Comment concevoir une base de données SIG à partir de zéro ? (2024)

Según mi experiencia, la definición del propósito de la base de datos SIG es algo fundamental y que ha de estar muy estudiado y definido previamente. Hemos de conocer qué respuestas se quieren obtener del sistema para alimentarlo de forma idónea con datos adecuados y precisos; también se ha de prestar especial atención a quién está dirigido el sistema y conocer sus requisitos es básico para que su utilidad sea óptima. Todas estas preguntas han de estar muy claras antes de empezar a trabajar para no crear sistemas que sean redundantes, que no respondan a nuestras cuestiones y que por lo tanto, no cumplan nuestros objetivos

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Having a clear idea of why we are creating the geodatabase is very essential. This will help us define its schema and data model. Be sure to check for online resources and find similar ideas to check how other people are using their databases to identify their problems and how they are addressing it. It will help in streamlining our process and minimize the mistakes from the very beginning.

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5. Create the database schema: Design the tables, fields, and relationships based on your data model. Define spatial data types and indexes for efficient spatial querying.6. Import or create data: Populate your database with existing data by importing shapefiles, CSV files, or other formats. You can also create new data using GIS software.7. Establish data quality controls: Implement measures to ensure data accuracy, consistency, and completeness. Perform data validation and error-checking regularly.8. Set up data access and security: Define user roles and permissions to control access to the database. Implement backup and recovery procedures to safeguard your data.

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One can benefit from a pre set data model, such as PODS Data Model, Arc Hydro Data Model, UPDM and others created by users world wide.

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Before diving into the various types of data models (vector, raster, object-oriented, etc.), it's essential to clarify the requirements. This not only benefits others but also enhances personal understanding. To achieve this, concentrate on defining at least one of the pre-data models – conceptual, logical, or physical, which will be based on requirement analysis.

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Choosing a database that integrates with other business systems natively can be extremely valuable. An example would be using SQL Server so you can use linked servers to query across other databases being used by other business systems. Do NOT create another data silo, like most business systems often do. GIS is often a value added service and therefore the return on investing in such a platform is the ability to integrate and visual data across systems into a cohesive operational platform. Using free databases like PostgreSQL can offer scalability without licensing but that is only a worthwhile RDBMS if you have the skills to support such a choice. Non-relational databases offer little value in a true Enterprise GIS deployment model.

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Certainly! The choice between open-source and proprietary software is influenced by budget constraints, required functionality, and scalability. For instance, developing a webGIS application with extensive data demands requires a database with robust GIS functionalities that seamlessly integrates with GIS-middleware servers. Understanding budget limitations, functional requirements, and future scalability drives the strategic selection of software for optimal outcomes.

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In the context of budget and research output, it is necessary to first consider the type software to explore. For instance, early career researchers across the globe are eager to undertake proper scientific research, however, the available budget makes that impossible. In this light, one has to choose between open source which is free or to use crack software which has wide range of shortcomings.

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Now you're speaking my language. I love all things Survey123, and building geodatabases in Survey123 Connect makes related tables and domains a breeze. Seven years ago, when I was in school, I could either build my tables the hard way or in Survey123 Connect, and I'm a spreadsheet girl, so Excel felt like home to me. LIFE IS EASIER when you have fun.Live IT or Loath IT!

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Certainement je stocke les données de types vectoriel dans des tables de format .shp avec les extensions accompagnatrices. Maintenant, si j'extrais des données dans un Raster ou je convertis un Raster en Vecteur, je je stoke également ces donnés dans des tables de types .shp. toutes ces donnes auront leurs attributs que l'on peut retrouver dans les tables attributaires de chaque entité.

As GIS practioners, we often store more data in our schemas than we should. It is always wise to remember to use data from the authoritive system rather than pull it in for convienance. Views and query layers help us do this. The problem with views and query layers is performance. This is where ETL, and other processes can save us the time and effort, again using those schemas to act as gate keepers.As you go through the workflow building process, remember to ask yourself if this step is the point of no return. If it is, what is the fall back plan if the data does not come over correctly. When you can answer that question, you know you have arrived at a decent solution for your situation.

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Going through iterations of the various data entry and queries help a lot. Involve other people, let them test, populate and interrogate your database before deployment as it’s incredible what people can come up with in term of finding bugs and dead-end from their own point view. We develop the UI/UX of the database but validating with actual users makes a huge difference, especially to find unforeseen gaps during the first steps of design.

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Designing a GIS database involves steps like understanding data needs, creating models, selecting database software, implementing the design, setting up maintenance procedures, testing, documenting, training users, and ensuring continuous improvement to adapt to evolving needs and technology.

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The work presentation is important as much as the work itself, the documentation is what your client needs and it have great commercial value, also to keep it updated and secure is the biggest advertisem*nt for you and will keep your clients flooding you with work. Your design will make this part easier or harder for you, so it shall considered from the beginning and how the client will read it.

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Designing a GIS database involves steps like understanding data needs, creating models, selecting database software, implementing the design, setting up maintenance procedures, testing, documenting, training users, and ensuring continuous improvement to adapt to evolving needs and technology.

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Designing a GIS database involves steps like understanding data needs, creating models, selecting database software, implementing the design, setting up maintenance procedures, testing, documenting, training users, and ensuring continuous improvement to adapt to evolving needs and technology.

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A crucial yet often overlooked factor is data lineage tracking. Knowing where your data comes from, how it's transformed, and its usage is vital. Without tracking data lineage, you risk integrating outdated or inaccurate data, leading to flawed analyses and decisions. Proper lineage tracking ensures transparency, data quality, and accountability, providing confidence in your GIS data's integrity and reliability. Neglecting this can result in costly errors and undermine the entire GIS system's value.

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