Thus, event ontology is better suited for modeling business processes as it allows describing not only the data structure but also the logic of actions performed by process participants. It records the history of changes, which is useful for analysis, auditing, and optimization. On the other hand, object ontology is more suitable for creating thesauruses, classifications, and information retrieval systems, where the structuring of knowledge about the subject area is important.

The boldsea technology integrates three architectural solutions for modeling information systems: the subject-event approach, semantic technologies, and the dataflow ideology for algorithm execution.

The subject-event approach (boldsea) can be broadly explained as follows: any activity (the functioning of a complex system involving subjects) can formally be represented as a set of events generated and registered by subjects. It is asserted that any content of activity can be expressed in terms of event systems: relationships between subjects, subjects and resources can be represented as a set of events, an event stream. In boldsea, not only management acts but also all recorded properties of activity elements are written as events, which allows for the unification of data storage and processing.
To unify and standardize the interaction of various software modules and independent applications, a semantic (combining data and metadata) recording format is used: events are created based on models and have semantic content that is independent of software elements or the structure of the data storage. All boldsea events are stored as temporal sequences, enabling the event storage to act as a message broker, ensuring asynchronous interaction between system elements.
Key principles and advantages of boldsea:
1. Unification of description at the lowest level: only events exist, everything else—subjects, objects (resources, documents)—is described as sets of events.
2. Combining metadata and data—the event stream contains complete information about the system (data on objects and subjects, business logic, system structure).
3. Achieving relativity of description—any object exists only for the specified subject and is described through a set of events distinguished by the latter.
4. Formalization of the description level—subjects distinguishing identical objects are assigned to the same level, and the description is consistent at each level.
5. Alignment of descriptions at the highest level: all possible models (structural, functional, etc.) are reduced to a common stream of elementary events.

Boldsea addresses several issues inherent in traditional semantic technologies by offering an event-oriented approach instead of an object-oriented one. Specifically, boldsea solves the following problems:
• Lack of temporality in traditional semantic technologies: Traditional semantic technologies, including Semantic Web standards (RDF/OWL/SPARQL), in their basic implementations lack temporal parameters and are not designed for modeling dynamic systems. In boldsea, all data is recorded as a sequence of events, ensuring its temporality. Events are recorded at the moment of their registration or generation and are not deleted, allowing the entire history of changes to be tracked.
• Need for additional extensions to work with time: Existing Semantic Web solutions require extensions to work with temporal data, making descriptions cumbersome. Boldsea is initially built on event semantics, which eliminates the need for additional extensions.
• Diversity and ambiguity of relationships: In boldsea, the number of relationships is reduced by using the act as the basic semantic primitive, allowing most relationships to be translated into acts.
• Problems with validating generated data: In boldsea, data semantics are validated against models, and trust in data can be controlled by analyzing the status of the actors creating it.
• Lack of consideration for the subjective factor: In boldsea, it is mandatory to record the actor creating the event, allowing for the consideration of different points of view.

Boldsea uses a Dataflow architecture for model execution, which is a key distinction from traditional approaches to business process management. Instead of step-by-step command execution, as in von Neumann architecture, boldsea ensures asynchronous operation execution as data becomes available. This is achieved through the following principles:
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Event-oriented execution: In boldsea, data is represented as semantically defined events rather than abstract values. Model execution occurs not by passing tokens with data from node to node but through recording subject events in storage.
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Model events: The program/model structure is represented as a directed graph, where model events are located at the nodes. Each model event contains conditions for its execution.
•
Asynchronous interaction: The semantic definiteness of events in the graph ensures parallel and asynchronous interaction of multiple independent executable models.
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Execution conditions: The condition for executing a model event is the successful execution of a query to the subject graph, which returns the value of a subject event. The query is initiated by subscribing to new events generated by other model nodes or by actor input.
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Reactive paradigm: Executable action models are implemented in the ideology of dynamic dataflow architecture and the reactive programming paradigm.
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Recording algorithm execution steps: Generated subject events record the steps of algorithm execution in the graph rather than intermediate calculation data.
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Local causality: Model events define only the logical causality of their execution and do not prescribe conditions for generating subsequent events. This corresponds to a business scheme where each actor performs their operation when the necessary resources are available and is unaware of who will use the result of their work.
As a result, the boldsea system is not focused on transforming input data into output data but on implementing business logic defined in semantic models. Using Dataflow allows for:
•
Maximum parallelization and scalability of processes.
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Simplicity in editing action models without stopping processes.
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Modification of existing models and introduction of new ones without stopping business processes. The added model event will generate new subject events based on their causality with existing events and cannot affect the already running action algorithm.
Thus, boldsea uses Dataflow to create a flexible, scalable, and dynamic model execution environment where the logic of operation is determined by the data (event) flow, not the sequence of commands.

The boldsea technology offers effective solutions to problems faced by applications implemented using traditional approaches (control flow architecture without semantics or with object semantics).

Existing problems:
• Traditional BPM systems use rigid process schemes that are difficult to change after implementation.
• Changing processes often requires stopping the system.
• Parallel processes and conditional transitions are difficult to implement.
• The history of process execution is stored fragmentarily.
boldsea solution: Representing processes as an event stream naturally supports parallelism and conditional logic. Models can be changed without stopping the system, and the complete event history allows for process analysis and optimization. The dataflow architecture ensures efficient execution of complex processes.

Existing problems:
• Focus on documents as static objects.
• Difficulty tracking the real status of documents.
• Limited capabilities for analyzing document workflows.
• Complex integration with other systems.
boldsea solution: Documents are represented as sequences of events of their creation and processing. This provides complete transparency of workflows and the ability to accurately track status. Semantic models simplify integration with other systems, and the event history allows for analyzing the efficiency of document management.

Existing problems:
• Lack of support for temporality (change history).
• Difficulty modeling dynamic processes.
• Focus on static relationships between objects.
• Need for special extensions to work with time.
boldsea solution: Built-in support for temporality through event streams. Events naturally reflect the dynamics of changes. Semantic models define rules for creating events, ensuring data integrity. The ability to create multiple classifications on a single dataset.

Existing problems:
• Lack of a semantic layer for data.
• Difficulty preserving the history of processing.
• Challenges in changing processing logic.
• Limited capabilities for analyzing historical data.
boldsea solution: Semantic models give a meaningful structure to data streams. Events preserve the complete history of processing. Logic can be changed without stopping the system. Temporal queries allow for analyzing data in its development. Easy integration with LLM.

Existing problems:
• Limited capabilities for modeling complex processes.
• Lack of semantic consistency.
• Difficulty integrating with existing systems.
• Scalability issues with solutions.
boldsea solution: Event semantics allow for describing complex processes without programming and executing models without compiling into code. The unified data format simplifies integration. The dataflow architecture ensures scalability. The event history allows for debugging and optimizing processes.
The boldsea technology offers a unified approach to solving these problems by representing activities as event streams, semantic modeling, and asynchronous data processing. This enables the creation of more flexible, scalable, and integrated solutions while maintaining simplicity in development and modification.

• Unified data representation: boldsea offers a unified data format where any facts, objects, processes, actions, and actors are described as systems of events. This allows for the unification of data storage and processing.
• Temporal data storage: All events in the boldsea system are stored as temporal sequences, enabling the event storage to act as a message broker and ensuring asynchronous interaction between system elements. Unlike traditional systems where data is often overwritten, boldsea preserves the entire history of changes.
• Semantic data clarity: Data in boldsea is created based on models and has semantic content independent of software elements or storage structure. This ensures the independence of the data's semantic content from the software.
• Executable semantic models: boldsea uses executable semantic models that define the structure of the event graph and the sequence of its construction. This allows for the creation of business logic algorithms directly in the semantic language without using traditional programming languages.
• Event-driven architecture: boldsea is based on an event-driven architecture where any activity is represented as a stream of events, distinguished and performed by actors. This enables efficient use of AI systems for data analysis and the creation of adaptive interfaces.
• Decentralized business process management: boldsea allows for the combination of temporal knowledge bases and business process modeling systems, enabling the participation of multiple independent actors in the creation and execution of processes.
• Cryptographic data protection: The boldsea platform includes cryptographic data protection features necessary for document management and protection against falsification.
• Low-code development: boldsea uses low-code technologies, minimizing time-to-market and reducing the need for developers.
• Relativity of object descriptions: Objects in boldsea are described as sets of events, eliminating the absolutization of their description inherent in object-oriented approaches.
• Dataflow architecture: The execution of action models in boldsea is based on the dataflow approach, ensuring asynchronous operation processing as data becomes available, unlike the step-by-step execution of commands in traditional systems.

Flexible modeling of dynamic processes
Unlike traditional approaches focused on static objects, boldsea naturally reflects the dynamics of business processes through event streams. This makes it easy to model complex scenarios with parallel tasks, conditional transitions, and multi-step operations. Processes are described as they actually occur in the organization, simplifying their understanding and optimization.
Changing models without system downtime
The unique architecture of boldsea allows for modifying business processes "on the fly" without interrupting system operation. When you add a new model event or change an existing one, it does not affect already running processes. The new logic takes effect immediately after the changes are made, ensuring continuity of business operations and the ability to quickly adapt to changing requirements.
Parallel execution of operations
The use of dataflow architecture ensures natural parallelization of processes. Events are generated asynchronously as soon as the necessary conditions are met, significantly increasing system performance. This is especially important for complex business processes with many participants and parallel operations.
Transparency and traceability of changes
Every action in the system is recorded as an event with a timestamp, actor, and context. Events are never deleted, forming a complete and immutable history of all operations. This provides an unprecedented level of transparency, enabling detailed audits and process efficiency analysis.
Semantic data consistency
In boldsea, all data is created based on semantic models, ensuring its consistency and integrity. The use of standardized dictionaries and a unified event format ensures a common understanding of data by all process participants and simplifies the integration of various systems.
Ease of integration
Thanks to the use of standard protocols and a unified data format, boldsea easily integrates with existing systems. The system's API allows for connecting external data sources, sensors, and software agents. At the same time, the semantic nature of the data ensures its comprehensibility for both humans and machines, simplifying the creation of integration solutions.

In general, the boldsea approach to modeling complex dynamic systems can be described as follows: any activity can formally be represented as a set of events generated and recorded by participants in this activity – actors. It is asserted that any content of activity can be expressed as an ordered system of events that capture relationships between actors, actors and resources, i.e., as an event ontology.
Event ontology is a formal model of activity represented as a directed acyclic graph, where the nodes are events, and the edges are causal relationships between events. The event record format includes its semantic description, capturing the performed act or change in the property value of an object, which is registered or generated by an actor. The event format also specifies references to causal events, defining its causal dependency on preceding events. The conditions for event execution are set by special logical expressions defined in the models. The results of model execution are recorded in the event graph as a sequence of domain-specific events.
Thus, event ontology simultaneously serves as: (1) a form of knowledge representation about the subject area (its semantic description), (2) a dynamic model of activity implemented in this subject area, and (3) a temporal data storage, essentially a knowledge graph of activity.
Unlike standard semantic approaches, boldsea emphasizes not so much data storage and retrieval but activity modeling using executable event models. Business logic implementation is based on the dataflow ideology: a logical expression associated with a model event, composed of values of preceding events, is considered the condition for the event's execution. As a result of executing semantic models, new events are generated, which record changes in objects of the subject area and simultaneously serve as conditions for generating subsequent events.
The values of domain-specific events can be entered by actors in a screen form field (or selected from a suggested list) or retrieved by a query to the graph written in a special language.
The boldsea ideology can be briefly summarized as follows:
1. All data in the subject area is created and stored as events that record the presence or change of object properties;
2. Events are recorded in a semantic format (containing not only property values but also metadata);
3. The model event format includes a logical expression that defines the condition for its execution, i.e., the generation of a domain-specific event, enabling the dataflow approach to algorithm execution.

boldsea-engine is simultaneously an ontology editor, providing semantic descriptions of the subject area (creating structures of concepts and actions), and a workflow engine, implementing the modeling and execution of business processes. Overall, the boldsea-engine should be positioned as a unified tool for semantic activity modeling, where the creation of business process models is implemented through the construction of an event ontology of the subject area.
As in traditional (object-oriented) ontology editors, the semantic description of the subject area in boldsea begins with the identification of concepts involved in the activity and their properties. A concept is a type of object represented in the activity by individuals – specific things with specific property values (an individual of the concept "house" is "house #5 on Park Street"). In addition to concepts and their properties, acts – events of changes in concept individuals – are introduced in the event ontology. To describe the sequence of acts performed by actors with individuals, the notion of "action" is introduced. Like a concept, an action in activity is represented by individuals.
In boldsea ontologies, two types of properties are distinguished: attributes and relationships. An attribute is a property whose value is directly recorded for an individual ("color," "weight," "acidity"). Attribute values are numbers and strings. Relationships, on the other hand, are recorded only between concepts ("having a friend," "being a client," "being part of"), meaning the value of a relationship can only be an individual (a specific person, detail). Property lists are stored in dictionaries.
The initial orientation of boldsea towards business process modeling requires specifying activity participants – actors, as well as roles that define actors' rights to perform events. An actor is essentially an identifier on behalf of which activity is carried out. No event in the system can be recorded without specifying an actor. An actor identifier can be associated with a person, a sensor, or a software agent. An actor can be assigned one or more roles.
Essentially, semantic activity modeling boils down to creating models of concepts and actions. Using models, the activity ontology is described: what properties individuals can have and what must or can happen to individuals. During model execution, domain-specific events are created, recording specific property values of individuals.
Individuals of concepts created based on models record the current state of the subject area, while individuals of actions record the history of property value changes. No event can be recorded without specifying the model by which it was created.
A model is a tree of model events describing the structure of concept properties: root properties are recorded on the model creation event, and nested properties are recorded on properties, properties of properties, and so on ("temperature 39 degrees, temperature has a tendency to rise, tendency is stable"). The model serves as a template for creating individuals of concepts and actions, representing sets of domain-specific events that assign property values to an individual's identifier.
A domain-specific event is formed based on a model event, which specifies the property type and the event on which this property is recorded. The creation of a domain-specific event based on a model event considers limiting properties, such as the condition for generating the domain-specific event (Condition), rights to create the event (Permission), allowable value range (Range), and others. The generation of domain-specific events based on model events can be initiated: (1) by an actor, when entering values in a screen form field built on the model, (2) upon receiving external data, and (3) automatically, when retrieving an event value by a query from the graph.

1. Event-Driven Semantic Approach:
a. boldsea introduces a subject-event method that models activities as a set of events generated by actors (e.g., humans, robots, sensors, or software agents). This approach captures both the semantic content and causal relationships between events, which is a significant departure from traditional workflow engines that rely on control flow architectures.
b. The use of directed acyclic graphs (DAGs) to represent events and their relationships is innovative, as it allows for capturing the temporal and causal aspects of processes, which traditional semantic technologies struggle to handle.
2. No-Code Development:
a. boldsea enables no-code creation and execution of semantic models for business processes. This allows non-technical users (e.g., business analysts) to model and modify complex processes without requiring programming expertise. This democratizes process automation and reduces reliance on IT departments.
3. Dataflow Architecture:
a. boldsea leverages a dataflow execution paradigm, which allows for real-time process modifications without interrupting ongoing activities. This is a significant improvement over traditional BPM systems, which often require system downtime for process changes.
b. The subscription mechanism for monitoring events and triggering new events based on conditions is a novel feature that enhances flexibility and scalability.
4. Unified Event Data Format:
a. boldsea introduces a unified event data format that integrates semantic modeling, workflow execution, and temporal data storage. This unification addresses the fragmentation often seen in enterprise systems, where separate solutions are used for BPM, knowledge management, and document automation.
5. Dynamic Process Modification:
a. The ability to dynamically modify model events without stopping the system is a key innovation. This feature ensures that business processes can evolve in real-time, adapting to changing requirements without disruption.
6. Semantic Consistency and Historical Records:
a. boldsea maintains semantic consistency across different business domains and preserves complete historical records of process execution. This is a significant improvement over existing systems, which often struggle with maintaining historical data and semantic integrity.

1. Enterprise Process Automation:
a. boldsea provides a unified platform for enterprise content management, process automation, and knowledge base maintenance. This integration reduces the complexity and cost of managing multiple specialized systems (e.g., BPM, CRM, document management).
b. The ability to model and execute processes in a no-code environment makes it accessible to a broader range of users, accelerating process automation initiatives.
2. Real-Time Adaptability:
a. The real-time modification capability allows businesses to adapt their processes quickly in response to changing market conditions, regulatory requirements, or internal needs. This agility is crucial in today’s fast-paced business environment.
3. Improved Decision-Making:
a. boldsea’s ability to maintain complete historical records and provide semantic consistency enables better analysis of process evolution over time. This can lead to more informed decision-making and continuous process improvement.
4. Scalability and Flexibility:
a. The dataflow architecture and event-driven approach make the system highly scalable and flexible. It can handle complex, distributed processes and support parallel processing, which is essential for large enterprises with diverse operations.
5. Integration with IoT and External Systems:
a. boldsea supports integration with IoT devices, external databases, and software agents, enabling seamless data exchange and interoperability with other systems. This is particularly valuable for industries leveraging IoT for data collection and analysis.
6. Role-Based Access Control:
a. The role-based access control mechanism ensures that only authorized actors can create or modify events, enhancing security and compliance in process execution.
7. Predictive Insights and Automation:
a. boldsea’s support for AI and machine learning models allows for predictive insights and automated decision-making based on historical event data. This can further enhance process efficiency and reduce manual intervention.
8. Audit Trail and Compliance:
a.The system maintains a complete history of events, providing an audit trail that can be used for compliance purposes. This is particularly important in regulated industries where tracking process execution is critical.

boldsea is highly innovative, particularly in its event-driven semantic approach, no-code development capabilities, and real-time adaptability. Its practical value lies in its ability to unify and simplify enterprise process automation, improve decision-making through historical data analysis, and enhance scalability and flexibility in complex environments. By addressing the limitations of traditional BPM systems and semantic technologies, boldsea offers a robust solution for modern enterprises seeking to optimize their business processes and maintain competitive advantage.

boldsea represents a fundamentally new approach to describing and automating business processes, significantly different from traditional systems. While classical solutions describe business through static objects—documents, roles, and statuses—boldsea focuses on events—actions and changes occurring within the organization.
The approach is based on representing a company's activity as a continuous stream of events. These can include actions like a manager creating a request, a client approving a budget, the system automatically calculating costs, or an accountant issuing an invoice. Each such event always has an initiator (actor)—whether it's an employee, a client, or a software system. Events always lead to changes in the state of objects, for example, a request receives a new status, or edits are made to a budget. At the same time, any event can only occur under certain conditions—for instance, an invoice is issued only after the budget is approved.
All events in the system form a directed graph—a network of interconnected actions where each subsequent event is conditioned by the previous ones. The system operates on the "dataflow" principle: each event has clear execution conditions, and when these conditions are met, the event occurs automatically and can trigger the next chain of events. Actions in the system can be performed manually through the user interface or automatically based on predefined rules or data received from external systems.
Unlike traditional semantic systems focused on data storage, boldsea enables the automation of complex business processes, tracks causal relationships of all changes, and flexibly restructures processes without programming.

— Ever feel like traditional business models are kind of stuck in the past? Well, we've been handed this stack of technical documents about something called Boldachov's Subject-Event-Approach.
— Oh, boldsea.
— Yeah, boldsea for short. And it's dense. But let's dive in and see what we can find.
— It seems to be making some pretty bold claims, from what I can gather. It kind of flips the script on how we model systems.
— Okay, let's unpack that a little. The core idea seems to be ditching thinking about things as static things and instead viewing them as a chain of events.
— Exactly. Like think of a customer journey map as an example. Instead of just seeing a customer as a data point, you see each interaction they have as an event that builds on the last.
— So not just customer, but like customer search for product. Customer compared prices. Customer made a purchase.
— Exactly.
— That's so much richer in terms of understanding what's actually happening.
— And what's really fascinating is that each event in boldsea isn't just a bland timestamp. It's like a breadcrumb, revealing not only what happened, but who triggered it and what conditions had to exist beforehand.
— It's like having a detective's case file, meticulously documenting every interaction. And that brings us to another big idea here, data becoming dynamic. Bottleneck. If we're tracking every event in a system, not just snapshots in time, you have this incredibly rich data set. Imagine the analysis.
— Imagine being able to rewind and replay a company's entire history.
— Oh, wow.
— Seeing every decision, every bottleneck, every success, all in context.
— Wow.
— boldsea could fundamentally change how we understand cause and effect within these complex systems.
— It'd be like having a time machine for your business.
— Yes.
— But there's more, right?
— Yeah.
— The document also talks about how boldsea handles different perspectives.
— Right. One of the examples they use is a simple bolt.
— Okay.
— To an engineer, it's a fastener. To the accounting department, it's an asset.
— Yeah.
— Traditionally, these viewpoints might be siloed in different databases. But with boldsea, each perspective is captured within the event stream. It's like a jazz band. Okay. Each musician has their part. But boldsea is the score that shows how they all come together to make music.
— So you could have, like, different teams, different software, even different companies collaborating seamlessly because they're speaking the same data language.
— That's the idea.
— That's huge. So it's like the Tower of Babel problem, but for data solved.
— Okay. I'm getting how all these events create a more dynamic view, but the document also keeps mentioning this event graph. What exactly is that?
— Think of it like a social network, but instead of people and their connections, you have events. Okay. Each event is a node, and the lines connecting them represent the relationships between them.
— Okay, I can visualize that, but what kind of relationships are we talking about here? It's not like events are friending each other, or are they?
— Not quite. Remember how each event in boldsea has that condition field that specifies what had to happen before it could occur?
— Right. Those conditions are the relationships. Event A has to happen before B, which then enables C, and so on.
— So, it's less about friendship and more about a chain of events, each one leading to the next.
— Exactly. Each chain forms a path through this graph. But then imagine multiple paths intertwining, branching off, converging. It creates this intricate web that maps out exactly how things unfold over time.
— Okay. Now my head's spinning a bit. Give me a real-world example of how this graph thing actually plays out.
— Sure. Imagine a simple manufacturing process. The event order placed might trigger raw materials ordered, which then leads to production scheduled and so on. Each of those events could have its own little sub-processes within the larger graph.
— And because you're tracking each tiny event, not just major milestones, you get this super granular view of the entire operation.
— And don't forget the accountability aspect. Since each event is linked to who triggered it, there's no more guessing games when things go wrong. The event graph tells the whole story.
— That's incredible. But hold on, the document suggests that this graph isn't just a record of what happened, it's a living model of the system itself.
— Right, it's like the difference between reading a history book and having a simulator. Because the graph doesn't just capture events, but the rules and dependencies between them, you can use it to game out different scenarios.
— So you're saying I could, like, run simulations, test what happens if we change suppliers, or introduce a new product, all within this event graph.
— Precisely. And this is where those standardized dictionaries become really powerful. If everyone is speaking the same data language, you can create models that span multiple systems, even multiple organizations.
— You could have a model for an entire supply chain with each company using boldsea to track their piece of the puzzle. That's next-level coordination.
— Exactly. And since the whole system is event-driven, it can react to changes in real time. A shipping delay from one supplier could automatically trigger adjustment to the production schedule of another minimizing disruptions.
— Wow. OK. So we've gone from this, like, static view of businesses to this dynamic, interconnected web of events. It's like we've zoomed out and are seeing the matrix or something.
— It is a pretty radical shift in thinking. But that responsiveness and adaptability you mentioned, that's where the magic happens. boldsea allows these systems to essentially self-optimize on the fly.
— OK. So color me intrigued, but this all seems pretty high tech. What's the learning curve like for actually using this thing? The document mentions a semantic engine that's doing all the behind-the-scenes work. Does that mean we need a computer science degree to use this?
— Not at all. And that's actually another point. The document emphasizes the accessibility of it all. This new code revolution we talked about earlier, it's at the heart of boldsea.
— Right. That idea of using visual tools and models instead of writing lines of code. So I'm picturing something like a digital flowchart builder, but for entire systems.
— That's a great way to visualize it. boldsea takes that concept and runs with it. They're talking about empowering everyone from business analysts to artists to understand and model the systems they interact with every day.
— That's wild. Democratizing access to this kind of complex data analysis could be a game changer. But with great power comes great responsibility, right? I mean, there have to be some potential downsides to all this interconnectedness.
— Absolutely. Absolutely. You can't talk about a system this transformative without acknowledging the potential challenges. Data security, for example, becomes paramount when you have a system recording every single event.
— Right. It would be like having a super detailed history book, but if it fell into the wrong hands, not ideal.
— Exactly. And then there are the broader questions about data privacy and ownership. These are things that need careful consideration, not just from a technical standpoint, but from an ethical one as well.
— It's like they say, technology is neutral, it's how we use it that matters. boldsea could be incredibly powerful, but it's up to us to make sure it's used responsibly.
— Precisely. Mm-hmm. But even if boldsea doesn't completely revolutionize the world overnight, I think it's incredibly thought-provoking. It challenges us to think differently about information, about how we make decisions about the very systems we build our lives around.
— It's a glimpse into a future where understanding complexity isn't just for the tech wizards, but for everyone. One. I have to say I'm both excited and a little terrified by the possibilities.
— That's the perfect way to put it. boldsea is both a powerful tool and a mirror reflecting back at us some fundamental questions about how we want to shape the future.
— And on that note, we'll leave you with this final thought. If our actions and decisions leave a digital trail shaping not just our own paths, but the entire system around us, what does that say about the butterfly effect of our choices? Something to ponder. Until next time, keep diving deep.

• boldsea technology: An approach to computer modeling of activities based on recording event streams and creating executable semantic models using the dataflow ideology.
• boldsea engine: A tool for activity modeling based on boldsea principles. It provides tools for creating event ontologies and a workflow engine for their execution.
• Semantic modeling: An approach to designing information systems that separates the semantic content of a domain from the application structure. It uses record formats that combine data and metadata.
• Event semantics: A method of describing activities as an event stream, where an event is the recording by an actor of the presence, change, or creation of objects and their property values.
• Control Flow principle: A traditional approach to algorithm execution where commands are executed sequentially step by step according to the algorithm.
• Dataflow principle: An approach to algorithm execution where operations are performed asynchronously as data becomes available.
• Temporal graph: A graph representing the temporal sequence of events and their relationships, structured as a directed acyclic graph (DAG).

• Actor: An entity that distinguishes, changes, or acts, which can be associated with a person, robot, software agent, or sensor. Adding an actor to the event format allows: (1) controlling the origin and validity of data, (2) obtaining a comprehensive description of actors as a set of events they generate, (3) including alternative opinions in the domain description.
• Individual: A unique object that is distinguished, changed, or created by an actor; an individual has spatial and/or temporal boundaries.
• Concept: The semantic type of an individual, which the actor associates with the individual; distinguishing an individual means indicating which concept it belongs to.
• Action: The semantic type of a temporally distributed individual, representing a partially ordered sequence of events.
• Value: What the actor distinguishes/changes in an individual; a value exists only as distinguished on an individual; an individual is described as a set of distinguishable values.
• Act: An event of changing the status/state of an individual (created, purchased, approved); the value of an act is the actor.
• Attribute: A property that the actor distinguishes in an individual directly, without reference to other individuals (color, hardness); the value of an attribute has a fixed data type (string, integer, etc.) and may have a unit of measurement.
• Relation: A property that the actor records in an individual only in relation to another individual ("has part," "is a client"); the value of the relation is the individual to which it is recorded.
• Role: The actor's relationship to a project, recording the actor's access rights to individuals (their properties); formally, a role is a list of rights granted to actors; in different organizations, the same actor may have different roles.
• Condition: A condition determining the possibility of an event occurring; defines ordering relationships between events; specified by a logical expression composed of values of preceding events.
• Causals: Records the sequence relationships between events defined by the logical expression Condition.
• Model Event: An event recording the presence of a property or act in a concept or action; a model event includes constraints on property values and conditions for actualization (Condition).
• Reification Event: An event recording the specific value of a property of a concept's individual or a specific act of an action; created based on a model event considering all constraints and conditions.
• Restriction: A property of a model event that imposes constraints on the possibility of creating a reification event and its values (mandatory, data type, access rights, etc.).
• Model: An ordered list of model events describing a concept or action. Individuals of concepts are created based on models. The same individual can participate in different actions, represented by different sets of properties, so a concept can have multiple models.
• Nested properties: Properties recorded on the root properties of a concept (properties of properties); up to 5 levels of nesting are allowed; properties on which nested properties are recorded are called parent properties.
• Vocabulary: A list of concepts or properties (attributes, relations, roles) used for the semantic description of the domain—creating models of concepts and actions; property vocabularies are linked to models.
• Application: A set of models and vocabularies combined to perform a fixed set of functions; an application is an element of functionality import/export.
• Project: A concept, a set of individuals of concepts, actions, and actors implementing purposeful activities within a fixed domain; the individual of the Project concept is assigned applications through which the organization's activities are implemented, roles, and other configuration parameters.

• Semantic technology: An approach to storing and transmitting data where information is represented in a unified format containing not only the data itself but also its semantic description (metadata), allowing the structure of data to be changed independently of the application code and enabling data exchange between independent applications.
• Knowledge graph: A data structure representing information as a network of interconnected entities (nodes) and their relationships (edges). Unlike traditional databases, knowledge graphs preserve semantic relationships between data elements.
• Directed Acyclic Graph (DAG): A data structure where elements are connected by unidirectional links without forming cycles. In boldsea, it is used to represent causal relationships between events.
• Dataflow architecture: An architectural approach that provides for asynchronous execution of operations when the necessary data is available, rather than following a predefined sequence of commands as in traditional control flow architecture (von Neumann). In boldsea, an event-driven variant of dataflow architecture is used, ensuring event execution when all causal events are present.
• Temporal data: Data that records the temporal sequence of system changes; temporal storages preserve the history of data changes.

• API (Application Programming Interface): A set of rules and protocols that allows different software systems to interact with each other.
• IoT (Internet of Things): A network of physical devices equipped with software and sensors for exchanging data over the internet.
• Metadata: Data about data, describing the structure, format, and context of the main information in the system.
• Scalability: The ability of a system to work efficiently as the load or volume of processed data increases by adding resources.

s• BPM systems (Business Process Management): Software platforms for modeling, automating, and analyzing an organization's business processes.
• ECM systems (Enterprise Content Management): Systems for managing corporate content, including functions for creating, storing, distributing, and archiving documents and other types of content.
• CRM systems (Customer Relationship Management): Systems for managing customer relationships, automating processes of interaction with clients.
• No-Code/Low-Code platforms: Tools for application development that allow creating software with minimal use of traditional programming through visual interfaces and ready-made components.