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PRIMER EJERCICIO I. TEC. I. CENTROS EDUCATIVOS

construccion casas

Batalla De Robots

Robots de Guerra

Robótica

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Aula invertida

Robotica educativa

Conceptos basicos de robótica

Aura Duque

Definiciones y ejemplos de robótica.

Jaque Beciez

La Robotica

Dayiiz VN

PRESENTACION DE ROBOTICA

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PRIMER EJERCICIO I. TEC. I. CENTROS EDUCATIVOS

construccion casas

Batalla De Robots

Robots de Guerra

Robótica

Robots de Guerra

Robots

Robots moviles

Tipos de robots

robots

Manual arduino

La robotica

Morfologia de robots

Arduino uno

Aula invertida

Robotica educativa

Conceptos basicos de robótica

Definiciones y ejemplos de robótica.

La Robotica

PRESENTACION DE ROBOTICA

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ADR, or Architecture Decision Record, is a valuable tool in software development for several reasons. It provides a centralized location for documenting and tracking architectural decisions, aiding both current and future team members. ADRs enhance communication among team members by documenting the rationale behind architectural decisions, especially beneficial during onboarding of new team members or when revisiting decisions. They serve as a knowledge base, enabling teams to learn from past decisions and refine their decision-making process. Additionally, ADRs contribute to transparency by helping stakeholders understand the reasons behind specific architectural choices. As with any other tool or process, introducing them into an organization can face several obstacles, and overcoming these challenges is crucial for successful implementation. In this talk I go through some common problems and our way of solving them.

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Data spaces in distributed environments should be allowed to evolve in agile ways providing data space owners with large flexibility about which data they store. Agility and heterogeneity, however, jeopardize data exchanges because representations may build on varying ontologies and data consumers may not rely on the semantic correctness of their queries in the context of semantically heterogeneous, evolving data spaces. Graph data spaces are one example of a powerful model for representing and querying data whose semantics may change over time. To assert and enforce conditions on individual graph data spaces, shape languages (e.g SHACL) have been developed. We investigate the question of how querying and programming can be guarded by reasoning over SHACL constraints in a distributed setting and we sketch a picture of how a future landscape based on semantically heterogeneous data spaces might look like.

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