conref.md

copyright	lastupdated	subcollection	content-type
years 2019, 2024	2024-04-10	discovery-data	conref

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Content references for overview subcollection

{: #conref}

Supported data sources

{: #data-sources-reuse}

The following table shows the supported data sources for each deployment type.

Data source	IBM Cloud	IBM Cloud Pak for Data
Box
Database (IBM Data Virtualization, IBM Db2, Microsoft SQL, Oracle, Postgres)
FileNet P8
HCL Notes
IBM Cloud Object Storage
Local file system
Salesforce
Microsoft SharePoint Online
Microsoft SharePoint On Premises
Website
Microsoft Windows file system
{: row-headers}
{: class="comparison-table"}
{: caption="Supported data sources" caption-side="top"}
{: summary="This table has row and column headers. The row headers identify supported data sources. The column headers identify the different product deployment type options. To understand which data sources are available for your deployment type, go to the row that describes the data source, and find the columns for the type of deployment you're interested in."}

Project descriptions

{: #projects-reuse}

Need	Goal	Project type
I want to extract data to support automation of repetitive document processing tasks.	I want to understand quickly what data is extracted from my documents and improve the data by applying enrichments.	Intelligent Document Processing
Which document contains the answer to my question?	Find meaningful information in sources that contain a mix of structured and unstructured data, and surface it in a stand-alone enterprise search application or in the search field of a business application.	Document Retrieval
Where is the part of the contract that I need for my task?	Quickly extract critical information from contracts.	Document Retrieval for Contracts
I want the chatbot I'm building to use knowledge that I own.	Give a virtual assistant quick access to technical information that is stored in various external data sources and document formats to answer customer questions.	Conversational Search
I want to uncover insights I didn't know to ask about.	Gain insights from pattern analysis or perform root cause analysis.	Content Mining
{: caption="Project type use cases" caption-side="top"}

Default enrichments per project type

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Some prebuilt enrichments are applied automatically to collections in a project based on the project type. The following table shows the default enrichments that are applied to each project type.

Enrichment	Document Retrieval	Document Retrieval for Contracts	Conversational Search	Content Mining
Contracts
Entities
Keywords
Part of Speech
Sentiment of Document
Table Understanding
{: row-headers}
{: class="comparison-table"}
{: caption="Default enrichments per project type" caption-side="top"}
{: summary="This table has row and column headers. The row headers identify project types. The column headers identify different enrichments. To understand which enrichments are applied to a project type by default, go to the row that describes the enrichments, and find the columns for the project type that you are interested in."}

Basic project defaults

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Some enrichments and query result settings are applied to each project type by default.

Project type	Default enrichments	Default query result settings
Intelligent Document Processing	Entities	Facets (by Entity), Passages
Document Retrieval	Entities	Facets (by Entity), Passages
Document Retrieval for Contracts	Entities, Table Understanding, and Contracts	Facets (by Category, Nature, Contract Term, Contract Payment Term, Contract Type, Contract Currency, Invoice Buyer, Invoice supplier, Invoice Currency, Purchase Order Buyer, Purchase Order Supplier, Purchase Order Payment Term) and Table Retrieval
Conversational Search	None	Passages
Content Mining	Part of Speech	None
Custom	None	Passages
{: caption="Basic project defaults" caption-side="top"}

Webhook security

{: #webhook-security-reuse}

To authenticate the webhook request, verify the JSON Web Token (JWT) that is sent with the request. The webhook microservice automatically generates a JWT and sends it in the Authorization header with each webhook call. It is your responsibility to add code to the external service that verifies the JWT.

The system can generate a JWT based on the sample secret that you specify, and in the Authorization header, you can pass this system-generated JWT to the external application. If you specify a value in the header, then the webhook microservice sends that value to the external application instead of the JWT. {: note}

For example, if you specify sample secret in the Secret field of the Webhooks object in the Create collection{: external} or update collection{: external} APIs, you might add sample code such as the following in Node.js:

const jwt = require('jsonwebtoken');
...
const token = request.headers.authentication; // grab the "Authentication" header
try {
  const decoded = jwt.verify(token, 'sample secret');
} catch(err) {
  // error thrown if token is invalid
}

{: codeblock}

Data model of the ping event

{: #ping-event-reuse}

Following are the ping event parameters:

Parameter	Description
event	The event name is ping.
instance_id	The {{site.data.keyword.discoveryshort}} instance ID.
version	The {{site.data.keyword.discoveryshort}} API version in the format yyyy-mm-dd.
data	An object with the event information: url, events, and metadata. \n \n - url: The configured webhook endpoint (URL). \n \n - events: An array of event string values. The events in this array are sent to the webhook URL. \n \n - metadata: An object with information that is specific to the created webhook.
created_at	The date and time the event was created.
{: caption="Ping event" caption-side="top"}