> For the complete documentation index, see [llms.txt](https://help.modelreef.io/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://help.modelreef.io/syntax/understanding-the-interface/data-library-viewer.md).

# Data Library Viewer

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### Opening the Data Library viewer

You can open the Data Library viewer from the main navigation or from links in the Variable or Driver Editor.

The viewer shows a table of entries, typically with columns such as:

* Name.
* Type (Variable, Driver, Modifier, Custom).
* Category and subcategory.
* Branch usage or links.
* Source (manual, import, Xero, QuickBooks, ticker, CSV).
* Forecast method (manual, regression, ML).

From here you can inspect and edit shared assumptions.
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### What lives in the Data Library

Entries include:

* Imported historical series from PDF, Excel, CSV, Xero, QuickBooks and stock tickers.
* Manually created drivers and assumptions.
* Shared variables used across branches.
* Modifiers for discount rates, FX or scenario adjustments.

Each entry represents a time series or rule set that can feed one or more variables.
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### Browsing, search and filters

The viewer provides tools to:

* Search by name, tag or category.
* Filter by type, for example only drivers or only imported series.
* Filter by source, to see for example all Xero mapped entries.
* Sort by name, last updated or other fields.

Use these tools to quickly find the assumptions you want to review or change.
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### Editing entries and downstream impact

When you open a Data Library entry you can:

* Change its name, type, category or frequency.
* Edit values directly or update the forecast method.
* Attach notes and supporting documents.
* Adjust which branches or variables reference it.

Any change to an entry:

* Updates all variables that use that entry.
* Reflows into P\&L, Balance Sheet, Cashflow and valuations.
* Updates dashboards and custom charts that depend on the series.

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Because edits propagate throughout the model, changes in the Data Library should be deliberate and documented.
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### Using the Data Library for central assumptions

You can use the Data Library to centralise assumptions such as:

* Wage inflation rates.
* General operating cost inflation.
* FX rates.
* Global discount rate modifiers.
* Core unit prices or tariff levels.

Variables and formulas then reference these entries instead of hard coding values, making it easy to update them in one place.
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## Related articles

* [Seasonality Inputs](/syntax/timing-syntax/seasonality-inputs.md)
* [Selecting Drivers in Sidebar](/syntax/formula-syntax/selecting-drivers-in-sidebar.md)
* [Key Entities (Variables, Drivers, Branches)](/help/getting-started/key-entities-variables-drivers-branches.md)
* [Build a Central Assumption Library](/how-tos/data-workflows-and-automation/build-a-central-assumption-library.md)