DOCSLIB.ORG

DCSA Information Model 3.0

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text

Load more

DCSA Information Model 3.0 December 2020 Table of contents Version history __________________________________________________ 8 1 Introduction __________________________________________________ 9 1.1 Preface ______________________________________________________ 9 1.2 Purpose ______________________________________________________ 9 1.3 Overview _____________________________________________________ 10 1.4 Conformance __________________________________________________ 10 1.5 Supporting publications ___________________________________________ 10 2 DCSA Information Model 3.0 ________________________________________ 13 2.1 Introduction ___________________________________________________ 13 2.2 Selected data modelling terms defined _________________________________ 14 2.3 The DCSA Information Model data types and formats ________________________ 15 2.3.1 Attribute naming conventions ____________________________________ 16 3 Logical Data Model ____________________________________________ 18 4 Logical Data Model usage ________________________________________ 20 4.1 Track and trace (T&T) ____________________________________________ 20 4.2 Operational vessel schedules (OVS) ___________________________________ 21 4.3 eDocumentation _______________________________________________ 23 5 Subject areas in the Logical Data Model _______________________________ 25 5.1 Shipment ____________________________________________________ 26 5.1.1 Shipment reference data _______________________________________ 31 5.2 Transport Document _____________________________________________ 32 5.2.1 Transport Document reference data ______________________________ 37 5.3 Party _______________________________________________________ 40 5.3.1 Party reference data _________________________________________ 43 5.4 Charges _____________________________________________________ 45 2 DCSA Information Model 3.0 5.5 Equipment ___________________________________________________ 47 5.5.1 Equipment reference data _____________________________________ 49 5.6 Stuffing ______________________________________________________ 50 5.6.1 Stuffing reference data _______________________________________ 55 5.7 Location _____________________________________________________ 57 5.7.1 Location reference data _______________________________________ 62 5.8 Transport ____________________________________________________ 66 5.8.1 Transport reference data ______________________________________ 69 5.9 Events _______________________________________________________ 71 5.9.1 Events reference data ________________________________________ 77 5.10 Vessel Sharing Agreement (VSA) ____________________________________ 80 5.10.1 VSA reference data __________________________________________ 83 5.11 Service ______________________________________________________ 83 5.12 Transport Journey ______________________________________________ 85 6 Appendix ___________________________________________________ 89 Tables Table 1: Supporting publications ___________________________________________ 12 Table 2: Selected data modelling terms ______________________________________ 15 Table 3: Data type overview ______________________________________________ 16 Table 4: Data attribute naming conventions ___________________________________ 17 Table 5: Shipment entity _______________________________________________ 27 Table 6: Booking entity ________________________________________________ 28 Table 7: Requested Equipment entity _______________________________________ 29 Table 8: Service Type entity _____________________________________________ 29 Table 9: Shipment Term entity ___________________________________________ 29 Table 10: References entity ______________________________________________ 30 Table 11: Reference Type entity ___________________________________________ 30 Table 12: Service Type __________________________________________________ 31 Table 13: Shipment Term _______________________________________________ 32 Table 14: Reference Type _______________________________________________ 32 Table 15: Transport Document entity _______________________________________ 34 Table 16: Document version entity _________________________________________ 35 3 DCSA Information Model 3.0 Table 17: Shipping Instruction entity ________________________________________ 36 Table 18: EBL Endorsement Chain entity _____________________________________ 36 Table 19: Transport Document Carrier Clauses entity ____________________________ 37 Table 20: Carrier Clauses entity __________________________________________ 37 Table 21: Transport Document Type entity ____________________________________ 37 Table 22: Transport Document Type ________________________________________ 38 Table 23: Transport Document version reference data entity _______________________ 39 Table 24: Party entity __________________________________________________ 41 Table 25: Document Party entity __________________________________________ 42 Table 26: Carrier entity ________________________________________________ 42 Table 27: Party Function entity ___________________________________________ 43 Table 28: Carrier, examples _____________________________________________ 44 Table 29: Party Function, examples ________________________________________ 45 Table 30: Charges entity _______________________________________________ 46 Table 31: Equipment entity ______________________________________________ 48 Table 32: ISO Equipment Code entity _______________________________________ 49 Table 33: ISO Equipment Code, examples ____________________________________ 50 Table 34: Shipment Equipment entity ________________________________________ 51 Table 35: Active Reefer Settings entity ______________________________________ 52 Table 36: Cargo Item entity _____________________________________________ 53 Table 37: Cargo line Item entity ___________________________________________ 53 Table 38: HS Code entity _______________________________________________ 54 Table 39: Seal entity __________________________________________________ 54 Table 40: Seal Source entity _____________________________________________ 55 Table 41: Seal Type entity _______________________________________________ 55 Table 42: Package Code entity ___________________________________________ 55 Table 43: Seal Source _________________________________________________ 56 Table 44: Seal Type ___________________________________________________ 56 Table 45: HS Code, example _____________________________________________ 57 Table 46: Location entity _______________________________________________ 59 Table 47: Shipment Location entity ________________________________________ 59 Table 48: Shipment Location Type entity _____________________________________ 59 Table 49: Country entity _______________________________________________ 60 4 DCSA Information Model 3.0 Table 50: UN Location entity _____________________________________________ 60 Table 51: Facility entity __________________________________________________ 61 Table 52: Facility Type entity _____________________________________________ 62 Table 53: Country, example _____________________________________________ 63 Table 54: UN Location, example __________________________________________ 63 Table 55: Facility ____________________________________________________ 64 Table 56: Facility Type _________________________________________________ 65 Table 57: Shipment Location Type _________________________________________ 66 Table 58: Mode of Transport entity ________________________________________ 67 Table 59: Transport entity ______________________________________________ 68 Table 60: Vessel entity _________________________________________________ 69 Table 61: Shipment Transport entity ________________________________________ 69 Table 62: Mode of Transport ______________________________________________ 71 Table 63: Event Classifier entity ___________________________________________ 72 Table 64: Empty Indicator entity __________________________________________ 73 Table 65: Shipment Information Type entity __________________________________ 73 Table 66: Shipment Event entity __________________________________________ 73 Table 67: Equipment Event Type entity ______________________________________ 74 Table 68: Transport Event Type entity _______________________________________ 74 Table 69: Shipment Event entity __________________________________________ 75 Table 70: Equipment Event entity __________________________________________ 76 Table 71: Transport Event entity ___________________________________________ 77 Table 72: SMDG Delay Reason entity _______________________________________ 77 Table 73: Event Classifier _______________________________________________ 77 Table 74: Delay Reason Codes ___________________________________________ 79 Table 75: Empty Indicator ______________________________________________ 79 Table 76: Equipment Event Type codes ______________________________________ 79 Table 77: Transport Event Type ___________________________________________ 80 Table 78: Shipment Information Type _______________________________________ 80 Table 79: Vessel Sharing Agreement entity ____________________________________ 81 Table 80: Vessel Sharing Agreement Type entity _______________________________ 82 Table 81: Vessel Sharing Agreement Partner entity ______________________________ 82 Table 82: Tradelane entity ______________________________________________ 83 5 DCSA Information Model 3.0 Table 83: Vessel Sharing Agreement Type ____________________________________ 83 Table 84: Service entity
Recommended publications
  • Arcgis Marine Data Model Reference

    Arcgis Marine Data Model Reference

    ArcGIS Marine Data Model Reference ArcGIS Marine Data Model (June 2003) This document provides an Dawn J. Wright, Oregon State U. overview of the ArcGIS Marine Patrick N. Halpin, Duke U. Data Model. This model focuses on Michael Blongewicz, DHI important features of the ocean realm, both natural and manmade, Steve Grisé, ESRI Redlands with a view towards the many Joe Breman, ESRI Redlands applications of marine GIS data. ArcGIS Data Models TABLE OF CONTENTS Acknowledgements ................................................................................................................... 4 Introduction ............................................................................................................................... 5 Why a Marine Data Model?.................................................................................................... 6 Intended Audience and Scope of the Model............................................................................ 8 The Process of Building a Data Model ..................................................................................... 10 Final Data Model Content, Purpose and Use........................................................................ 14 Data Model Description ........................................................................................................... 16 Overview ............................................................................................................................. 16 Conceptual Framework....................................................................................................
  • PML, an Object Oriented Process Modelling Language

    PML, an Object Oriented Process Modelling Language

    PML, an Object Oriented Process Modeling Language Prof. Dr.-Ing. Reiner Anderl 1, and Dipl.-Ing. Jochen Raßler 2 1 Prof. Dr.-Ing. Reiner Anderl, Germany, [email protected] 2 Dipl.-Ing. Jochen Raßler, Germany, [email protected] Abstract: Processes are very important for the success within many business fields. They define the proper application of methods, technologies, tools and company structures in order to reach business goals. Important processes to be defined are manufacturing processes or product development processes for example to guarantee the company’s success. Over the last decades many process modeling languages have been developed to cover the needs of process modeling. Those modeling languages have several limitations, mainly they are still procedural and didn’t follow the paradigm change to object oriented modeling and thus often lead to process models, which are difficult to maintain. In previous papers we have introduced PML, Process Modeling Language, and shown it’s usage in process modeling. PML is derived from UML and hence fully object oriented and uses modern modeling techniques. It is based on process class diagrams that describe methods and resources for process modeling. In this paper the modeling language is described in more detail and new language elements will be introduced to develop the language to a generic usable process modeling language. Keywords: process modeling language, PML, UML 1. Introduction As the tendency of enterprises to collaborate growths steadily, industry faces new challenges managing business processes, product development processes, manufacturing processes and much more. Furthermore, discipline spanning product development processes are increasing, e.
  • A Model-To-Model Transformation of a Generic Relational Database Schema Into a Form Type Data Model

    A Model-To-Model Transformation of a Generic Relational Database Schema Into a Form Type Data Model

    Proceedings of the Federated Conference on Computer Science DOI: 10.15439/2016F408 and Information Systems pp. 1577–1580 ACSIS, Vol. 8. ISSN 2300-5963 A Model-to-Model Transformation of a Generic Relational Database Schema into a Form Type Data Model Sonja Ristić, Slavica Kordić, Milan Čeliković, Vladimir Dimitrieski, Ivan Luković University of Novi Sad, Faculty of Technical Sciences, Trg D. Obradovića 6, 21000 Novi Sad, Serbia Email: {sdristic, slavica, milancel, dimitrieski, ivan}@uns.ac.rs ฀ engineering and review different database meta-models Abstract—An important phase of a data-oriented software (MM) that are used in the database reengineering process system reengineering is a database reengineering process and, applied in IIS*Studio. In [5] we propose an MD approach to in particular, its subprocess – a database reverse engineering data structure conceptualization phase of database reverse process. In this paper we present one of the model-to-model engineering process that is conducted through a chain of transformations from a chain of transformations aimed at transformation of a generic relational database schema into a M2M transformations. In this paper we present the final step form type data model. The transformation is a step of the data of the conceptualization phasethe M2M transformation of structure conceptualization phase of a model-driven database a generic relational database schema into a form type model. reverse engineering process that is implemented in IIS*Studio The form type concept and the IIS*Studio architecture are development environment. given in Section 2. Classifications of form types and relation schemes are described in Section 3. The transformation of a I.
  • Metamodeling the Enhanced Entity-Relationship Model

    Metamodeling the Enhanced Entity-Relationship Model

    Metamodeling the Enhanced Entity-Relationship Model Robson N. Fidalgo1, Edson Alves1, Sergio España2, Jaelson Castro1, Oscar Pastor2 1 Center for Informatics, Federal University of Pernambuco, Recife(PE), Brazil {rdnf, eas4, jbc}@cin.ufpe.br 2 Centro de Investigación ProS, Universitat Politècnica de València, València, España {sergio.espana,opastor}@pros.upv.es Abstract. A metamodel provides an abstract syntax to distinguish between valid and invalid models. That is, a metamodel is as useful for a modeling language as a grammar is for a programming language. In this context, although the Enhanced Entity-Relationship (EER) Model is the ”de facto” standard modeling language for database conceptual design, to the best of our knowledge, there are only two proposals of EER metamodels, which do not provide a full support to Chen’s notation. Furthermore, neither a discussion about the engineering used for specifying these metamodels is presented nor a comparative analysis among them is made. With the aim at overcoming these drawbacks, we show a detailed and practical view of how to formalize the EER Model by means of a metamodel that (i) covers all elements of the Chen’s notation, (ii) defines well-formedness rules needed for creating syntactically correct EER schemas, and (iii) can be used as a starting point to create Computer Aided Software Engineering (CASE) tools for EER modeling, interchange metadata among these tools, perform automatic SQL/DDL code generation, and/or extend (or reuse part of) the EER Model. In order to show the feasibility, expressiveness, and usefulness of our metamodel (named EERMM), we have developed a CASE tool (named EERCASE), which has been tested with a practical example that covers all EER constructors, confirming that our metamodel is feasible, useful, more expressive than related ones and correctly defined.
  • Extending and Evaluating the Model-Based Product Definition

    Extending and Evaluating the Model-Based Product Definition

    NIST GCR 18-015 Extending and Evaluating the Model-based Product Definition Nathan W. Hartman Jesse Zahner Purdue University This publication is available free of charge from: https://doi.org/10.6028/NIST.GCR.18-015 NIST GCR 18-015 Extending and Evaluating the Model-based Product Definition Prepared for Thomas D. Hedberg, Jr. Allison Barnard Feeney U.S. Department of Commerce Engineering Laboratory National Institute of Standards and Technology Gaithersburg, MD 20899-8260 By Nathan W. Hartman Jesse Zahner PLM Center of Excellence Purdue University This publication is available free of charge from: https://doi.org/10.6028/NIST.GCR.18-015 December 2017 U.S. Department of Commerce Wilbur L. Ross, Jr., Secretary National Institute of Standards and Technology Walter Copan, NIST Director and Undersecretary of Commerce for Standards and Technology Disclaimer Any opinions, findings, conclusions, or recommendations expressed in this publication do not necessarily reflect the views of the National Institute of Standards and Technology (NIST). Additionally, neither NIST nor any of its employees make any warranty, expressed or implied, nor assume any legal liability or responsibility for the accuracy, completeness, or usefulness of any information, product, or process included in this publication. The report was prepared under cooperative agreement 70NANB15H311 between the National Institute of Standards and Technology and Purdue University. The statements and conclusions contained in this report are those of the authors and do not imply recommendations or endorsements by the National Institute of Standards and Technology. Certain commercial systems are identified in this report. Such identification does not imply recommendation or endorsement by the National Institute of Standards and Technology.
  • Enterprise Data Modeling Using the Entity-Relationship Model

    Enterprise Data Modeling Using the Entity-Relationship Model

    Database Systems Session 3 – Main Theme Enterprise Data Modeling Using The Entity/Relationship Model Dr. Jean-Claude Franchitti New York University Computer Science Department Courant Institute of Mathematical Sciences Presentation material partially based on textbook slides Fundamentals of Database Systems (6th Edition) by Ramez Elmasri and Shamkant Navathe Slides copyright © 2011 1 Agenda 11 SessionSession OverviewOverview 22 EnterpriseEnterprise DataData ModelingModeling UsingUsing thethe ERER ModelModel 33 UsingUsing thethe EnhancedEnhanced Entity-RelationshipEntity-Relationship ModelModel 44 CaseCase StudyStudy 55 SummarySummary andand ConclusionConclusion 2 Session Agenda Session Overview Enterprise Data Modeling Using the ER Model Using the Extended ER Model Case Study Summary & Conclusion 3 What is the class about? Course description and syllabus: » http://www.nyu.edu/classes/jcf/CSCI-GA.2433-001 » http://cs.nyu.edu/courses/fall11/CSCI-GA.2433-001/ Textbooks: » Fundamentals of Database Systems (6th Edition) Ramez Elmasri and Shamkant Navathe Addition Wesley ISBN-10: 0-1360-8620-9, ISBN-13: 978-0136086208 6th Edition (04/10) 4 Icons / Metaphors Information Common Realization Knowledge/Competency Pattern Governance Alignment Solution Approach 55 Agenda 11 SessionSession OverviewOverview 22 EnterpriseEnterprise DataData ModelingModeling UsingUsing thethe ERER ModelModel 33 UsingUsing thethe EnhancedEnhanced Entity-RelationshipEntity-Relationship ModelModel 44 CaseCase StudyStudy 55 SummarySummary andand ConclusionConclusion
  • Gis Data Models

    Gis Data Models

    GIS DATA MODELS CONCEPTUAL MODEL OF SPATIAL INFORMATION 1. Introduction GIS does not store a map in any conventional sense, nor it stores a particular image or view of geographic area. Instead, a GIS stores the data from which we can draw a desired view to suit a particular purpose known as geographic data. There are two types of data in GIS; spatial data and non-spatial data (Attribute data). Non-spatial data include information about the features. For example, name of roads, schools, forests etc., population or census data for the region concerned etc. Non-spatial or attribute data is that qualifies the spatial data. It describes some aspects of the spatial data, not specified by its geometry alone. A geographical information system essentially integrates the above two types of data and allows user to derive new data for planning. Spatial models are important in that way in which information is represented affects the type of analysis that can be performed and the type of graphic display that can be performed and the type of analysis that can be obtained. In GIS systems there is a major distinction between what are usually referred to as vector GIS and raster GIS. These two approaches to spatial data processing, often to be found in the same GIS package, reflect two different methods of spatial modeling: the former focusing on discrete objects that are to be described, and the latter concerned primarily with recording what is to be found at a predetermined set of locations that may be grid cells or points.
  • The Layman's Guide to Reading Data Models

    The Layman's Guide to Reading Data Models

    Data Architecture & Engineering Services The Layman’s Guide to Reading Data Models A data model shows a data asset’s structure, including the relationships and constraints that determine how data will be stored and accessed. 1. Common Types of Data Models Conceptual Data Model A conceptual data model defines high-level relationships between real-world entities in a particular domain. Entities are typically depicted in boxes, while lines or arrows map the relationships between entities (as shown in Figure 1). Figure 1: Conceptual Data Model Logical Data Model A logical data model defines how a data model should be implemented, with as much detail as possible, without regard for its physical implementation in a database. Within a logical data model, an entity’s box contains a list of the entity’s attributes. One or more attributes is designated as a primary key, whose value uniquely specifies an instance of that entity. A primary key may be referred to in another entity as a foreign key. In the Figure 2 example, each Employee works for only one Employer. Each Employer may have zero or more Employees. This is indicated via the model’s line notation (refer to the Describing Relationships section). Figure 2: Logical Data Model Last Updated: 03/30/2021 OIT|EADG|DEA|DAES 1 The Layman’s Guide to Reading Data Models Physical Data Model A physical data model describes the implementation of a data model in a database (as shown in Figure 3). Entities are described as tables, Attributes are translated to table column, and Each column’s data type is specified.
  • An Object Oriented Shared Data Model for GIS and Distributed Hydrologic Models

    An Object Oriented Shared Data Model for GIS and Distributed Hydrologic Models

    An Object Oriented Shared Data Model for GIS and Distributed Hydrologic Models M. Kumar and C. Duffy International Journal of Geographical Information Science, IJGIS-2008-0131 Accepted for publication Sep. 2008 Abstract Distributed physical models for the space-time distribution of water, energy, vegetation, and mass flow require new strategies for data representation, model domain decomposition, a-priori parameterization, and visualization. The Geographic Information System (GIS) has been traditionally used to accomplish these data management functionalities in hydrologic applications. However, the interaction between the data management tools and the physical model are often loosely integrated and nondynamic. This leads to several issues addressed in this paper: a) The data types and formats for the physical model system and the distributed data or parameters may be different, with significant data preprocessing required before they can be shared. b) The management tools may not be accessible or shared by the GIS and physical model. c) The individual systems may be operating-system dependent or are driven by proprietary data structures. The impediment to seamless data flow between the two software components has the effect of increasing the model setup time and analysis time of model output results, and also makes it restrictive to perform sophisticated numerical modeling procedures (sensitivity analysis, real time forecasting, etc.) that utilize extensive GIS data. These limitations can be offset to a large degree by developing an integrated software component that shares data between the (hydrologic) model and the GIS modules. We contend that the pre-requisite for the development of such an integrated software component is a “shared data-model” that is designed using an Object Oriented Strategy.
  • Metamodelling for MDA

    Metamodelling for MDA

    Metamodelling for MDA First International Workshop York, UK, November 2003 Proceedings Edited by Andy Evans Paul Sammut James S. Willans Table of Contents Preface ........................................................ 4 Principles Calling a Spade a Spade in the MDA Infrastructure ................... 9 Colin Atkinson and Thomas K¨uhne Do MDA Transformations Preserve Meaning? An investigation into preservingsemantics ........................................... 13 Anneke Kleppe and Jos Warmer MDA components: Challenges and Opportunities ..................... 23 Jean B´ezivin, S´ebastien G´erard, Pierre-Alain Muller and Laurent Rioux SafetyChallengesforModelDrivenDevelopment ..................... 42 N. Audsley, P. M. Conmy, S. K. Crook-Dawkins and R. Hawkins Invited talk: UML2 - a language for MDA (putting the U, M and L intoUML)?................................................... 61 Alan Moore Languages and Applications Using an MDA approach to model traceability within a modelling framework .................................................... 62 John Dalton, Peter W Norman, Steve Whittle, and T Eshan Rajabally Services integration by models annotation and transformation .......... 77 Olivier Nano and Mireille Blay-Fornarino 1 A Metamodel of Prototypical Instances .............................. 93 Andy Evans, Girish Maskeri, Alan Moore Paul Sammut and James S. Willans Metamodelling of Transaction Configurations ......................... 106 StenLoecherandHeinrichHussmann Invitedtalk:MarketingtheMDAToolChain......................... 109 Stephen
  • Patterns: Model-Driven Development Using IBM Rational Software Architect

    Patterns: Model-Driven Development Using IBM Rational Software Architect

    Front cover Patterns: Model-Driven Development Using IBM Rational Software Architect Learn how to automate pattern-driven development Build a model-driven development framework Follow a service-oriented architecture case study Peter Swithinbank Mandy Chessell Tracy Gardner Catherine Griffin Jessica Man Helen Wylie Larry Yusuf ibm.com/redbooks International Technical Support Organization Patterns: Model-Driven Development Using IBM Rational Software Architect December 2005 SG24-7105-00 Note: Before using this information and the product it supports, read the information in “Notices” on page ix. First Edition (December 2005) This edition applies to Version 6.0.0.1 of Rational Software Architect (product number 5724-I70). © Copyright International Business Machines Corporation 2005. All rights reserved. Note to U.S. Government Users Restricted Rights -- Use, duplication or disclosure restricted by GSA ADP Schedule Contract with IBM Corp. Contents Notices . ix Trademarks . x Preface . xi For solution architects . xi For project planners or project managers . xii For those working on a project that uses model-driven development . xii How this book is organized . xiii The team that wrote this redbook. xiv Become a published author . xv Comments welcome. xvi Part 1. Approach . 1 Chapter 1. Overview and concepts of model-driven development. 3 1.1 Current business environment and drivers . 4 1.2 A model-driven approach to software development . 5 1.2.1 Models as sketches and blueprints . 6 1.2.2 Precise models enable automation . 6 1.2.3 The role of patterns in model-driven development . 7 1.2.4 Not just code . 7 1.3 Benefits of model-driven development .
  • Aircraft Systems Modeling

    Aircraft Systems Modeling

    Aircraft Systems Modeling Model Based Systems Engineering in Avionics Design and Aircraft Simulation ii Linköping Studies in Science and Technology Thesis No. 1394 Aircraft Systems Modeling Model Based Systems Engineering in Avionics Design and Aircraft Simulation Henric Andersson Department of Management and Engineering Division of Machine Design Linköpings universitet SE-581 83 Linköping, Sweden Linköping 2009 iii Aircraft Systems Modeling Model Based Systems Engineering in Avionics Design and Aircraft Simulation LIU-TEK-LIC-2009:2 ISBN 978-91-7393-692-7 ISSN 0280-7971 Copyright © March 2009 by Henric Andersson [email protected] www.iei.liu.se/machine Division of Machine Design Department of Management and Engineering Linköpings universitet SE-581 83 Linköping, Sweden Printed in Sweden by LiU-Tryck, Linköping, 2009 iv Abstract AIRCRAFT DEVELOPERS, like other development and manufacturing companies, are experiencing increasing complexity in their products and growing competition in the global market. One way to confront the challenges is to make the development process more efficient and to shorten time to market for new products/variants by using design and development methods based on models. Model Based Systems Engineering (MBSE) is introduced to, in a structured way, support engineers with aids and rules in order to engineer systems in a new way. In this thesis, model based strategies for aircraft and avionics development are stud- ied. A background to avionics architectures and in particular Integrated Modular Avion- ics is described. The integrating discipline Systems Engineering, MBSE and applicable standards are also described. A survey on available and emerging modeling techniques and tools, such as Hosted Simulation, is presented and Modeling Domains are defined in order to analyze the engineering environment with all its vital parts to support an MBSE approach.