Programmers always write programs for specific subject areas. For example, accounting software is based on accounting rules, and websites, where you can watch TV shows, are designed around concepts from the TV industry, such as seasons and episodes. The same goes for everything else; booking flights and hotels, finding tours, selling and buying cars, and so on.
Understanding the subject area that you're writing a program for is just as important as knowing how to program. This does not mean you need to know it thoroughly – sometimes the field can be really complicated (for example, accounting or technological production), but a general understanding is still required.
Let's consider Hexlet since you know it a little already. You know the subject matter quite well, though you've hardly thought about it the way we're going to do it now. First of all, to understand it, we need to highlight the key concepts. Learning resources tend to be divided into courses and lessons but there are actually many more ways to sort them. With Hexlet, we also have professions, challenges (practice tasks to do after the course), code reviews, quizzes, course participants (you become a participant when you join the course), and projects. This list could go on and on. You'll probably be surprised, but there are over 200 of these concepts on Hexlet, also known as entities, and they're all defined using code.
The entities have a kind of relationship with each other. For example, the quiz contains/aggregates questions. And each question, in turn, contains the answers. A profession consists of courses, and courses consist of lessons, and lessons consist of theory, quizzes, and practice. These connections have specific names. For example:
- One lesson may only be in one course, but a course contains many lessons. This connection is called “one to many”.
- Many users can take one course, and one user can take many courses. This connection is already called “many to many”.
- A one-to-one relationship is less common. On Hexlet, lessons and exercises are connected in this way.
In reality, it's even more complicated because the same entity can look wholly different from different systems' points of view. A Hexlet user from the accountant's perspective (we do have an accountant!) and from tech support's perspective are two different things.
The description of some area's entities (or domain) in question and the relationships between them is called a domain ontology. The experts in the relevant field have a strong mental model and understanding of such ontology (an accountant knows accounting, a teacher knows education theory). But unlike programmers, they often present it on an intuitive level, informally. In practice, programmers (or business analysts and managers) communicate with customers, who may themselves act as experts and build a formal ontology with them (this constantly occurs in the process of project development and is not isolated to separate design phases). In other words, they single out specific terms and agree on what they mean and how they relate to each other. Then, using the ER-model the programmer creates the necessary data model. The ER model is used in high-level (conceptual) database design. This is the stage at which the beginnings of the architecture of the future application start to appear.
It's rarely possible to say unequivocally what connection exists between the two entities. Sometimes programmers think ahead and immediately build more complex relations, such as m2m rather than o2m, which affects the code complexity. The more complex the relation, the more code and money it takes to create and maintain it. The relations complexity can be ordered as follows (in ascending order): o2o, o2m, m2m. Sometimes programmers make a mistake when choosing a relationship, which indicates a poor understanding of the subject area. Here's an interesting example. Imagine a system that needs to have a user and a passport. Intuitively, there's a one-to-one relationship between these concepts, after all, one user can only have one passport. Right? Not quite; the passport can be changed if it has been lost or expired. In addition, some countries allow you to have several passports at the same time.
On the other hand, the real world is always more complex and way more significant than any model. And the programmer's task is not to create a universal and comprehensive model to cover a given area but to understand the needs of a particular business, choose only the relevant parts of the subject area under consideration, and turn them into code.
Depending on the language resources, the way entities are represented in code can vary. Some have types (using ATDs, interfaces, or classes), others define structures, and others provide no options at all except dictionaries (associative arrays).
Object-oriented programming (OOP) is directly related to the topic at hand. In the next lesson, we'll start exploring different subject areas and building suitable data models, while learning new features of JavaScript in the process.
The topic in question will be most fully explored when we start learning about ORM. For now, the main thing is that you have a general idea of the subject area, entities, and relationships. Don't forget to read the information on the links provided – the more questions you have at this stage, the better.
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For example, accounting software is based on accounting rules, and websites, where you can watch TV shows, are designed around concepts from the TV industry, such as seasons and episodes. The same goes for everything else; booking flights and hotels, finding tours, selling and buying cars, and so on.\n\n\n\nUnderstanding the subject area that you're writing a program for is just as important as knowing how to program. This does not mean you need to know it thoroughly – sometimes the field can be really complicated (for example, accounting or technological production), but a general understanding is still required.\n\nLet's consider Hexlet since you know it a little already. You know the subject matter quite well, though you've hardly thought about it the way we're going to do it now. First of all, to understand it, we need to highlight the key concepts. Learning resources tend to be divided into courses and lessons but there are actually many more ways to sort them. With Hexlet, we also have professions, challenges (practice tasks to do after the course), code reviews, quizzes, course participants (you become a participant when you join the course), and projects. This list could go on and on. You'll probably be surprised, but there are over 200 of these concepts on Hexlet, also known as _entities_, and they're all defined using code.\n\nThe entities have a kind of relationship with each other. For example, the quiz contains/aggregates questions. And each question, in turn, contains the answers. A profession consists of courses, and courses consist of lessons, and lessons consist of theory, quizzes, and practice. These connections have specific names. For example:\n\n- One lesson may only be in one course, but a course contains many lessons. This connection is called “one to many”.\n- Many users can take one course, and one user can take many courses. This connection is already called “many to many”.\n- A one-to-one relationship is less common. On Hexlet, lessons and exercises are connected in this way.\n\n\n\nIn reality, it's even more complicated because the same entity can look wholly different from different systems' points of view. A Hexlet user from the accountant's perspective (we do have an accountant!) and from tech support's perspective are two different things.\n\nThe description of some area's entities (or domain) in question and the relationships between them is called a __domain ontology__. The experts in the relevant field have a strong mental model and understanding of such ontology (an accountant knows accounting, a teacher knows education theory). But unlike programmers, they often present it on an intuitive level, informally. In practice, programmers (or business analysts and managers) communicate with customers, who may themselves act as experts and build a formal ontology with them (this constantly occurs in the process of project development and is not isolated to separate design phases). In other words, they single out specific terms and agree on what they mean and how they relate to each other. Then, using the [ER-model](https://en.wikipedia.org/wiki/Entity%E2%80%93relationship_model) the programmer creates the necessary data model. The ER model is used in high-level (conceptual) database design. This is the stage at which the beginnings of the architecture of the future application start to appear.\n\nIt's rarely possible to say unequivocally what connection exists between the two entities. Sometimes programmers think ahead and immediately build more complex relations, such as m2m rather than o2m, which affects the code complexity. The more complex the relation, the more code and money it takes to create and maintain it. The relations complexity can be ordered as follows (in ascending order): o2o, o2m, m2m. Sometimes programmers make a mistake when choosing a relationship, which indicates a poor understanding of the subject area. Here's an interesting example. Imagine a system that needs to have a user and a passport. Intuitively, there's a one-to-one relationship between these concepts, after all, one user can only have one passport. Right? Not quite; the passport can be changed if it has been lost or expired. In addition, some countries allow you to have several passports at the same time.\n\nOn the other hand, the real world is always more complex and way more significant than any model. And the programmer's task is not to create a universal and comprehensive model to cover a given area but to understand the needs of a particular business, choose only the relevant parts of the subject area under consideration, and turn them into code.\n\nDepending on the language resources, the way entities are represented in code can vary. Some have types (using ATDs, interfaces, or classes), others define structures, and others provide no options at all except dictionaries (associative arrays).\n\nObject-oriented programming (OOP) is directly related to the topic at hand. In the next lesson, we'll start exploring different subject areas and building suitable data models, while learning new features of JavaScript in the process.\n\n\n\nThe topic in question will be most fully explored when we start learning about ORM. For now, the main thing is that you have a general idea of the subject area, entities, and relationships. Don't forget to read the information on the links provided – the more questions you have at this stage, the better.\n"},"lessonMember":null,"courseMember":null,"course":{"start_lesson":{"exercise":null,"units":[{"id":6897,"name":"theory","url":"/courses/js-data-abstraction/lessons/intro/theory_unit"}],"links":[],"ordered_units":[{"id":6897,"name":"theory","url":"/courses/js-data-abstraction/lessons/intro/theory_unit"}],"id":3037,"slug":"intro","state":"approved","name":"About course","course_order":10,"goal":"Learn about the course, its structure, objectives, and goals","self_study":null,"theory_video_provider":null,"theory_video_uid":null,"theory":"Abstraction is the primary way to handle complexity in programming. It allows you to escape the implementation details and focus on the essentials.\n\nA good abstraction example is the array sort function. It doesn't matter how it's implemented; what matters is that it leads to the result we're interested in.\n\nAnother example is higher-order functions, such as `map`, `filter`, and `reduce`, which allow you to process collections without thinking about what goes on under the hood. Collections even don't have to be flat; you can build such functions for any complex structures, such as trees. And due to this abstraction, we can focus on the processing itself rather than the data traversal technicalities.\n\nOn the other hand, the data itself often has a complex structure. Representing a user in an unconventional system may require defining dozens or hundreds of different parameters and the associated data. In situations like this, it's a good idea to hide this structure behind a set of functions, which cover the internal complexity and simplify code support. 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stroke-linecap="round" stroke-linejoin="round" class="tabler-icon tabler-icon-lock "><path d="M5 13a2 2 0 0 1 2 -2h10a2 2 0 0 1 2 2v6a2 2 0 0 1 -2 2h-10a2 2 0 0 1 -2 -2v-6"></path><path d="M11 16a1 1 0 1 0 2 0a1 1 0 0 0 -2 0"></path><path d="M8 11v-4a4 4 0 1 1 8 0v4"></path></svg></div><p style="font-size:var(--mantine-font-size-sm)" class="mantine-focus-auto m_b6d8b162 mantine-Text-root">JS: Building abstractions with data</p></div><h1 style="--title-fw:var(--mantine-h1-font-weight);--title-lh:var(--mantine-h1-line-height);--title-fz:var(--mantine-h1-font-size);margin-bottom:var(--mantine-spacing-xl)" class="m_8a5d1357 mantine-Title-root" data-order="1">Theory: Ontology</h1><script type="application/ld+json">{"@context":"https://schema.org","@type":"LearningResource","name":"Ontology","inLanguage":"en","isPartOf":{"@type":"LearningResource","name":"JS: Building abstractions with data"},"isAccessibleForFree":"False","hasPart":{"@type":"WebPageElement","isAccessibleForFree":"False","cssSelector":".paywalled"}}</script><div class=""><div style="--alert-color:var(--mantine-color-indigo-light-color);margin-bottom:var(--mantine-spacing-lg);font-size:var(--mantine-font-size-lg)" class="m_66836ed3 mantine-Alert-root" id="mantine-_R_remqrdub_" role="alert" aria-describedby="mantine-_R_remqrdub_-body" aria-labelledby="mantine-_R_remqrdub_-title"><div class="m_a5d60502 mantine-Alert-wrapper"><div class="m_667f2a6a mantine-Alert-icon"><svg xmlns="http://www.w3.org/2000/svg" width="24" height="24" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" class="tabler-icon tabler-icon-rocket "><path d="M4 13a8 8 0 0 1 7 7a6 6 0 0 0 3 -5a9 9 0 0 0 6 -8a3 3 0 0 0 -3 -3a9 9 0 0 0 -8 6a6 6 0 0 0 -5 3"></path><path d="M7 14a6 6 0 0 0 -3 6a6 6 0 0 0 6 -3"></path><path d="M14 9a1 1 0 1 0 2 0a1 1 0 1 0 -2 0"></path></svg></div><div class="m_667c2793 mantine-Alert-body"><div class="m_6a03f287 mantine-Alert-title"><span id="mantine-_R_remqrdub_-title" class="m_698f4f23 mantine-Alert-label">Full access to materials</span></div><div id="mantine-_R_remqrdub_-body" class="m_7fa78076 mantine-Alert-message"><div style="--group-gap:var(--mantine-spacing-md);--group-align:center;--group-justify:space-between;--group-wrap:wrap" class="m_4081bf90 mantine-Group-root"><p class="mantine-focus-auto m_b6d8b162 mantine-Text-root">Sign up and get access to this and dozens of other courses</p><a style="--button-height:var(--button-height-xs);--button-padding-x:var(--button-padding-x-xs);--button-fz:var(--mantine-font-size-xs);--button-bg:linear-gradient(45deg, var(--mantine-color-blue-filled) 0%, var(--mantine-color-cyan-filled) 100%);--button-hover:linear-gradient(45deg, var(--mantine-color-blue-filled) 0%, var(--mantine-color-cyan-filled) 100%);--button-color:var(--mantine-color-white);--button-bd:none" class="mantine-focus-auto mantine-active m_77c9d27d mantine-Button-root m_87cf2631 mantine-UnstyledButton-root" data-variant="gradient" data-size="xs" href="/u/new"><span class="m_80f1301b mantine-Button-inner"><span class="m_811560b9 mantine-Button-label">Sign up</span></span></a></div></div></div></div></div><div class="paywalled m_d08caa0 mantine-Typography-root"><p>Programmers always write programs for specific subject areas. For example, accounting software is based on accounting rules, and websites, where you can watch TV shows, are designed around concepts from the TV industry, such as seasons and episodes. The same goes for everything else; booking flights and hotels, finding tours, selling and buying cars, and so on.</p>
<p><img style="--image-object-fit:contain;width:auto" class="m_9e117634 mantine-Image-root" src="/rails/active_storage/blobs/proxy/eyJfcmFpbHMiOnsiZGF0YSI6NzM5OCwicHVyIjoiYmxvYl9pZCJ9fQ==--460a4d73a062f770590de066107556e50b7ac978/domain.png" alt="Domain" loading="lazy"/></p>
<p>Understanding the subject area that you're writing a program for is just as important as knowing how to program. This does not mean you need to know it thoroughly – sometimes the field can be really complicated (for example, accounting or technological production), but a general understanding is still required.</p>
<p>Let's consider Hexlet since you know it a little already. You know the subject matter quite well, though you've hardly thought about it the way we're going to do it now. First of all, to understand it, we need to highlight the key concepts. Learning resources tend to be divided into courses and lessons but there are actually many more ways to sort them. With Hexlet, we also have professions, challenges (practice tasks to do after the course), code reviews, quizzes, course participants (you become a participant when you join the course), and projects. This list could go on and on. You'll probably be surprised, but there are over 200 of these concepts on Hexlet, also known as <em>entities</em>, and they're all defined using code.</p>
<p>The entities have a kind of relationship with each other. For example, the quiz contains/aggregates questions. And each question, in turn, contains the answers. A profession consists of courses, and courses consist of lessons, and lessons consist of theory, quizzes, and practice. These connections have specific names. For example:</p>
<ul>
<li>One lesson may only be in one course, but a course contains many lessons. This connection is called “one to many”.</li>
<li>Many users can take one course, and one user can take many courses. This connection is already called “many to many”.</li>
<li>A one-to-one relationship is less common. On Hexlet, lessons and exercises are connected in this way.</li>
</ul>
<p><img style="--image-object-fit:contain;width:auto" class="m_9e117634 mantine-Image-root" src="/rails/active_storage/blobs/proxy/eyJfcmFpbHMiOnsiZGF0YSI6NzM5OSwicHVyIjoiYmxvYl9pZCJ9fQ==--736dd928fc1f4a2cc7824bbce15f0652a51a9dc8/car-erd.png" alt="ERD" loading="lazy"/></p>
<p>In reality, it's even more complicated because the same entity can look wholly different from different systems' points of view. A Hexlet user from the accountant's perspective (we do have an accountant!) and from tech support's perspective are two different things.</p>
<p>The description of some area's entities (or domain) in question and the relationships between them is called a <strong>domain ontology</strong>. The experts in the relevant field have a strong mental model and understanding of such ontology (an accountant knows accounting, a teacher knows education theory). But unlike programmers, they often present it on an intuitive level, informally. In practice, programmers (or business analysts and managers) communicate with customers, who may themselves act as experts and build a formal ontology with them (this constantly occurs in the process of project development and is not isolated to separate design phases). In other words, they single out specific terms and agree on what they mean and how they relate to each other. Then, using the <a style="text-decoration:underline" class="mantine-focus-auto m_849cf0da m_b6d8b162 mantine-Text-root mantine-Anchor-root" data-underline="hover" href="https://en.wikipedia.org/wiki/Entity%E2%80%93relationship_model" rel="noopener noreferrer" target="_blank">ER-model</a> the programmer creates the necessary data model. The ER model is used in high-level (conceptual) database design. This is the stage at which the beginnings of the architecture of the future application start to appear.</p>
<p>It's rarely possible to say unequivocally what connection exists between the two entities. Sometimes programmers think ahead and immediately build more complex relations, such as m2m rather than o2m, which affects the code complexity. The more complex the relation, the more code and money it takes to create and maintain it. The relations complexity can be ordered as follows (in ascending order): o2o, o2m, m2m. Sometimes programmers make a mistake when choosing a relationship, which indicates a poor understanding of the subject area. Here's an interesting example. Imagine a system that needs to have a user and a passport. Intuitively, there's a one-to-one relationship between these concepts, after all, one user can only have one passport. Right? Not quite; the passport can be changed if it has been lost or expired. In addition, some countries allow you to have several passports at the same time.</p>
<p>On the other hand, the real world is always more complex and way more significant than any model. And the programmer's task is not to create a universal and comprehensive model to cover a given area but to understand the needs of a particular business, choose only the relevant parts of the subject area under consideration, and turn them into code.</p>
<p>Depending on the language resources, the way entities are represented in code can vary. Some have types (using ATDs, interfaces, or classes), others define structures, and others provide no options at all except dictionaries (associative arrays).</p>
<p>Object-oriented programming (OOP) is directly related to the topic at hand. In the next lesson, we'll start exploring different subject areas and building suitable data models, while learning new features of JavaScript in the process.</p>
<p><img style="--image-object-fit:contain;width:auto" class="m_9e117634 mantine-Image-root" src="/rails/active_storage/blobs/proxy/eyJfcmFpbHMiOnsiZGF0YSI6NzQwMCwicHVyIjoiYmxvYl9pZCJ9fQ==--bc79e5fd3cf9bb80c1f1bf461bc6073e6c22caf8/ddd.png" alt="DDD" loading="lazy"/></p>
<p>The topic in question will be most fully explored when we start learning about ORM. For now, the main thing is that you have a general idea of the subject area, entities, and relationships. 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