Schema

as donto believed on

From Dontopedia, the open, paraconsistent wiki. (Last updated 2026-06-08.)

Schema is My collection.

63 facts·27 predicates·21 sources·11 in dispute

Mostly:rdf:type(17), has field(5), contains(4)

Rdf:typein dispute`rdf:type`

Data Structure Definition^[4]sourceall time · 1ee9897b 4621 4696 A058 06bd8b63f6d2
Collection Schema^[5]all time · 58af948e Ad4f 4c4d 8464 06c37433c965
Plan^[6]all time · 6
Data Structure^[7]all time · 05681b5b 7cd5 4bbc A01d 846d2ca71209
Data Schema^[7]all time · 05681b5b 7cd5 4bbc A01d 846d2ca71209
Schema Object^[9]all time · F80d8de8 0d2a 446e Ac9c Fc4672dce4f0
Technical Specification^[10]all time · 606
Schema Definition^[11]all time · Bfbfd340 90ed 4b66 Accf 3baa0cf8bc7c
Database Structure^[12]all time · 8769b3dc Dc08 4d76 9935 C0166e90c298
Database Schema^[13]all time · 1bbb1dc1 7dd4 47ad 9637 C6b03aeeb55d

Inbound mentions (47)

Other subjects in dontopedia point AT this entity as a value. These are inverse relationships — e.g. "X motherOf this subject" — and answer questions the forward facts can't. Grouped by predicate.

`hasParameter`Has Parameter(6)

Create Classex:create-class
Json.dumpex:json.dump
Json.dumpsex:json.dumps
Send Email Notificationex:send_email_notification
Share Metadata Schemaex:share_metadata_schema
Validateex:validate

`hasSchema`Has Schema(4)

Collectionex:collection
Example Collectionex:example-collection
Example Collectionex:example-collection
Vector Collectionex:vector-collection

`isPartOf`Is Part of(2)

Id Fieldex:id-field
Vector Fieldex:vector-field

`locatedIn`Located in(2)

Analyzersex:analyzers
Field Typesex:field-types

`serializesData`Serializes Data(2)

Json.dump Callex:json.dump_call
Json.dumps Callex:json.dumps_call

`shouldBe`Should Be(2)

Tool Call Componentsex:tool-call-components
Ui in Generalex:ui-in-general

`usesSchema`Uses Schema(2)

Collectionex:collection
Collection Creationex:collection-creation

`about`About(1)

Schema Adviceex:schema-advice

`assignedTo`Assigned to(1)

Schema Objectex:schema-object

`believesSchemaNotReviewed`Believes Schema Not Reviewed(1)

Foxhopex:foxhop

`clarifiedRegarding`Clarified Regarding(1)

Lisamegawattsex:lisamegawatts

`considersReviving`Considers Reviving(1)

Ajaxdavisex:ajaxdavis

`createdWith`Created With(1)

Collectionex:collection

`defines`Defines(1)

Fields Definitionex:fields-definition

`describes`Describes(1)

Docstringsex:docstrings

`discusses`Discusses(1)

Section 5ex:section-5

`ensuresCompatibility`Ensures Compatibility(1)

Repair User Profile Schema Toolex:repair-user-profile-schema-tool

`equivalentTo`Equivalent to(1)

Collectionsex:collections

`handlesResponsibility`Handles Responsibility(1)

Omega Botex:omega-bot

`hasNotSettledOn`Has Not Settled on(1)

Ajaxdavisex:ajaxdavis

`includesTag`Includes Tag(1)

Tags Repair User Profile Schemaex:tags-repair-user-profile-schema

`instantiatedWith`Instantiated With(1)

Collection Objectex:collection-object

`isCreatedWithSchema`Is Created With Schema(1)

Example Collectionex:example-collection

`isLike`Is Like(1)

Dnaex:dna

`notHumanReviewed`Not Human Reviewed(1)

Firehoseex:firehose

`plannedComponent`Planned Component(1)

Blah Projectex:blah-project

`plansToAddTo`Plans to Add to(1)

Ajaxdavisex:ajaxdavis

`relatesTo`Relates to(1)

Section 5ex:section-5

`requestsShare`Requests Share(1)

Message 4ex:message-4

`requires`Requires(1)

Collectionex:collection

`reviews`Reviews(1)

Step2ex:step2

`shouldBeAppliedTo`Should Be Applied to(1)

Normalisationex:normalisation

`target`Target(1)

Optimize Schemaex:optimize-schema

`willIncludeSchema`Will Include Schema(1)

Blah Mono Repoex:blah-mono-repo

Other facts (42)

The long tail: predicates that appear too rarely to warrant their own section. Filter or scroll to find a specific one. Each row links to its source.

42 facts

Predicate	Value	Ref
Has Field	Id Field	[5]
Has Field	Embedding Field	[5]
Has Field	Fields	[16]
Has Field	Id Field	[19]
Has Field	Vector Field	[19]
Contains	Role Class	[13]
Contains	Permission Class	[13]
Contains	User Class	[13]
Contains	Role Permission Association	[13]
Contains Field	Id Field	[17]
Contains Field	Vector Field	[17]
Contains Field	Id Field	[19]
Contains Field	Vector Field	[19]
Can Contain	Text Data	[7]
Can Contain	Vector Data	[7]
Unifies	Text Data	[7]
Unifies	Vector Data	[7]
Includes	text properties	[7]
Includes	vector properties	[7]
Has	class name	[8]
Has	properties array	[8]
Has Description	Test Collection	[15]
Has Description	Example collection	[18]
Has Component	Field Types	[20]
Has Component	Analyzers	[20]
Specifies How to	Build Body	[1]
Lacks Human Review	yet	[2]
Potentially Revived	true	[3]
Description	My collection	[5]
Has Vectorizer	text2vec-contextionary	[8]
Describes	default vectorizer for text	[8]
Is Example of	Python Code	[8]
Has Vectorizer Config	Text2vec Contextionary	[8]
Is Defined by	Tpmjs Package Scope	[10]
Used by	Vector Collection	[11]
Is Instanceof	CollectionSchema	[15]
Has Vector Dimension	128	[17]
Is Based on	Fields Definition	[17]
Used to Create	Example Collection	[19]
Used for	Collection Creation	[19]
Optimized for	Types of Queries	[20]
Optimizes for	Query Types	[21]

Timeline axis is valid_time — when each source says the fact was true in the world, not when Dontopedia learned about it. Retracted rows are kept for provenance; coloured stripes indicate the context kind.

63 undated

—

specifiesHowToblah/fetch/part-6

ex:build-body

—

lacksHumanReviewblah/fetch/part-11

yet

—

potentiallyRevivedblah/tpmjs/part-10

true

—

typebeam/1ee9897b-4621-4696-a058-06bd8b63f6d2

ex:DataStructureDefinition

—

descriptionbeam/58af948e-ad4f-4c4d-8464-06c37433c965

My collection

—

typebeam/58af948e-ad4f-4c4d-8464-06c37433c965

ex:CollectionSchema

—

labelbeam/58af948e-ad4f-4c4d-8464-06c37433c965

My collection

—

hasFieldbeam/58af948e-ad4f-4c4d-8464-06c37433c965

ex:id-field

—

hasFieldbeam/58af948e-ad4f-4c4d-8464-06c37433c965

ex:embedding-field

—

typeblah/fetch/6

ex:Plan

—

typebeam/05681b5b-7cd5-4bbc-a01d-846d2ca71209

ex:DataStructure

—

canContainbeam/05681b5b-7cd5-4bbc-a01d-846d2ca71209

ex:text-data

—

canContainbeam/05681b5b-7cd5-4bbc-a01d-846d2ca71209

ex:vector-data

—

unifiesbeam/05681b5b-7cd5-4bbc-a01d-846d2ca71209

ex:text-data

—

unifiesbeam/05681b5b-7cd5-4bbc-a01d-846d2ca71209

ex:vector-data

—

typebeam/05681b5b-7cd5-4bbc-a01d-846d2ca71209

ex:DataSchema

—

includesbeam/05681b5b-7cd5-4bbc-a01d-846d2ca71209

text properties

—

includesbeam/05681b5b-7cd5-4bbc-a01d-846d2ca71209

vector properties

—

hasbeam/7d88293f-b412-4a42-9fde-d4ff46d757a3

class name

—

hasbeam/7d88293f-b412-4a42-9fde-d4ff46d757a3

properties array

—

hasVectorizerbeam/7d88293f-b412-4a42-9fde-d4ff46d757a3

text2vec-contextionary

—

describesbeam/7d88293f-b412-4a42-9fde-d4ff46d757a3

default vectorizer for text

—

isExampleOfbeam/7d88293f-b412-4a42-9fde-d4ff46d757a3

ex:python-code

—

hasVectorizerConfigbeam/7d88293f-b412-4a42-9fde-d4ff46d757a3

ex:text2vec-contextionary

—

typebeam/f80d8de8-0d2a-446e-ac9c-fc4672dce4f0

ex:SchemaObject

—

typeblah/omega/606

ex:TechnicalSpecification

—

isDefinedByblah/omega/606

ex:tpmjs-package-scope

—

typebeam/bfbfd340-90ed-4b66-accf-3baa0cf8bc7c

ex:SchemaDefinition

—

usedBybeam/bfbfd340-90ed-4b66-accf-3baa0cf8bc7c

ex:vector-collection

—

typebeam/8769b3dc-dc08-4d76-9935-c0166e90c298

ex:DatabaseStructure

—

labelbeam/8769b3dc-dc08-4d76-9935-c0166e90c298

Schema

—

typebeam/1bbb1dc1-7dd4-47ad-9637-c6b03aeeb55d

ex:DatabaseSchema

—

containsbeam/1bbb1dc1-7dd4-47ad-9637-c6b03aeeb55d

ex:Role-class

—

containsbeam/1bbb1dc1-7dd4-47ad-9637-c6b03aeeb55d

ex:Permission-class

—

containsbeam/1bbb1dc1-7dd4-47ad-9637-c6b03aeeb55d

ex:User-class

—

containsbeam/1bbb1dc1-7dd4-47ad-9637-c6b03aeeb55d

ex:role-permission-association

—

typebeam/e9c89e43-ecf8-45b8-8f1f-afc5186cfb3f

ex:DataStructure

—

labelbeam/e9c89e43-ecf8-45b8-8f1f-afc5186cfb3f

Schema

—

typebeam/86785515-9f1f-4fdd-887b-9264324ad027

ex:CollectionSchema

—

hasDescriptionbeam/86785515-9f1f-4fdd-887b-9264324ad027

Test Collection

—

isInstanceofbeam/86785515-9f1f-4fdd-887b-9264324ad027

CollectionSchema

—

typebeam/36d3d33e-7909-4a4e-8c54-4700df9427bc

ex:CollectionSchema

—

hasFieldbeam/36d3d33e-7909-4a4e-8c54-4700df9427bc

ex:fields

—

hasVectorDimensionbeam/a57de09c-31cd-4c63-9205-77ae5f17cbdb

128

—

typebeam/a57de09c-31cd-4c63-9205-77ae5f17cbdb

ex:CollectionSchema

—

isBasedOnbeam/a57de09c-31cd-4c63-9205-77ae5f17cbdb

ex:fields-definition

—

containsFieldbeam/a57de09c-31cd-4c63-9205-77ae5f17cbdb

ex:id-field

—

containsFieldbeam/a57de09c-31cd-4c63-9205-77ae5f17cbdb

ex:vector-field

—

hasDescriptionbeam/c1884d4f-6cc0-42a1-9d04-1b18cb1f2a49

Example collection

—

typebeam/c1884d4f-6cc0-42a1-9d04-1b18cb1f2a49

ex:CollectionSchema

—

typebeam/d3060ac4-5d8b-4c26-9520-70ab56f38813

ex:CollectionSchema

—

hasFieldbeam/d3060ac4-5d8b-4c26-9520-70ab56f38813

ex:id-field

—

hasFieldbeam/d3060ac4-5d8b-4c26-9520-70ab56f38813

ex:vector-field

—

usedToCreatebeam/d3060ac4-5d8b-4c26-9520-70ab56f38813

ex:example-collection

—

usedForbeam/d3060ac4-5d8b-4c26-9520-70ab56f38813

ex:collection-creation

—

containsFieldbeam/d3060ac4-5d8b-4c26-9520-70ab56f38813

ex:id-field

—

containsFieldbeam/d3060ac4-5d8b-4c26-9520-70ab56f38813

ex:vector-field

—

typebeam/a6d72d2f-c189-45ad-890b-135b3254ee12

ex:DatabaseSchema

—

labelbeam/a6d72d2f-c189-45ad-890b-135b3254ee12

schema

—

hasComponentbeam/a6d72d2f-c189-45ad-890b-135b3254ee12

ex:field-types

—

hasComponentbeam/a6d72d2f-c189-45ad-890b-135b3254ee12

ex:analyzers

—

optimizedForbeam/a6d72d2f-c189-45ad-890b-135b3254ee12

ex:types-of-queries

—

optimizesForbeam/3ee33951-97e3-40c5-bd76-b5e04138e5eb

ex:query-types

References (21)

21 references

[1]Part 61 fact
ctx:discord/blah/fetch/part-6
[2]Part 111 fact
ctx:discord/blah/fetch/part-11
[3]Part 101 fact
ctx:discord/blah/tpmjs/part-10
[4]1ee9897b 4621 4696 A058 06bd8b63f6d21 fact
ctx:claims/beam/1ee9897b-4621-4696-a058-06bd8b63f6d2
- full textbeam-chunk
  text/plain1 KBdoc:beam/1ee9897b-4621-4696-a058-06bd8b63f6d2
  Show excerpt
  - Use dictionaries to store the data types and constraints for each field. 2. **Update the Data Model Generator Class**: - Modify the `DataModelGenerator` class to accept `field_types` and `field_constraints` as parameters. - Appl…
[5]58af948e Ad4f 4c4d 8464 06c37433c9655 facts
ctx:claims/beam/58af948e-ad4f-4c4d-8464-06c37433c965
- full textbeam-chunk
  text/plain1 KBdoc:beam/58af948e-ad4f-4c4d-8464-06c37433c965
  Show excerpt
  import numpy as np from pymilvus import connections, FieldSchema, CollectionSchema, DataType, Collection, utility # Initialize Milvus connections.connect("default", host="localhost", port="19530") # Define schema fields = [ FieldSchem…
[6]61 fact
ctx:discord/blah/fetch/6
- full textfetch-6
  text/plain3 KBdoc:agent/fetch-6/713268e3-903c-4c43-bda4-06e9583c3ff2
  Show excerpt
  [2026-02-05 02:00] traves_theberge: https://github.com/Traves-Theberge/Tasky-2.0 [2026-02-05 02:02] traves_theberge: indexing it on deepwiki right now [2026-02-05 02:03] traves_theberge: well tasky has a task list which it can create tasks …
[7]05681b5b 7cd5 4bbc A01d 846d2ca712098 facts
ctx:claims/beam/05681b5b-7cd5-4bbc-a01d-846d2ca71209
- full textbeam-chunk
  text/plain1 KBdoc:beam/05681b5b-7cd5-4bbc-a01d-846d2ca71209
  Show excerpt
  By following these steps and adding debugging information, you should be able to identify and resolve the issue causing the `Error: unable to retrieve data`. [Turn 2236] User: hmm, what if I need to query both text and vector data simultan…
[8]7d88293f B412 4a42 9fde D4ff46d757a36 facts
ctx:claims/beam/7d88293f-b412-4a42-9fde-d4ff46d757a3
- full textbeam-chunk
  text/plain1 KBdoc:beam/7d88293f-b412-4a42-9fde-d4ff46d757a3
  Show excerpt
  [Turn 2238] User: hmm, what if I need to handle different vector sizes for my data? Can Weaviate accommodate that? [Turn 2239] Assistant: Weaviate can handle different vector sizes for your data, but it requires some additional configurati…
[9]F80d8de8 0d2a 446e Ac9c Fc4672dce4f01 fact
ctx:claims/beam/f80d8de8-0d2a-446e-ac9c-fc4672dce4f0
- full textbeam-chunk
  text/plain1 KBdoc:beam/f80d8de8-0d2a-446e-ac9c-fc4672dce4f0
  Show excerpt
  # Create the schema in Weaviate client.schema.create_class(schema) print("Schema created successfully.") ``` #### Inserting Data When inserting data, you can specify which vector property to use based on the vector size. ```python # Add …
[10]6062 facts
ctx:discord/blah/omega/606
- full textomega-606
  text/plain3 KBdoc:agent/omega-606/751a80c4-ad4e-47db-bf9f-61ef1e735bfd
  Show excerpt
  [2025-12-05 20:59] omega [bot]: 🔧 1/1: githubCreateIssue ✅ Success ```json { "success": true, "issueNumber": 709, "issueUrl": "https://github.com/thomasdavis/omega/issues/709", "message": "Created issue #709: Add \"Tech Translate\" …
[11]Bfbfd340 90ed 4b66 Accf 3baa0cf8bc7c2 facts
ctx:claims/beam/bfbfd340-90ed-4b66-accf-3baa0cf8bc7c
- full textbeam-chunk
  text/plain1 KBdoc:beam/bfbfd340-90ed-4b66-accf-3baa0cf8bc7c
  Show excerpt
  vector_collection = Collection("rag_vectors", schema) # Insert documents into MongoDB documents = df.to_dict(orient='records') document_collection.insert_many(documents) # Insert vectors into Milvus vectors = df[['id', 'vector']].values.t…
[12]8769b3dc Dc08 4d76 9935 C0166e90c2982 facts
ctx:claims/beam/8769b3dc-dc08-4d76-9935-c0166e90c298
- full textbeam-chunk
  text/plain1 KBdoc:beam/8769b3dc-dc08-4d76-9935-c0166e90c298
  Show excerpt
  1. **Primary Key and Indexes**: - Ensure that the primary key is properly indexed. - Add indexes to columns that are frequently queried, such as `username` and `email`. 2. **Data Types**: - Use appropriate data types to optimize s…
[13]1bbb1dc1 7dd4 47ad 9637 C6b03aeeb55d5 facts
ctx:claims/beam/1bbb1dc1-7dd4-47ad-9637-c6b03aeeb55d
[14]E9c89e43 Ecf8 45b8 8f1f Afc5186cfb3f2 facts
ctx:claims/beam/e9c89e43-ecf8-45b8-8f1f-afc5186cfb3f
[15]86785515 9f1f 4fdd 887b 9264324ad0273 facts
ctx:claims/beam/86785515-9f1f-4fdd-887b-9264324ad027
[16]36d3d33e 7909 4a4e 8c54 4700df9427bc2 facts
ctx:claims/beam/36d3d33e-7909-4a4e-8c54-4700df9427bc
[17]A57de09c 31cd 4c63 9205 77ae5f17cbdb5 facts
ctx:claims/beam/a57de09c-31cd-4c63-9205-77ae5f17cbdb
- full textbeam-chunk
  text/plain1 KBdoc:beam/a57de09c-31cd-4c63-9205-77ae5f17cbdb
  Show excerpt
  - `connections.connect("default", host="localhost", port="19530")`: Connects to the Milvus server running on localhost at port 19530. 2. **Define Schema**: - `fields`: Defines the schema with an integer primary key (`id`) and a float…
[18]C1884d4f 6cc0 42a1 9d04 1b18cb1f2a492 facts
ctx:claims/beam/c1884d4f-6cc0-42a1-9d04-1b18cb1f2a49
- full textbeam-chunk
  text/plain1 KBdoc:beam/c1884d4f-6cc0-42a1-9d04-1b18cb1f2a49
  Show excerpt
  # Connect to Milvus server connections.connect("default", host="localhost", port="19530") # Define schema fields = [ FieldSchema(name="id", dtype=DataType.INT64, is_primary=True), FieldSchema(name="vector", dtype=DataType.FLOAT_VEC…
[19]D3060ac4 5d8b 4c26 9520 70ab56f388137 facts
ctx:claims/beam/d3060ac4-5d8b-4c26-9520-70ab56f38813
- full textbeam-chunk
  text/plain1 KBdoc:beam/d3060ac4-5d8b-4c26-9520-70ab56f38813
  Show excerpt
  [Turn 4944] User: I'm spending 6 hours on Milvus tutorials to improve my database skills, targeting a 20% knowledge increase. As part of this, I want to practice designing an efficient vector indexing workflow using Milvus. Can you guide me…
[20]A6d72d2f C189 45ad 890b 135b3254ee125 facts
ctx:claims/beam/a6d72d2f-c189-45ad-890b-135b3254ee12
[21]3ee33951 97e3 40c5 Bd76 B5e04138e5eb1 fact
ctx:claims/beam/3ee33951-97e3-40c5-bd76-b5e04138e5eb
- full textbeam-chunk
  text/plain1 KBdoc:beam/3ee33951-97e3-40c5-bd76-b5e04138e5eb
  Show excerpt
  Your query parameters are quite basic (`*:*` and `rows=10`). While this is fine for testing, you should ensure that your actual queries are optimized for the specific use case. ### 3. **Configuration Settings** Ensure that your Solr config…

Keep researching

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Schema

Rdf:typein disputerdf:type

Inbound mentions (47)

hasParameterHas Parameter(6)

hasSchemaHas Schema(4)

isPartOfIs Part of(2)

locatedInLocated in(2)

serializesDataSerializes Data(2)

shouldBeShould Be(2)

usesSchemaUses Schema(2)

aboutAbout(1)

assignedToAssigned to(1)

believesSchemaNotReviewedBelieves Schema Not Reviewed(1)

clarifiedRegardingClarified Regarding(1)

considersRevivingConsiders Reviving(1)

createdWithCreated With(1)

definesDefines(1)

describesDescribes(1)

discussesDiscusses(1)

ensuresCompatibilityEnsures Compatibility(1)

equivalentToEquivalent to(1)

handlesResponsibilityHandles Responsibility(1)

hasNotSettledOnHas Not Settled on(1)

includesTagIncludes Tag(1)

instantiatedWithInstantiated With(1)

isCreatedWithSchemaIs Created With Schema(1)

isLikeIs Like(1)

notHumanReviewedNot Human Reviewed(1)

plannedComponentPlanned Component(1)

plansToAddToPlans to Add to(1)

relatesToRelates to(1)

requestsShareRequests Share(1)

requiresRequires(1)

reviewsReviews(1)

shouldBeAppliedToShould Be Applied to(1)

targetTarget(1)

willIncludeSchemaWill Include Schema(1)

Other facts (42)

Timeline

References (21)

See also

Keep researching

Rdf:typein dispute`rdf:type`

`hasParameter`Has Parameter(6)

`hasSchema`Has Schema(4)

`isPartOf`Is Part of(2)

`locatedIn`Located in(2)

`serializesData`Serializes Data(2)

`shouldBe`Should Be(2)

`usesSchema`Uses Schema(2)

`about`About(1)

`assignedTo`Assigned to(1)

`believesSchemaNotReviewed`Believes Schema Not Reviewed(1)

`clarifiedRegarding`Clarified Regarding(1)

`considersReviving`Considers Reviving(1)

`createdWith`Created With(1)

`defines`Defines(1)

`describes`Describes(1)

`discusses`Discusses(1)

`ensuresCompatibility`Ensures Compatibility(1)

`equivalentTo`Equivalent to(1)

`handlesResponsibility`Handles Responsibility(1)

`hasNotSettledOn`Has Not Settled on(1)

`includesTag`Includes Tag(1)

`instantiatedWith`Instantiated With(1)

`isCreatedWithSchema`Is Created With Schema(1)

`isLike`Is Like(1)

`notHumanReviewed`Not Human Reviewed(1)

`plannedComponent`Planned Component(1)

`plansToAddTo`Plans to Add to(1)

`relatesTo`Relates to(1)

`requestsShare`Requests Share(1)

`requires`Requires(1)

`reviews`Reviews(1)

`shouldBeAppliedTo`Should Be Applied to(1)

`target`Target(1)

`willIncludeSchema`Will Include Schema(1)