Arches Modeling Documentation Archived 20220610

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By clicking on the SLIDESHOW link, you will be able to access information on the following topics. You can also go to the topic slide/section by clicking each topic below:

What is a Data Model?
Types of Data Models
Structured data
Key elements of structured data
-Clean Data
-Controlled Vocabularies
-Universal Unique Identifiers
-Triples
Structured data in a data model

What is a Semantic Data Model?
Semantic Standards
Semantic Formats
Semantic Ontologies
Semantic Web

What is an Arches Resource Model?
Resource Model and Branches
Anatomy of an Arches Branch
Data Types
Concept Collections
Relationships between Resource Models
Arches Designer
Encoding the ontology
Reference Data Manager

The Modeling Process
Data requirements
Data content standards
Creating a conceptual model
Building Arches Resource Models

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(Coming soon!) Documentation on the following topics:

Introduction

Assumptions
ARM WG Ontology
Linked Open Data
What makes a good data model?

Modeling Patterns

Introduction

The benefits of modeling your data in Arches using the principles described in this documentation, include the following:

Domain expertise

The CIDOC-CRM has been developed by cultural heritage domain experts for those working in the cultural heritage field.  The CRM provides the framework to build conceptual models for archives, libraries, and museums. Working with the CRM will allow cultural heritage institutions to partner with other similar communities and to build information systems that support specialized research questions

More information about the CRM can be found here.

Information Search and Retrieval

Structuring your data into a data model, or schema, will enhance the searchability and findability of information stored within it. The schema provides the outline for where and how the information is stored. The more detailed and precise your data models are, built using the Arches Designer, the better return of search results for those using your Arches instance. Linked Data is a graph structure that can enhance searchability by establishing semantic connections between resource elements.

Shareability and Interoperability

Linked Data and semantic standardization allow the possibility for organizations to share their data with other institutions who structure their data following the same guidelines. The benefit of sharing data in this way is to enhance collaboration between organizations and to share resources and work between multiple entities.

Structured data sets will enhance interoperability and data usability for a wider variety of computer and software systems.

General Data Management Terms

• Structured data: data that is organized and formatted within a database or other such repository to enhance data searchability and to allow for more effective processing and analysis.
• Data cleaning: the process of ensuring consistency and accuracy of records stored within a table or database, such as spelling, date order, or consistent identification.
• Standards: the rules or documented agreement on the format, structure, representation, usage, etc of the ways in which data are described or recorded. They are the best practices of how data and metadata should be described, formatted, or included in a data set.
• Controlled vocabulary: a set of standardized terms, thesauri, or subject headings that are preferred for a data set. It ensures consistency of vocabulary to control for spelling differences, homonyms, or name variations for a single defined entity.
• Data Model: An abstract, visual representation of data objects for a group or organization in order to structure a database. A good data model follows formalized standards, or best practices, in format and structure.
• Conceptual Model: A type of data model that establishes entities, their properties, and the relationship between each entity. The model is used to formalize entity relationships to represent the semantics of an organization.
• Ontology: An ontology defines the elements — entities and their properties — within a data structure. It formalizes the conceptual data model with a common controlled vocabulary, identifiers, and structure that allows for system interoperability of the database.
• Universal Unique Identifier (UUID): a 128-bit number used to reliably identify an object or entity within a database.

Arches Specific Terms

For a larger collection of Arches Terminology, see the Arches Glossary Here.

• Arches Designer: A user interface for facilitating database design, i.e. the creation of Resource Models. The Arches Designer consists of many different tools, such as the Graph Designer and Card Manager, each of which helps build a different facet of Resource Model creation.
• Reference Data Manager: The Reference Data Manager (RDM) is a core Arches module to create and maintain concept schemes (controlled vocabularies) or thesauri. It enables the creation and maintenance of controlled vocabularies for use in dropdowns and controlled fields within the various Arches Resource forms. For more information: [Reference Data Manager (RDM)](https://arches.readthedocs.io/en/stable/rdm/)
• ARM WG: The group established to provide consensus-based guidance on Arches Resource Models and constituent Branches, specifically on how to build and apply them. More information on the ARM [can be found here](https://www.archesproject.org/arm-wg/).

Arches

• Arches Documentation

CIDOC CRM

• CIDOC-CRM Primer
• CIDOC-CRM Tutorial
• CIDOC-CRM Video Overview with Stephen Stead
• Learning Ontology & CIDOC CRM
• CIDOC-CRM Functional Units

Other Examples

• W3C Semantic Web: Simple Knowledge Management System (SKOS) 
• Linked Art Modeling 
• Swiss Art Research Infrastructure Project- SARI 
• Ontology Management Environment- Data for History Consortium