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Slides for the presentation at Elastic {ON} Tour Tokyo 2017
https://www.elastic.co/elasticon/tour/2017/tokyo
Session Video: https://www.elastic.co/jp/elasticon/tour/2017/tokyo/microsoft
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Looking to implement MLOps using AWS services and Kubeflow? Come and learn about machine learning from the experts of Provectus and Amazon Web Services (AWS)!
Businesses recognize that machine learning projects are important but go beyond just building and deploying models, which is mostly done by organizations. Successful ML projects entail a complete lifecycle involving ML, DevOps, and data engineering and are built on top of ML infrastructure.
AWS and Amazon SageMaker provide a foundation for building infrastructure for machine learning while Kubeflow is a great open source project, which is not given enough credit in the AWS community. In this webinar, we show how to design and build an end-to-end ML infrastructure on AWS.
Agenda
- Introductions
- Case Study: GoCheck Kids
- Overview of AWS Infrastructure for Machine Learning
- Provectus ML Infrastructure on AWS
- Experimentation
- MLOps
- Feature Store
Intended Audience
Technology executives & decision makers, manager-level tech roles, data engineers & data scientists, ML practitioners & ML engineers, and developers
Presenters
- Stepan Pushkarev, Chief Technology Officer, Provectus
- Qingwei Li, ML Specialist Solutions Architect, AWS
Feel free to share this presentation with your colleagues and don't hesitate to reach out to us at info@provectus.com if you have any questions!
REQUEST WEBINAR: https://provectus.com/webinar-mlops-and-reproducible-ml-on-aws-with-kubeflow-and-sagemaker-aug-2020/
The document provides an overview of Microsoft SQL Server Reporting Services (SSRS). It discusses SSRS architecture and components. It outlines new features in SSRS 2008 related to report authoring, processing, rendering, server architecture, and programmability. Steps for creating a shared data source and designing basic reports using the report designer are also presented.
Slides for the presentation at Elastic {ON} Tour Tokyo 2017
https://www.elastic.co/elasticon/tour/2017/tokyo
Session Video: https://www.elastic.co/jp/elasticon/tour/2017/tokyo/microsoft
MLOps and Reproducible ML on AWS with Kubeflow and SageMakerProvectus
Looking to implement MLOps using AWS services and Kubeflow? Come and learn about machine learning from the experts of Provectus and Amazon Web Services (AWS)!
Businesses recognize that machine learning projects are important but go beyond just building and deploying models, which is mostly done by organizations. Successful ML projects entail a complete lifecycle involving ML, DevOps, and data engineering and are built on top of ML infrastructure.
AWS and Amazon SageMaker provide a foundation for building infrastructure for machine learning while Kubeflow is a great open source project, which is not given enough credit in the AWS community. In this webinar, we show how to design and build an end-to-end ML infrastructure on AWS.
Agenda
- Introductions
- Case Study: GoCheck Kids
- Overview of AWS Infrastructure for Machine Learning
- Provectus ML Infrastructure on AWS
- Experimentation
- MLOps
- Feature Store
Intended Audience
Technology executives & decision makers, manager-level tech roles, data engineers & data scientists, ML practitioners & ML engineers, and developers
Presenters
- Stepan Pushkarev, Chief Technology Officer, Provectus
- Qingwei Li, ML Specialist Solutions Architect, AWS
Feel free to share this presentation with your colleagues and don't hesitate to reach out to us at info@provectus.com if you have any questions!
REQUEST WEBINAR: https://provectus.com/webinar-mlops-and-reproducible-ml-on-aws-with-kubeflow-and-sagemaker-aug-2020/
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Watch full webinar here: https://buff.ly/2KTz2IB
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Attend this session to learn:
- What’s the role of Denodo in an API strategy
- Integration between Denodo and other elements of the API stack, like API management tools
- How easy it is to access Denodo as a RESTful endpoint
- Advanced options of Denodo web services: OAuth, OpenAPI, geographical capabilities, etc.
For the full video of this presentation, please visit:
https://www.embedded-vision.com/platinum-members/renesas/embedded-vision-training/videos/pages/may-2019-embedded-vision-summit
For more information about embedded vision, please visit:
http://www.embedded-vision.com
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The Dynamically Reconfigurable Processing (DRP) block in the Arm Cortex-A9 based RZ/A2M MPU accelerates image processing algorithms with spatially pipelined, time-multiplexed, reconfigurable- hardware compute resources. This hybrid ARM/DRP architecture combines the economy, flexibility and ease-of-use of microprocessors with the high throughput and low latency of performance- optimized hardware.
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In this presentation, Sato examines the DRP block’s architecture and operation, presents benchmarks demonstrating performance up to 20x greater than traditional CPUs and introduces resources for developing DRP-based embedded vision systems with the RZ/A2M MPU.
世間では、情報システムの運用・監視の「自動化」というキーワードがもてはやされがちで、各種のツール・プロダクト等が出てくる昨今です。しかし、「自動化」の実態は深い霧のベールに包まれていると感じていませんか。今回は、以下の現場視点でこのベールを脱がしてみたいと思います。
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#jtf2016
平成28年7月24日(日)
valohai에서 발표한 2021, State of MLOps 2021 survey 자료를 요약하여 정리한 것입니다. 조직내에서 MLOps 와 관련하여 역할과 팀의 규모, 집중하는 영역, 현재 툴링화 하여 사용하고 있는 영역 등에 대한 100명의 응답자 내용을 정리한 것입니다.
Denodo as the Core Pillar of your API StrategyDenodo
Watch full webinar here: https://buff.ly/2KTz2IB
Most people associate data virtualization with BI and analytics. However, one of the core ideas behind data virtualization is the decoupling of the consumption method from the data model. Why should the need for data requests in JSON over HTTP require extra development? Denodo provides immediate access to its datasets via REST, OData 4, GeoJSON and other protocols, with no coding involved. Easy to scale, cloud friendly and ready to integrate with API management tools, Denodo can be the perfect tool to fulfill your API strategy!
Attend this session to learn:
- What’s the role of Denodo in an API strategy
- Integration between Denodo and other elements of the API stack, like API management tools
- How easy it is to access Denodo as a RESTful endpoint
- Advanced options of Denodo web services: OAuth, OpenAPI, geographical capabilities, etc.
For the full video of this presentation, please visit:
https://www.embedded-vision.com/platinum-members/renesas/embedded-vision-training/videos/pages/may-2019-embedded-vision-summit
For more information about embedded vision, please visit:
http://www.embedded-vision.com
Yoshio Sato, Senior Product Marketing Manager in the Industrial Business Unit at Renesas, presents the "Dynamically Reconfigurable Processor Technology for Vision Processing" tutorial at the May 2019 Embedded Vision Summit.
The Dynamically Reconfigurable Processing (DRP) block in the Arm Cortex-A9 based RZ/A2M MPU accelerates image processing algorithms with spatially pipelined, time-multiplexed, reconfigurable- hardware compute resources. This hybrid ARM/DRP architecture combines the economy, flexibility and ease-of-use of microprocessors with the high throughput and low latency of performance- optimized hardware.
DRP technology achieves silicon area efficiency by dividing large data paths into sub- blocks that can be swapped into the DRP hardware on each clock cycle to accelerate multiple complex algorithms while avoiding the cost and power penalties associated with large FPGAs. Pre-built libraries and a C-language programming environment deliver these benefits without the need for hardware design expertise. Designs can be iteratively enhanced through pre-production and even after mass-market deployment.
In this presentation, Sato examines the DRP block’s architecture and operation, presents benchmarks demonstrating performance up to 20x greater than traditional CPUs and introduces resources for developing DRP-based embedded vision systems with the RZ/A2M MPU.
世間では、情報システムの運用・監視の「自動化」というキーワードがもてはやされがちで、各種のツール・プロダクト等が出てくる昨今です。しかし、「自動化」の実態は深い霧のベールに包まれていると感じていませんか。今回は、以下の現場視点でこのベールを脱がしてみたいと思います。
July Tech Festa 2016 発表資料
#jtf2016
平成28年7月24日(日)
valohai에서 발표한 2021, State of MLOps 2021 survey 자료를 요약하여 정리한 것입니다. 조직내에서 MLOps 와 관련하여 역할과 팀의 규모, 집중하는 영역, 현재 툴링화 하여 사용하고 있는 영역 등에 대한 100명의 응답자 내용을 정리한 것입니다.
The document discusses cyber-physical systems and the role of architecture description languages. It covers topics like heterogeneous systems, design challenges and possibilities, and examples. Architecture description languages play a key role by enabling abstraction and modeling of complex CPS, allowing exploration of design alternatives, and serving as standardized documentation. Some challenges of CPS design include interdisciplinary collaboration, security, scalability, and meeting real-time constraints.
CASE (COMPUTER AIDED SOFTWARE ENGINEERING)
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project management
Internal Interface
Reverse Software Engineering
Architecture of CASE environment.
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CASE tools are programs that automate and support various phases of the software development life cycle. They include components like a central repository to store diagrams and reports, diagramming tools, documentation tools, and code generation tools. CASE tools can improve software quality, reduce errors, standardize processes, and speed up development times. Some examples of CASE tools include programming tools, documentation tools, diagramming tools, and requirement tracing tools.
Agile Methodology Approach to SSRS Reporting. How to utilize principles from Agile project management process and utilize it for creating better SSRS reports.
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This presentation is about a lecture I gave within the "Software systems and services" immigration course at the Gran Sasso Science Institute, L'Aquila (Italy): http://cs.gssi.infn.it/.
http://www.ivanomalavolta.com
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Recording:
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Despite its grandiose-sounding title, this deck consists of just three slides showing the Scala 3 code to be rewritten whenever the details of the operators begin to fade away.
The code is my rough and ready translation of a Haskell user-validation program found in a book called Finding Success (and Failure) in Haskell - Fall in love with applicative functors.
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Explore the seamless transition to e-invoicing with this comprehensive guide tailored for Saudi Arabian businesses. Navigate the process effortlessly with step-by-step instructions designed to streamline implementation and enhance efficiency.
E-Invoicing Implementation: A Step-by-Step Guide for Saudi Arabian Companies
Open CAESAR Initiative
1. Open CAESAR Initiative
INTRODUCING THE
Maged Elaasar, PhD (elaasar@jpl.nasa.gov)
IMCE Program Software Architect
January 24, 2019
Copyright 2019 California Institute of Technology. Government sponsorship acknowledged
MBSE Symposium
Approved for U.S. and foreign release under CL#19-0535
2. • Reference herein to any specific commercial product, process, or service
by trade name, trademark, manufacturer, or otherwise, does not
constitute or imply its endorsement by the United States Government or
the Jet Propulsion Laboratory, California Institute of Technology
2
Disclaimer
3. Key MBSE challenges
3
Challenges Mitigations
System modeling tools are too complex
and rigid to use for systems engineers
à
We need to use domain-specific tools to
lower the bar to entry and provide
curated libraries and model templates
Different projects create system models
differently making it hard to reuse or
analyze consistently à
We need to define modeling
methodologies and facilitate
conforming to them using tools
Heterogeneous tools are used in SE
because many discipline-specific analyses
are needed à
We need effective tool integration
strategies, facilitating cross tool linking
or interchange
Model content is rapidly changing as
work progresses, increasing risk, and
latency in decision making à
We need effective cross-tools
configuration management, change
management, and continuous
automated analysis
Models are being authored by separate
teams with different concerns/expertise
à
We need to enable federated multi-
viewpoint architecture with methods to
keep the viewpoints aligned
Standard model notation is not sufficient
to present their content and
communicate it to stakeholders à
We need ability to design custom
reporting viewpoints, automatically
generate and make them accessible
4. 4
Modern MBSE process
Methodology Vocabulary
Authoring Viewpoint
Automated Analysis
Continuous Integration
Baseline Configuration
Reporting Viewpoint
Feedback Mechanism
Variant Configuration
Change Proposal
induces
conforms toautomates
authors
merges into
triggers
involves
produces
allows
generates
incorporates
Mostly not
rigorous or ill-
defined now
Not existent or has
no well-defined
semantics now
Typically fragmented across
tools with different schemas
and formats
Typically done sporadically
around milestones now
Not always
supported
now or
have poor
support
Typically run manually and
from client applications now
Typically limited to a few
standard viewpoints and
not easily accessible
Not always
clearly identified
Typically done ad-hoc and
hard to keep track of
Typically
done
manually with
no tool
support
5. • CAESAR stands for Computer Aided Engineering for Systems ARchitecture
– A software platform to enable an integrated model centric approach to SE
• Addresses key challenges with carrying out a scalable and agile MBSE process
• Enables a methodology-driven use of SE tools to perform SE functions
• Promotes reuse of existing technology while minimizing vendor lock-in
• Infuses development best practices learned from software engineering
5
What is CAESAR?
Integrated Model Centric Engineering
(IMCE)
Model Based Systems Engineering
(MBSE)
transforms into
6. The CAESAR Concept
6
CAESAR
CAESAR Ecosystem
Authoring Tools Analysis/Reporting Tools
• A semantic data warehouse system for MBSE
– Acquires information from SE authoring tools acting as data sources
– Curates, integrates, configuration manages SE information baseline in one place
– Verifies the consistency of federated information and measures precise differences
– Analyzes information, generates reports and proposes changes
System
Development
Team
System
Stakeholders
7. 7
Key Functions
Information Authoring
Supports authoring information by
different tools, which can be existing tools
that have been adapted or new
methodology-specific tools
Information Representation
Supports representing information using
tool-neutral ontologies that have modular
design, expressive syntax & formal semantics
Information Analysis
Supports analyzing information with
reasoners and by other analysis tools
using published query end points and APIs
Information Configuration
Supports maintaining a baseline configuration
for information (as well as variant
configurations) and version controlling the
results of running integration workflows
Information Reporting
Supports authoring reports on information
to address different stakeholder concerns,
regenerating them when the integration
workflows rerun and organizing them in
accessible reporting dashboards
Information Integration
Supports defining methodology specific
integrating workflows for the information
fragments and proposing changes to keep
them consistent
8. • CAESAR represents Information as a set of ontologies expressed in the
Ontology Modeling Language (OML)
• OML is a tool-neutral representation that allows representing
information, exchanging it, and analyzing it using a variety of tools
• OML is designed after the W3C standard Web Ontology Language 2
(OWL2) making it expressive, modular and extensible
• OML has Description Logic semantics allowing reasoning with over-the-
shelf DL reasoners
8
Information representation
APIs
Exchange
formats
IDEs
Analysis
Formats
EMF
ScalaJS
REST
DSL
JSON
ZIP XMI
Eclipse
VS Code
Theia
RDF/SPARQL
Parquet/SQL
OML
Maps to
9. 9
Information architecture
System Analysis
System Design
Application
Discipline
Foundation
Base MissionXSD ProjectAnalysis
V&V Behavior Requirements Structure
Fault
Protection
Ground
System
Electrical
specializes
specializes
Mechanical
Flight
System
System A Subsystem B
specializes
Subsystem C
:System A :Subsystem B :Subsystem C
Vocabulary Ontologies
(Project-independent)
User Ontologies
(Project-specific) Instance of
OML
10. CAESAR
• CAESAR enables authoring ontologies directly in OML textual/graphical
DSLs using one of its OML IDEs (Eclipse, VS Code, and Theia)
• CAESAR enables authoring ontologies using its own CAESAR IDE, a multi-
disciplinary modeling tool which can be extended with custom viewpoints
• CAESAR also enables authoring ontologies using third party tools that
have been adapted using a tool adapter (which supports bi-directional
transformations between OML and the tool’s native format)
10
Information authoring
Third Party Tool
Tool
Adapter
OML IDE
OML
OML
Native
Native
Tool
Adapter
CAESAR IDE
OML
Methodology
Extension
If needed
11. • CAESAR enables methodology-specific incremental integration of
ontology fragments (from different tools) into a unified dataset
• The integration methodology is specified as a workflow graph whose
nodes are configured with analysis scripts and that can be run manually
or automatically based on events
• CAESAR helps maintain consistency between the integrated fragments
by proposing changes to those fragments to restore consistency
11
Information integration
CAESARData Source
A
Data Source
C
Data Source
B
A
B
C
A+B
A+B+C
B+C
Every node runs
analysis scripts
Change proposal
Change Integration
Overlap
that needs to
be consistent
Fully
Integrated
model
12. • CAESAR supports query APIs and a query language (SPARQL), which
can be used by any tool to perform powerful analysis on the dataset
• CAESAR supports a rule language and some default analyses through
a DL reasoner like satisfiability analysis (every class can be
instantiated) and consistency checking (no contradictory axioms exist)
• CAESAR supports optimizing analysis pipelines by developing common
analyses building blocks that can be reused
12
Information analysis
CAESAR DL Reasoner
Audit
Framework
Satisfiability Analysis
Consistency Check
Well-formedness analysis
Query
endpoint & API
Notebooks, Mathematica,
etc.
Analysis Database
Map, Filter, Reduce
13. • CAESAR allows creating reports on datasets or their analysis results
using a variety of reporting tools to address stakeholders concerns
• Reports can be automatically produced during integration and stored
for efficient viewing later (historical reports are archived)
• Reports are published on a project portal, where they are organized in
categories and can be searched and viewed (with access control)
• Reports can be commented on and/or approved by stakeholders
13
Information reporting
CAESAR
Tool Adapters
14. • CAESAR allows a project to have a baseline configuration of data sources,
as well as variant configurations (representing change proposals)
• The project integration workflow can run on any configuration allowing the
impact of changes to be analyzed before merging them into baseline
• The entire history of integration (including datasets, analysis results and
reports) with full provenance is version controlled
• The configuration history enables provenance audit, trend analysis, as
well as the possibility for incremental analysis
14
Information configuration
v3
V2
V1
CAESARData Source
A’
Data Source
B
Data Source
A
A’
A
B
A’+B
A+B
15. 15
CAESAR conceptual architecture
CAESAR Server
CAESAR Ecosystem
Adapter
CAESAR Client
API
Integration
Service
repository
Authoring
Tool
Reporting
Tool
Configuration
Service
Analysis
Service
Reporting
Service
C/M
Repository
Analysis
Repository
Adapter
repository
Analysis
Scripts
Analysis
Tool
Libraries /
Templates
16. CAESAR Hydrogen release : EFSE application
16
CAESAR Server
AdapterAdapter
API
Adapter
Repo
Reop
Electrical Functional Design
Wiring & Harnessing Design
System Decomposition
Repo
CAESAR
Workbench
EFSE
System Decomposition
Electrical Functional Design
Electrical
Functional Design
Adapter
Component List
Function List
Resource Reports
System
Block Diagram
Electric Schematics
AdapterAdapterRepo OML
Workbench
EFSE Vocabulary
17. • Currently, we have one multitenant deployment of CAESAR at JPL
– However, we can create separate deployments to large projects if needed
• Currently, the development team provides operational support
– However, we plan to train a separate Ops team in the future
17
CAESAR deployment and operation
Deployment
Mars
Sample Return
18. 18
CAESAR@JPL
Engineering Development Office
Program Management Office
Integrated Model Centric Engineering
R&D Program
manages
supports
Leads
Software Architect
Engineering and Science
Directorate 3x
Systems Engineering & Formulation
Division 31
hosts sponsors
develops
Mars
Sample Return
……
19. 19
CAESAR R&D roadmap
• Carried out initial product systems engineering
• Developed POC: mass management
• Developed minimal viable platform (MVP)
• Developed first application: Electrical Flight System Eng. *
• Rolled out first deployment
• Onboarded the EUROPA project
• Extending platform capabilities
• Developing the next set of applications*
• Mass management
• Power management
• Behavior specification
• Improving DevOps support
• Onboarding PSYCHE and MSR projects
• ...
FY17
FY18
FY19
FY20
* Our methodology is to develop applications in partnership with:
• Subject matter experts (practice owners)
• Engaged projects
20. 20
Open CAESAR Initiative
Open
MBSE Vendors
MBSE SMEsMBSE Users
MBSE Researchers leads
ContributesContributes
• Open sourcing CAEDSAR on GitHub.com (https://open-caesar.github.io/ )
– Apache 2.0 license
– A repository is created for each separately released component
– A dev team is assigned to each repository
– Work packages are defined as GiHub Projects
21. • Information representation
– OML language definition and tooling
• Information architecture
– Vocabularies for SE disciplines / applications
• Information authoring
– Authoring tools and their adapter interfaces
• Information integration
– Infrastructure for integrating / synchronizing data sources
• Information analysis
– Analysis tools and their adapter interfaces
• Information reporting
– Reporting tools and their adapter interfaces
• Information configuration
– Infrastructure for variability, change proposal, provenance
• Example projects
– Case study projects to demonstrate ideas
21
Open CAESAR possible contributions
22. • We plan to create an Open CAESAR consortium
– The vision is to have the technology widely infused across the industry
– The mission is to collaborate with partners to realize the technology
• Why should you join?
– Users: collaborate closely to address shared MBSE challenges in practice
– Vendors: build better integration for your tools and technologies
– SMEs: influence the extensibility and customizability of the platform
– Researchers: access industrial case studies for your research
• How do you join?
– Send a statement of interest to collaborate from your team
– Present your R&D roadmap that intersects with Open CAESAR’s
22
Open CAESAR consortium
24. 24
JPL Systems Engineering Domains
Project System
Flight System
Project
System Engineering
Flight
System Engineering
Mission System
Mission Operations
Systems Engineering
Subsystem X Subsystem Y
Spacecraft Bus System
Spacecraft
Systems Engineering
Instrument System
Instrument
Systems Engineering
Subsystem X Subsystem Y Subsystem X Subsystem Y
Program:
Level 1
Project:
Level 2
System:
Level 3
Subsystem:
Level 4
25. 25
JPL 10 Systems Engineering Functions (Disciplines)
Define
architecture
Specify
requirements
Characterize and
analyze design
Manage technical resources
and performance
Define
interfaces
Perform verification
and validation
Conduct
reviews
Manage and
control change
Manage
risk
Manage
tasks
26. 26
JPL Flight Systems Engineering Applications
Electrical Systems &
Signals
• Compositional System
Design Description Capture
• System Block Diagram
• Function Lists, Net Lists
• Electrical Flight Systems
Engineering
• Circuit Data Sheets
Functional and
Behavioral Design
• Scenario Definition, Planning
and Analysis
• Fault Protection Monitors and
Responses
• Functional Description
Document Generation
• Specification of FSW
behavioral design
• Power scenario analysis
• Data scenario analysis
Physical & Mechanical
Composition
• Compositional System
Design Description Capture
• Master Ref. Des. list
reconciled with drawing tree
• Mass Management Process /
MEL
• Mass Properties
Management
• Mapping Assembly
aggregations vs. Subsystem
Aggregations
27. 27
OML example
Rover Navigation
∃ Performs
Component Function
Performs
Rover_A Navigation_A
r: Rover_A n: Navigation_A
∃ Performs
p:Performs
Mission
Terminology
Project
Design
Terminology
Project
Scenario
Description
open terminology https://flightsystem {
extends <https://mission>
concept Rover {
extends mission:Component
restrictsSome mission:Performs to Navigation
}
concept Navigation {
extends mission:Function
}
scalarDataProperty maxSpeed {
domain Navigation
range XMLSchema:decimal
}
scalarDataProperty speed {
domain Navigation
range XMLSchema:decimal
}
}
maxSpeed : decimal
speed : decimal
maxSpeed = 200.0
speed = 50.0
Flight System
Terminology
*0..1
closed description <https://project/scenario> {
extends <https:///project/design>
conceptInstance r : design:Rover_A
conceptInstance n : design:Navigation_A {
vzlueOf flightsystem:speed is 50.0
}
relationInstance p : mission:Performs {
from r
to n
}
}
closed terminology <https:/project/design> {
extends <https://flightsystem>
concept Rover_A {
extends flightsystem:Rover
restricsSome mission:Performs to Navigation_A
}
concept Navigation_A {
extends flightsystem:Navigation
restricts flightsystem:maxSpeed to 200.0
}
}
open terminology https://mission {
concept Component
concept Function
relation Performs {
from Component
to Function
inverseFunctional
}
}
34. • OML Workbench
– Develop OML v2 as a language server and support new IDEs (Theia, Gitpod)
• CAESAR Workbench
– Improve collaboration support
– Improve validation support
– Improve authoring viewpoints
• CAESAR Server
– Refactor into micro services architecture (Lagom, Kafka, Event Sourcing, etc.)
– Support user authorization (roles)
– Orchestrate deployment with Cubernates
– Stand up three deployments on AWS: dev, staging, and op
• CAESAR Client
– Improve integration perspective
– Implement configuration perspective
– Support user-role based UI
• Tool Adapters
– Support document generation (bikeshed)
– Support diagram generation (SIFT / TSP)
– Support report generation (Jupiter Notebooks)
34
CAESAR platform R&D plan for FY19
36. OML IDE
36
CAESAR SysML adapter
CAESAR Server
SysML
Model
Adapter
DSL
Vocabulary
Embedding in
SysML
DSL
Model
DSL
Profile or Library
Rover Navigation
∃ Performs
Component Function
Performs
maxSpeed : decimal
speed : decimal
«stereotype»
Rover
«stereotype»
Navigation
«stereotype»
Component
«stereotype»
Function
maxSpeed : decimal
speed : decimal
«stereotype»
SysML::Block
«metaclass»
UML::Dependency
Profile Embedding
«stereotype»
Performs
37. OML IDE
37
CAESAR vs. SysML v2
CAESAR Server
SysML 1.x
Model
AdapterAdapter
SysML 2.x
Model
v1.x
v2.x
DSL
Vocabulary
Em
bedded
in
SysM
L1.x
Em
bedded
in
SysM
L
2.x
Hopefully cleaner
mapping
DSL
Model
DSL
Profile
DSL
Profile
39. 39
CAESAR vs. OpenMBEE
Model Management System
(MMS)
View Editor
Model Development Kit
(MDK)
Other SE Tools
Model Development Kit
(MDK)
CAESAR
Server
Adapter
OpenMBEE
CRUD CRUD
42. • Basic tooling:
– OML Abstract syntax, Java API, XMI interchange format (EMF)
– OML Textual syntax / language server (Xtext)
– OML Graphical syntax (Sprotty)
– OML Semantics by mapping to OWL (Jena)
• Other APIs:
– OML Scala functional API
– OML Java script API
– OML REST API
• Other interchange formats:
– OML JSON format
– OML Parquet format
– OML Zip format
42
CAESAR: information representation work packages
43. • Foundation vocabularies:
– Vocabulary for architecture description
– Vocabulary for architecture integration
– Vocabulary for diagram representation
• SE discipline vocabularies:
– Vocabulary for requirements
– Vocabulary for use cases
– Vocabulary for system structure
– Vocabulary for system behavior
– Vocabulary for V&V
– Vocabulary for I&T
• SE application vocabularies:
– Vocabularies for different application domains (aerospace, automotive, etc.)
43
CAESAR: information architecture work packages
44. • OML IDEs:
– OML IDE support in Eclipse (textual editor, graphical viewer, EMF frameworks)
– OML IDE support in Theia (textual editor, graphical viewer, Gitpod integration)
– OML IDE support in VS Code (textual editor)
• EMF-based tools:
– New EMF-based tool for existing OML vocabulary
– New OML vocabulary for an existing EMF-based tool
– Generic OML adapter CLI based on OML-EMF vocabulary mapping
• UML-based tools:
– New UML-based tool for existing OML vocabulary
– New OML vocabulary for an existing UML-based tool
– Generic OML adapter CLI based on OML-UML vocabulary mapping
• Other tools and technologies:
– Adapt to SE tools (Requirements, Testing, etc.)
– Incorporate emerging tools (VR/AR)
– Integrate smart (AI) digital assistants to facilitate authoring
44
CAESAR: information authoring work packages
45. • Continuous integration and delivery:
– Vocabulary for describing a model integration workflow
– Service to run a model integration workflow
– Service to publish the results of a model integration flow
• Proposing change deltas to integrated SE tools:
– Way to represent change delta in OML
– Framework to propose a change delta in OML
– Framework to apply the change delta in a given tool
45
CAESAR: information integration work packages
46. • Analysis on OML representation directly:
– Programmatic query API for OML
• Analysis using a triple store:
– Way to publish OML ontologies into a triple store
– SPARQL endpoint for OML
– Way to reason on OML with a DL reasoner
– Higher level query language for OML
• Analysis using relational database:
– Way to publish OML ontologies into a relational database
– SQL endpoint for OML
• Analysis using other analysis tools:
– Framework for descriptive, predictive, prescriptive analytics
– Framework for apply execution semantics
– Framework to perform co-simulation
46
CAESAR: information analysis work packages
47. • Ontology visualization on the web:
– Web-based widgets for visualizing OML ontologies
• Ontology reporting tools:
– Interfaces for OML ontologies in various reporting tools
– Way for reports to display change deltas
– Way to report on trends in the evolution history
• Reporting dashboards:
– Way to organize reports to make it easy to browse/search
– Way to review and comment OML ontologies
– Way to approve changes to OML ontologies
– Way to subscribe to changes in reports
• Interactive Reporting tools
– Tool to browse the contents of the OML ontologies
– Tool to assess impact of change to OML ontologies
– Tool to perform text search on OML ontologies
– Tool to integrate with smart digital assistant
47
CAESAR: information reporting work packages
48. • Configuration management of ontologies:
– Way to manage OML ontologies in a SCM repository
– Way to compare and merge ontologies in different repository configurations
– Way to propose changes and doing pull requests using configurations
48
CAESAR: information configuration work packages