Data Templates Overview

Data Templates define how results are captured and structured in Albert. This article explains what Data Templates are, when to use them, how to create and configure them (including units and validation), how to connect them to scripts for automation, and best practices and troubleshooting tips.

On this page

• 📘 Overview: What Data Templates Are & When to Use Them

• 🧩 Creating Data Templates

• 🛠️ Configuring Results, Units, Data Types & Validation

• 📎 Pre-linking Parameters

• 🤖 Script Automation

• 🌍 Manage Translations

• ✅ Best Practices

• 🩺 Troubleshooting

• ❓ FAQ

Data Templates are structured layouts that define which results and (optionally) parameters are captured for a given type of experiment or test. They represent the standardized output of an experiment in Albert.

🎯What Data Templates help with

• ✓ Consistent results
  Capture data in the same way across runs, teams, and locations.

• ✓ Reusable structures
  Turn frequent tests into templates you can apply again and again.

• ✓ Structured entries
  Use units and validation rules so data stays clean and comparable.

• ✓ Less manual work
  Automate data capture with scripts instead of copy-and-paste.

🧪Use Data Templates when…

• ✓ You repeatedly run the same type of experiment and want consistent, comparable results.

• ✓ Your test follows a standard method (e.g., ASTM, ISO) and the output must match that structure.

• ✓ Multiple colleagues or sites need to compare results across runs or locations.

• ✓ You want to automate data entry from instruments or files into Property Tasks.

Typically, only certain users—such as an Albert Champion or Albert Administrator—can create or edit Data Templates. If you need a new template or changes to an existing one, contact one of these users.

Start from the Global Create button, give your template a clear name and description, and select the first set of results you want to capture.

🧾Define the basics

• 1 Use a specific name including property, conditions, and method (e.g. “Viscosity – 25°C – ASTM D445”).

• 2 Add a short description explaining when and why the template is used.

📚Connect to standards & results

• 3 Link to ASTM, ISO, or internal methods via the Organization / Standard field.

• 4 Select or create the result columns you want in the template output.

1. Click the Global Create button at the top of your Albert screen.

2. In the modal, choose Data Template.

3. Fill in the name, description, and (optionally) Organization / Standard.

4. Under Results, search and select existing result definitions, or type to create new result columns.

5. Click Create. The template opens so you can configure the details.

💡 Tip: If a similar template already exists, duplicate it and adjust name, description, and results instead of starting from scratch.

After creating your Data Template, refine each result column with units and data types so entries are consistent, readable, and ready for analysis.

📏Units

• ✓ Set a unit for each result (e.g. wt%, °C, Pa·s).

• ✓ Units appear in the column header and keep interpretation consistent.

✅Data types

• TText for free-form entries.

• #Numeric for numbers only.

• ƒFunction for calculated values.

• ▾Dropdown for predefined options.

• 🖼️Image for structured image uploads.

• 📈Curve for continuous series (e.g. time–voltage or temperature–property curves).

📐Consistent units in every column

For every result column, pick the unit that matches the value being recorded. This keeps results comparable across experiments and locations.

• 1 Open the Data Template that you want to configure.

• 2 Click the unit selector in the result column header.

• 3 Choose the appropriate unit, such as wt% for “Component A” or °C for “Temperature”. Other examples include Pa·s or your org-specific units.

🧪Make entries clean & machine-readable

Data types control what can be entered in each column so results stay consistent and ready for analysis.

• N Set “Temperature (°C)” to Numeric so entries like “room temp” are blocked, while values like 25 are accepted.

• ƒ Use Function columns when a value should be calculated (e.g. averages or deltas) so Albert computes it directly in the template instead of external tools.

• ▾ Choose Dropdown when only a limited set of values should be allowed (e.g. “Pass / Fail”, a 1–5 score, or grade levels).

🖼️Capture images as structured results

Set a result’s data type to Image when you want users to upload pictures as part of the result (for example, microscope images, plate photos, or visual checks).

• 1 Change the result’s data type to Image in the Data Template.

• 2 Users can upload one or more images directly into that result when working in tasks or worksheets.

• 3 The images will appear in the Task view, in Reports, and in the result grid in the worksheet.

✨ Tip: Pair images with a simple classifier score (e.g. 1–5) stored in a Dropdown or Numeric result. This keeps images for review and structured numbers for predictive capabilities with Breakthrough.

📈Capture continuous measurements as curves

Use the Curve data type when your results are measured continuously over an axis (for example time, temperature, or frequency) instead of as a single summarized value.

• 1 Configure which columns in the CSV act as the X- and Y-axes in the Data Template (for example time vs. voltage).

• 2 Users upload curve files directly from Tasks; Albert stores the full curve, not just summary points.

• 3 Clicking a curve file opens an instant curve report using the axes defined in the Data Template.

Current limitations: Curve data caps discrete data entry at 1000 rows, only supports curves from a single CSV at a time (no cross-sample overlays yet), and is not yet available in calculations. Future releases will add richer overlays and reporting for continuous data.

Parameters capture the conditions of the test (e.g. temperature, instrument). Pre-linking them to a Data Template ensures this context is always collected.

🌡️Typical Parameters

• ✓Temperature, humidity, pressure.

• ✓Instrument or method version.

• ✓Sample ID, batch or lot.

🧩Why pre-link?

• 1Reduce manual setup for each new task.

• 2Ensure key conditions are always captured.

• 3Standardize context across teams and sites.

1. Open the Data Template you want to configure.

2. Add individual Parameters.

3. Mark critical Parameters as required if tasks must not be created without a value.

When someone creates a Property Task using this Data Template, all pre-linked Parameters appear automatically, saving setup time and preventing missing context.

Important: If a Parameter is marked required, task creation will be blocked until a value is provided.

Script Automation lets you attach Python scripts to Data Templates to transform raw data (for example from instruments or files) into structured results in Property Tasks.

For a deeper dive, see: Script Automation with Data Templates.

📥Typical inputs

• ✓Instrument exports (CSV, Excel, proprietary formats).

• ✓Other raw data files from lab equipment.

📤Typical outputs

• 1Filled-in result columns mapped from the source data.

• 2Derived metrics and calculations stored as results.

• 3Consistent formatting and units for downstream analysis.

1. Open the Data Template you want to automate.

2. Go to the Script / Automation section.

3. Click Upload Python Script.

4. Select your .py file and upload it.

Scripts turn repetitive, error-prone data entry into a fast, reliable pipeline from instruments to structured results.

⚡Less manual work, cleaner data

• 1 Automated data capture
  Pull instrument exports directly into the right result columns instead of copy-pasting.

• 2 Improved accuracy
  Reduce transcription errors and mismatched units by letting the script handle parsing and mapping.

🚀Smarter, scalable workflows

• 3 Custom transformation
  Clean, reshape, and calculate exactly what your team needs using your own Python logic.

• 4 End-to-end automation
  Connect data generation, processing, and analysis so results are ready to use as soon as tasks are completed.

• 5 Scale
  Handle large batches and complex datasets with the same effort as a single run.

If you want to use script automation but don’t have Python expertise, reach out to your Albert Administrator or your Albert representative.

Use translations to make the same Data Template usable for teams in different languages, without duplicating templates.

🔍Why translate?

• ✓ Make templates easier to find in search and views for non-English users.

• ✓ Reduce duplication of templates across regions.

🤝What gets translated

• 1Data Template name.

• 2Result column names.

• 3Parameters and Parameter Groups.

1. Open the Data Template you want to localize.

2. Navigate to the Manage Translations page.

3. For each available language, provide translations for the template name, result names, and any linked Parameters or Parameter Groups.

Users will see these translated values in tasks, search results, and other places in Albert, making templates easier to find and understand.

The languages you see under Manage Translations are currently supported. To request additional languages, contact your Albert representative.

Use these practices to keep your Data Templates reliable, reusable, and easy for colleagues to work with.

📐Design

• 1 Align templates with ASTM, ISO, or internal methods where applicable.

• 2 Use clear names and descriptions instead of generic titles.

• 3 Create separate templates for distinct test types rather than one catch-all.

🧼Data quality

• ✓Set units for each result and keep them consistent.

• ✓Use appropriate data types (Numeric, Text, Dropdown, Function, Image, Curve).

• ✓Mark critical Parameters and results as required.

♻️Lifecycle

• 1 Pilot new templates with a small group before full rollout.

• 2 Document what scripts do and what inputs they expect.

• 3 Review templates periodically to keep them aligned with current processes.

Use these quick checks to diagnose common issues before escalating.

🔐Access & structure

• A Can’t create or edit templates: check your role (e.g. Champion, Administrator) and contact your Albert Administrator if needed.

• B Missing result names: try alternate spellings or ask an admin to create the definition.

⚙️Validation & automation

• V Data won’t save: make sure values match the column type (numeric vs text vs dropdown vs image vs curve).

• S Script issues: confirm the correct script is attached, check for errors, and verify input files match what the script expects.

• 🌐 Translations not showing: verify translations exist for the right language and your user language matches.

🚫Validation & saving errors

• 1 Check data type: Numeric columns only accept numbers.

• 2 Remove units from values: enter 25 instead of 25 °C in numeric fields.

• 3 Dropdowns: select one of the allowed options instead of typing free text.

• 4 Images: make sure you’re uploading a supported image file type for Image fields.

• 5 Curves: upload CSV files where the columns match the X/Y axes configured for the Curve result in the Data Template.

Quick answers to common questions about Data Templates.

👥Ownership & editing

• Q Who can create templates?
  Typically, Albert Champions or Albert Administrators.

• A Editing in-use templates:
  Changes affect future tasks. For major changes, duplicate the template and migrate users.

📊Usage & automation

• T Relation to Property Tasks:
  Tasks use Data Templates as the output structure for capturing results and parameters.

• I Images in results:
  Yes — set the data type to Image to store images in tasks, reports, and the worksheet result grid.

• 🤖 Do I need a script?
  No. Scripts are optional and mainly for automatically loading data from instruments or files.

← Return to Guide Overview · Need more help with Data Templates? Contact support.