llm/
WSO2Con ASIA 2016: An Introduction to the WSO2 Analytics PlatformWSO2
In today’s connected world organizations have access to an enormous amount of data. We often don’t know what they mean or how we can use them, in terms of hindsight, oversight, insight and foresight, to gain competitive advantage in the market. Use cases ranging from simple system monitoring to complex fraud analysis demands this.
The WSO2 Data Analytics platform lets you collect data, allows you to explore it through batch, real-time, interactive and predictive processing technologies and allows you to communicate your results. In this talk, we will discuss the WSO2 Data Analytics platform and how it brings together all analytics technologies into a single platform and user experience.
A brief introduction to generative models in general is given, followed by a succinct discussion about text generation models and the "Transformer" architecture. Finally, the focus is set on a non-technical discussion about ChatGPT with a selection of recent news articles.
Transcript: Selling digital books in 2024: Insights from industry leaders - T...BookNet Canada
The publishing industry has been selling digital audiobooks and ebooks for over a decade and has found its groove. What’s changed? What has stayed the same? Where do we go from here? Join a group of leading sales peers from across the industry for a conversation about the lessons learned since the popularization of digital books, best practices, digital book supply chain management, and more.
Link to video recording: https://bnctechforum.ca/sessions/selling-digital-books-in-2024-insights-from-industry-leaders/
Presented by BookNet Canada on May 28, 2024, with support from the Department of Canadian Heritage.
INTERFACE, by apidays - APIs of the Future: Are you Ready? by Mike Amundsenapidays
INTERFACE, by apidays 2021 - It’s APIs all the way down
June 30, July 1 & 2, 2021
APIs of the Future: Are you Ready?
Mike Amundsen, Author of "Design and Build Great APIs"
I summarize requirements for an "Open Analytics Environment" (aka "the Cauldron"), and some work being performed at the University of Chicago and Argonne National Laboratory towards its realization.
Introduction to Big Data Analytics: Batch, Real-Time, and the Best of Both Wo...WSO2
In this webinar, Srinath Perera, director of research at WSO2, will discuss
Big data landscape: concepts, use cases, and technologies
Real-time analytics with WSO2 CEP
Batch analytics with WSO2 BAM
Combining batch and real-time analytics
Introducing WSO2 Machine Learner
Building and deploying LLM applications with Apache AirflowKaxil Naik
Behind the growing interest in Generate AI and LLM-based enterprise applications lies an expanded set of requirements for data integrations and ML orchestration. Enterprises want to use proprietary data to power LLM-based applications that create new business value, but they face challenges in moving beyond experimentation. The pipelines that power these models need to run reliably at scale, bringing together data from many sources and reacting continuously to changing conditions.
This talk focuses on the design patterns for using Apache Airflow to support LLM applications created using private enterprise data. We’ll go through a real-world example of what this looks like, as well as a proposal to improve Airflow and to add additional Airflow Providers to make it easier to interact with LLMs such as the ones from OpenAI (such as GPT4) and the ones on HuggingFace, while working with both structured and unstructured data.
In short, this shows how these Airflow patterns enable reliable, traceable, and scalable LLM applications within the enterprise.
https://airflowsummit.org/sessions/2023/keynote-llm/
WSO2Con ASIA 2016: An Introduction to the WSO2 Analytics PlatformWSO2
In today’s connected world organizations have access to an enormous amount of data. We often don’t know what they mean or how we can use them, in terms of hindsight, oversight, insight and foresight, to gain competitive advantage in the market. Use cases ranging from simple system monitoring to complex fraud analysis demands this.
The WSO2 Data Analytics platform lets you collect data, allows you to explore it through batch, real-time, interactive and predictive processing technologies and allows you to communicate your results. In this talk, we will discuss the WSO2 Data Analytics platform and how it brings together all analytics technologies into a single platform and user experience.
A brief introduction to generative models in general is given, followed by a succinct discussion about text generation models and the "Transformer" architecture. Finally, the focus is set on a non-technical discussion about ChatGPT with a selection of recent news articles.
Transcript: Selling digital books in 2024: Insights from industry leaders - T...BookNet Canada
The publishing industry has been selling digital audiobooks and ebooks for over a decade and has found its groove. What’s changed? What has stayed the same? Where do we go from here? Join a group of leading sales peers from across the industry for a conversation about the lessons learned since the popularization of digital books, best practices, digital book supply chain management, and more.
Link to video recording: https://bnctechforum.ca/sessions/selling-digital-books-in-2024-insights-from-industry-leaders/
Presented by BookNet Canada on May 28, 2024, with support from the Department of Canadian Heritage.
GraphRAG is All You need? LLM & Knowledge GraphGuy Korland
Guy Korland, CEO and Co-founder of FalkorDB, will review two articles on the integration of language models with knowledge graphs.
1. Unifying Large Language Models and Knowledge Graphs: A Roadmap.
https://arxiv.org/abs/2306.08302
2. Microsoft Research's GraphRAG paper and a review paper on various uses of knowledge graphs:
https://www.microsoft.com/en-us/research/blog/graphrag-unlocking-llm-discovery-on-narrative-private-data/
The Art of the Pitch: WordPress Relationships and SalesLaura Byrne
Clients don’t know what they don’t know. What web solutions are right for them? How does WordPress come into the picture? How do you make sure you understand scope and timeline? What do you do if sometime changes?
All these questions and more will be explored as we talk about matching clients’ needs with what your agency offers without pulling teeth or pulling your hair out. Practical tips, and strategies for successful relationship building that leads to closing the deal.
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...DanBrown980551
Do you want to learn how to model and simulate an electrical network from scratch in under an hour?
Then welcome to this PowSyBl workshop, hosted by Rte, the French Transmission System Operator (TSO)!
During the webinar, you will discover the PowSyBl ecosystem as well as handle and study an electrical network through an interactive Python notebook.
PowSyBl is an open source project hosted by LF Energy, which offers a comprehensive set of features for electrical grid modelling and simulation. Among other advanced features, PowSyBl provides:
- A fully editable and extendable library for grid component modelling;
- Visualization tools to display your network;
- Grid simulation tools, such as power flows, security analyses (with or without remedial actions) and sensitivity analyses;
The framework is mostly written in Java, with a Python binding so that Python developers can access PowSyBl functionalities as well.
What you will learn during the webinar:
- For beginners: discover PowSyBl's functionalities through a quick general presentation and the notebook, without needing any expert coding skills;
- For advanced developers: master the skills to efficiently apply PowSyBl functionalities to your real-world scenarios.
Let's dive deeper into the world of ODC! Ricardo Alves (OutSystems) will join us to tell all about the new Data Fabric. After that, Sezen de Bruijn (OutSystems) will get into the details on how to best design a sturdy architecture within ODC.
Smart TV Buyer Insights Survey 2024 by 91mobiles.pdf91mobiles
91mobiles recently conducted a Smart TV Buyer Insights Survey in which we asked over 3,000 respondents about the TV they own, aspects they look at on a new TV, and their TV buying preferences.
UiPath Test Automation using UiPath Test Suite series, part 3DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 3. In this session, we will cover desktop automation along with UI automation.
Topics covered:
UI automation Introduction,
UI automation Sample
Desktop automation flow
Pradeep Chinnala, Senior Consultant Automation Developer @WonderBotz and UiPath MVP
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
Accelerate your Kubernetes clusters with Varnish CachingThijs Feryn
A presentation about the usage and availability of Varnish on Kubernetes. This talk explores the capabilities of Varnish caching and shows how to use the Varnish Helm chart to deploy it to Kubernetes.
This presentation was delivered at K8SUG Singapore. See https://feryn.eu/presentations/accelerate-your-kubernetes-clusters-with-varnish-caching-k8sug-singapore-28-2024 for more details.
GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using Deplo...James Anderson
Effective Application Security in Software Delivery lifecycle using Deployment Firewall and DBOM
The modern software delivery process (or the CI/CD process) includes many tools, distributed teams, open-source code, and cloud platforms. Constant focus on speed to release software to market, along with the traditional slow and manual security checks has caused gaps in continuous security as an important piece in the software supply chain. Today organizations feel more susceptible to external and internal cyber threats due to the vast attack surface in their applications supply chain and the lack of end-to-end governance and risk management.
The software team must secure its software delivery process to avoid vulnerability and security breaches. This needs to be achieved with existing tool chains and without extensive rework of the delivery processes. This talk will present strategies and techniques for providing visibility into the true risk of the existing vulnerabilities, preventing the introduction of security issues in the software, resolving vulnerabilities in production environments quickly, and capturing the deployment bill of materials (DBOM).
Speakers:
Bob Boule
Robert Boule is a technology enthusiast with PASSION for technology and making things work along with a knack for helping others understand how things work. He comes with around 20 years of solution engineering experience in application security, software continuous delivery, and SaaS platforms. He is known for his dynamic presentations in CI/CD and application security integrated in software delivery lifecycle.
Gopinath Rebala
Gopinath Rebala is the CTO of OpsMx, where he has overall responsibility for the machine learning and data processing architectures for Secure Software Delivery. Gopi also has a strong connection with our customers, leading design and architecture for strategic implementations. Gopi is a frequent speaker and well-known leader in continuous delivery and integrating security into software delivery.
Neuro-symbolic is not enough, we need neuro-*semantic*Frank van Harmelen
Neuro-symbolic (NeSy) AI is on the rise. However, simply machine learning on just any symbolic structure is not sufficient to really harvest the gains of NeSy. These will only be gained when the symbolic structures have an actual semantics. I give an operational definition of semantics as “predictable inference”.
All of this illustrated with link prediction over knowledge graphs, but the argument is general.
Dev Dives: Train smarter, not harder – active learning and UiPath LLMs for do...UiPathCommunity
💥 Speed, accuracy, and scaling – discover the superpowers of GenAI in action with UiPath Document Understanding and Communications Mining™:
See how to accelerate model training and optimize model performance with active learning
Learn about the latest enhancements to out-of-the-box document processing – with little to no training required
Get an exclusive demo of the new family of UiPath LLMs – GenAI models specialized for processing different types of documents and messages
This is a hands-on session specifically designed for automation developers and AI enthusiasts seeking to enhance their knowledge in leveraging the latest intelligent document processing capabilities offered by UiPath.
Speakers:
👨🏫 Andras Palfi, Senior Product Manager, UiPath
👩🏫 Lenka Dulovicova, Product Program Manager, UiPath
"Impact of front-end architecture on development cost", Viktor TurskyiFwdays
I have heard many times that architecture is not important for the front-end. Also, many times I have seen how developers implement features on the front-end just following the standard rules for a framework and think that this is enough to successfully launch the project, and then the project fails. How to prevent this and what approach to choose? I have launched dozens of complex projects and during the talk we will analyze which approaches have worked for me and which have not.
2. Notetaking – not really necessary, just bookmark:
http://hyperdata.org/krdb2010
Questions – if I'm not clear any time, please raise your hand,
general questions at the end
Mobile phones – be discrete!
IRC -
Server: irc.freenode.net
Channel: #swig
available through a browser at: http://www.mibbit.com
Twitter tag - #krdb
(I'm @danja)
3. Objectives
To answer questions like :
● What is a platform?
● What are the benefits of using platforms?
● What is a Web platform?
● How can Semantic Web technologies contribute?
● How do different kinds of platforms compare, and
what analogies might be useful?
4. Part 1 : Platforms in General
● Defining “Platform”
● A Plethora of Platforms
● Working with Web Platforms
[a <http://dbpedia.org/resource/Coffee_break>]
Part 2 : Semantic Web Platforms
● Review of Semantic Web Technologies
● Semantic Web Platforms
● The Web as Platform
6. “Platform” (“Piattaforma”)
● a raised horizontal surface (palco)
● political program - a document stating the
aims and principles of a political party
things
●the combination of a particular computer which
and a particular operating system support
something
●weapons platform - any military structure else
or vehicle bearing weapons
●platform shoe, chopine - a woman's shoe
with a very high thick sole (zeppa)
Source: Wordnet
12. Working Definition
A platform is a system designed to keep developers
and users out of the mud and closer to heaven.
Una piattaforma è un sistema progettato per
mantenere gli sviluppatori e gli utenti fuori dal fango e
più vicino al cielo.
13. Layered Models
Layer n + 1
Supports Depends on
Layer n
Supports Depends on
Layer n - 1
14. A Plethora of Platforms
loose taxonomy:
● Abstract Platforms
● Workbench Platforms
● Dedicated Platforms
15. Abstract Platforms
What do they support? : Ideas
● branches of mathematics
e.g. geometry, logic
● the sciences
● human languages
● the arts
16. Geometry
Typical mode of use : modelling physical systems
Applications : surveying (earth-measuring),
architecture, engineering...
18. Logic
(propositional, just declarative statements)
A
& C
B
C=A∧B
Typical mode of use : modelling electronic systems
Applications : control circuits, building computers...
19. Logic
(adding predicates and quantifiers)
(∃x)(∃y)(Go(x) ∧ Person(John) ∧ City(Boston) ∧ Bus(y)
∧ Agnt(x,John) ∧ Dest(x,Boston) ∧ Inst(x,y))
(∃x)(∃y)(Go(x) ∧ Person(John) ∧ City(Boston) ∧ Bus(y)
∧ Agnt(x,John) ∧ Dest(x,Boston) ∧ Inst(x,y))
Typical mode of use : modelling physical systems
Applications : knowledge representation & processing
Source: John F. Sowa, http://www.jfsowa.com/krbook
20. Conceptual Graphs
(a dialect of Common Logic)
(∃x)(∃y)(Go(x) ∧ Person(John) ∧ City(Boston) ∧ Bus(y)
∧ Agnt(x,John) ∧ Dest(x,Boston) ∧ Inst(x,y))
Concepts :
Named Entities : John, Boston
Entity Types : Person, Go, City, Bus
Relations : Agnt (Agent), Dest (Destination), Inst (Instrument)
Source: John F. Sowa, http://www.jfsowa.com/krbook
22. Natural Language to CGs
John is going to Boston by bus.
Informal
The person John is the agent of some instance of
going, the city Boston is the destination, and a bus is
the instrument.
Formal
23. Conceptual Graphs can be derived from
Natural Language.
Conceptual Graphs express knowledge
in a formal mathematical language.
But why should we care about
something so abstract?
24. Case Study : Legacy Re-engineering
Analyze software and documentation of a large corporation.
Generate :
● English glossary of all terms with pointers to the software
● Structure diagrams of the programs, files, and data
● List of discrepancies between software and documentation
Source: John Sowa, http://www.jfsowa.com/talks/iss.pdf
25. Case Study : Legacy Re-engineering
Software
1.5 million lines of COBOL programs in daily use, some of
which up to 40 years old
Documentation
100 megabytes of English reports, manuals, e-mails, Lotus
Notes, HTML, and program comments
Source: John Sowa, http://www.jfsowa.com/talks/iss.pdf
26. COBOL Examples
IDENTIFICATION DIVISION.
PROGRAM-ID. HELLO-WORLD.
PROCEDURE DIVISION.
DISPLAY 'Hello, world'.
STOP RUN.
ADD YEARS TO AGE
age = age + years
“The use of COBOL cripples the mind; its teaching should, therefore, be regarded
as a criminal offense." - Dijkstra
Source : http://en.wikipedia.org/wiki/Cobol
27. Case Study : Legacy Re-engineering
A major consulting firm had estimated that the job would take
40 people two years to analyze the documentation and
determine the cross references.
Source: John Sowa, http://www.jfsowa.com/talks/iss.pdf
28. Case Study : Legacy Re-engineering
Approach
● Translate the COBOL programs to Conceptual Graphs
● Use the Conceptual Graphs from COBOL to interpret the
English
● Use the Analogy Engine to compare the graphs derived
from COBOL to the graphs derived from English
● Record the similarities and discrepancies
Source: John Sowa, http://www.jfsowa.com/talks/iss.pdf
29. Case Study : Legacy Re-engineering
VivoMind Analogy Engine
Three methods of analogy:
1. Matching labels:
* Compare type labels on conceptual graphs.
2. Matching subgraphs:
* Compare subgraphs independent of labels.
3. Matching transformations:
* Transform subgraphs.
Source: John Sowa, http://www.jfsowa.com/talks/mitre.htm
30. Case Study : Legacy Re-engineering
Excerpt from the Documentation
The input file that is used to create this piece of the Billing
Interface for the General Ledger is an extract from the 61 byte file
that is created by the COBOL program BILLCRUA in the Billing
History production run. This file is used instead of the history file
for time efficiency. This file contains the billing transaction codes
(types of records) that are to be interfaced to General Ledger for
the given month.
For this process the following transaction codes are used: 32 —
loss on unbilled, 72 — gain on uncollected, and 85 — loss on
uncollected. Any of these records that are actually taxes are
bypassed. Only client types 01 — Mar, 05 — Internal
Non/Billable, 06 — Internal Billable, and 08 — BAS are selected.
This is determined by a GETBDATA call to the client file.
Note that none of the files or COBOL variables are named.
By matching the English graphs to the COBOL graphs, VAE
identified all the file names and COBOL variables involved.
Source: John Sowa, http://www.jfsowa.com/talks/iss.pdf
31. Case Study : Legacy Re-engineering
Job finished in 8 weeks by two programmers, Arun Majumdar
and André LeClerc.
● Four weeks for customization: Design, ontology, and
additional programming for I/O formats.
●Three weeks to run English parser + VAE + extensions:
VAE handled matches with strong evidence (close semantic
distance). Matches with weak evidence were confirmed or
corrected by Majumdarand LeClerc.
● One week to produce a CD-ROM with integrated views
of the results: Glossary, data dictionary, data flow diagrams,
process architecture, system context diagrams.
Source: John Sowa, http://www.jfsowa.com/talks/iss.pdf
32. Case Study : Legacy Re-engineering
Contradiction Found by VAE
From analyzing English documentation:
● Every employee is a human being.
● No human being is a computer.
From analyzing COBOL programs:
● Some employees are computers.
What is the reason for this contradiction?
Source: John Sowa, http://www.jfsowa.com/talks/iss.pdf
33. Case Study : Legacy Re-engineering
In 1979 a COBOL programmer made a quick patch :
● Two computers were used to assist human consultants.
● But there was no provision to bill for computer time.
● Therefore, the programmer named the computers Bob and
Sally, and assigned them employee IDs.
Source: John Sowa, http://www.jfsowa.com/talks/iss.pdf
34. Case Study : Legacy Re-engineering
For more than 20 years:
● Bob and Sally were issued payroll checks.
● But they never cashed them.
VAE discovered the two computer “employees.”
Source: John Sowa, http://www.jfsowa.com/talks/iss.pdf
35. Why should we care about
abstract platforms?
- concrete benefits.
36. All models are wrong.
Some are useful.
- George E. P. Box
37. A Plethora of Platforms
loose taxonomy:
● Abstract Platforms
● Workbench Platforms
● Dedicated Platforms
38. Workbench Platforms
What do they support? :
tools and raw materials
...but end product will often be
indirect
39.
40. A “Jig”
- a device that holds a piece of work and
guides the tools operating on it
54. Virtual Machine as Platform
- Java Style
User Developer
Applications Coding Tools
JRE JDK
JVM
Operating System
Hardware
55. Virtual Machine as Platform
- Squeak Style
Users and Developers
Applications & Coding Tools
System Image
VM
Operating System
Hardware
(See also : emacs)
62. Eclipse Platform
● Core functionality : fairly generic app stuff
● Built on a mechanism for discovering, integrating,
and running modules called plug-ins
● Plug-ins represented as bundles based on the
OSGi * specification
(* originally Open Services Gateway initiative)
83. HTML
<!DOCTYPE html>
<html>
...
<h2>
<a href="http://localhost/wordpress/?p=4">Hello localhost!</a>
</h2>
<p>This is some sample text which doesn’t really</p>
<p>say a lot</p>
…
</html>
84. RSS
...
<item>
<title>Hello localhost!</title>
<link>http://localhost/wordpress/?p=4</link>
<pubDate>Wed, 15 Sep 2010 14:31:01 +0000</pubDate>
<dc:creator>admin</dc:creator>
<description><![CDATA[This is some sample text which
doesn’t really say a lot]]></description>
</item>
...
85. System Characteristics :
Recording Studio
● Raw Input : instrument output/sounds
(various acoustic/electrical signals)
● Output : music (combined and more structured
acoustic/electrical signals) sometimes
● Processing : analog & digital signal processing and mixing
● Storage : computer filesystem
● User Interface : core DAW GUI, plus per-module UI
86. Data Characteristics : Recording Studio
“Models”
● Analog Signals
● Digital Signals
● Structured Recordings (multi-track time/amplitude)
Formats
● Audio data formats (wav, aiff, mp3, CD formats)
● MIDI file format
● Proprietary DAW multi-track format
Protocols
● Analog audio (various levels/impedances)
● MIDI protocol
87. System Characteristics :
Content Management System
● Raw Input : human-readable text + annotations
● Output : more structured text published as Web
resources (HTTP+HTML/RSS)
● Processing : text data structured into DB, converted into
markup
● Storage : SQL Database
● User Interface : HTML in Web browser (dashboard or output)
88. Data Characteristics :
Content Management System
Models
● DB Schema
● Markup
Formats
● HTML
● RSS
● Binary image formats
● SQL
● (PHP)
Protocols
● HTTP
89. Parallels can be drawn
between different kinds of
platforms.
So what?
90. Problem : Impedance mismatch
I want to connect electric guitar directly to mixer, but -
● Signal from electric guitar : 2 volts @ 10 kΩ impedance
● Signal expected by mixer is 20mV @ 100Ω
92. Impedance Matching Transformer
(DI Box)
Signal from
electric guitar Signal to mixer
(10 kΩ output (100 Ω input)
impedance)
(electricity - magnetic flux - electricity)
93. Problem : Impedance mismatch
I want to connect a blog feed directly to a particular aggregator,
but -
● Signal from blog is RSS 2.0
● Signal expected by aggregator is Atom
103. Parallels can be drawn
between different kinds of
platforms.
So what?
Problems in one domain may
have been solved in another.
104. Problem : multitrack structures not
available outside DAW for other tools
● proprietary format only
● vafanculo, need to talk to their developers
105. Wordpress Export
“When you click the button below WordPress will create an XML
file for you to save to your computer.
This format, which we call WordPress eXtended RSS or WXR,
will contain your posts, pages, comments, custom fields,
categories, and tags.”
119. Semantic Web = Web of Data
Informed by :
● Traditional RDBMS & other kinds of data store
● Logics
● Grids
● “The Cloud”
● Hypertext and the Web!
120. Logical Base
● open world assumption
● uniform identifiers
● declarative sentences
121. What works on the Web?
● Uniform Identifiers (URIs)
– for resources
● Common Interface Protocol (HTTP)
● Standard Representation Formats
(notably HTML)
Altogether: a REST Configuration
122. A hyperlink
page.html home.html
<a href=”http://example.org/home.html“>
Home Page
</a>
123. Evolving the Link
page.html home.html
home
<a href=”http://example.org/home.html”
rel=”home”>
Home Page
</a>
124. page home
x:home
<rdf:Description
rdf:about=”http://example.org/page”>
<x:home
rdf:resource=”http://example.org/home” />
</rdf:Description>
138. Part 1 : Platforms in General
● Defining “Platform”
● A Plethora of Platforms
● Working with Web Platforms
[a <http://dbpedia.org/resource/Coffee_break>]
Part 2 : Semantic Web Platforms