Science Central Quick Start Guide

Getting Started with Science Central™

Platform Access

Navigate to: https://sc.emsl.pnnl.gov/
Dashboard: Access the All Modules view
Selection: Choose the appropriate tool for your research

Component Selection Guide

Choose Proposal Management when you need to:

Submit research proposals and letters of intent (LOI)
Track the status of submitted proposals
Manage user projects and experiments
Schedule experiments and instrument time
Access funding and collaboration opportunities
View and manage publication requirements

Choose Data Portal when you need to:

Search and discover scientific datasets
Access released datasets from completed projects
Browse MONet (Molecular Observation Network) data
Download datasets for analysis
Explore research data by project, instrument, or researcher
Find datasets to enhance your research findings

Choose Sample Submission (LIMS) when you need to:

Submit sample metadata for laboratory analysis
Track sample shipment and analysis status
Download metadata templates
Manage sample information and workflows
Access reviewer tables for sample status

Choose L7 Enterprise Science Platform when you need to:

Manage laboratory information systems
Track samples, projects, and workflows
Access comprehensive LIMS functionality
Monitor analysis progress and results
Manage laboratory inventory and equipment
Create and manage experimental workflows

Choose Circles when you need to:

Collaborate with other researchers
Share research findings
Connect with peers in your field
Participate in collaborative projects
Access shared resources and datasets

Choose Modeling Workbench when you need to:

Develop machine learning models
Perform statistical analysis with Python, R, or Julia
Train deep learning models with TensorFlow
Access high-performance computing resources
Run batch processing jobs

Choose Insight Engine when you need to:

Create data visualizations
Perform exploratory data analysis
Analyze multi-omics datasets
Use specialized bioinformatics tools
Build interactive dashboards

Quick Start Workflows

For Proposal Submission and Management

Getting Started with Proposals

Access: Select Proposal Management from the main menu
Login: Authenticate through NEXUS User Portal
Navigate: Use the dashboard to access key functions:
- Proposals/Projects: Submit new proposals and manage existing ones
- Schedule Experiments: Book instrument time and plan experiments
- Get Data: Access your experimental data and results
- Publications: Manage publication requirements and submissions
Submit: Click “Submit a Proposal/LOI” to start a new proposal
Track: Monitor proposal status and project progress through the dashboard

Key Features Available:

ORCID Integration: Link your ORCID profile for streamlined submission
Training Modules: Access required training for facility use
Reviews: Participate in the peer review process
Sample Status: Track sample processing (coming soon)

For Data Discovery and Access

Getting Started with Data Portal

Access: Select Data Portal from the main menu
Browse: Explore available datasets using multiple views:
- All Data: Browse complete dataset collection
- MONet: Access Molecular Observation Network datasets
Search: Use search functionality to find specific datasets:
- Search by project title, abstract, or ID
- Filter by released data, project, or instrument group
Select: Choose datasets of interest and review metadata
Download: Access and download datasets for your research

Dataset Information Includes:

Project Details: Principal investigator, project duration, institution
Data Volume: Number of uploads and total data size
Research Context: Project abstracts and research objectives
Data Policy: Access to data usage policies and guidelines

For Sample Management and LIMS

Getting Started with Sample Submission

Access: Navigate to LIMS → Sample Submission
Templates: Download metadata templates for sample preparation
Submit: Create new shipment applications with sample metadata
Track: Monitor shipment status and processing progress
Review: Access reviewer tables for detailed sample information

Getting Started with L7 Platform

Access: Navigate to LIMS → L7 for comprehensive laboratory management
Dashboard: View key metrics and recent activity
Manage: Access various laboratory functions:
- Entities: Register and manage laboratory entities
- Samples: Track sample workflows and status
- Projects: Manage experimental projects
- Analysis: Monitor analytical processes
- Inventory: Manage laboratory inventory
- Equipment: Track instrument usage and maintenance

Key L7 Capabilities:

Workflow Management: Design and execute analytical workflows
Data Integration: Connect sample metadata with analytical results
Quality Control: Monitor analytical quality and compliance
Collaboration: Share data and workflows with team members

For New Data Science Users

Getting Started with Python Analysis

Access: Select Modeling Workbench → Data Science
Environment: JupyterLab will open with Python 3 kernel
Create: New notebook for your analysis
Libraries: Pre-installed packages include pandas, numpy, matplotlib, seaborn
Data: Upload data through the file browser
Analysis: Begin with exploratory data analysis

Sample Python Code to Get Started:

import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import seaborn as sns

# Load your data
df = pd.read_csv('your_data.csv')

# Basic exploration
print(df.head())
print(df.describe())
print(df.info())

# Quick visualization
plt.figure(figsize=(10, 6))
df.hist(bins=20, figsize=(12, 8))
plt.tight_layout()
plt.show()

For Multi-omics Researchers

Getting Started with MAP

Access: Select Insight Engine → MAP
Upload: Use Data Upload to import your datasets
Explore: Browse MAP Store for relevant applications
Select: Choose application based on your data type and goals
Workflow: Design analysis workflow or use recommended pipeline
Monitor: Track progress through Job Status

Typical MAP Workflow:

Quality Control → Use PMart for initial data assessment
Differential Analysis → Apply statistical tests for group comparisons
Visualization → Create publication-ready figures with MODE
Integration → Combine datasets using iPMart (if multi-omics)
Machine Learning → Apply SLOPE for predictive modeling (if needed)

For High-Performance Computing Users

Getting Started with Tahoma OnDemand

Access: Select Modeling Workbench → Tahoma OnDemand
Dashboard: Open OnDemand interface shows available applications
Resources: Choose between Cluster Desktop, Jupyter, or RStudio
Jobs: Submit computational jobs through the job scheduler
Monitor: Track job progress and resource usage

Common Tasks

File Management

Upload: Use file browser upload buttons in each environment
Organization: Create folders to organize your work
Sharing: Set appropriate permissions for collaborative projects
Backup: Download important results regularly

Collaboration

Sharing Notebooks: Export and share analysis notebooks
Team Access: Invite collaborators to shared workspaces
Version Control: Use Git integration where available
Documentation: Maintain clear documentation of your work

Troubleshooting

Common Issues and Solutions

Issue: Cannot access Proposal Management

Solution: Ensure you have valid EMSL user credentials
Alternative: Check ORCID integration and profile completion
Contact: User Office at uo@emsl.pnnl.gov for account issues

Issue: Data Portal search not returning results

Solution: Clear search filters and try broader search terms
Alternative: Use “All Data” tab and browse by category
Contact: Data management team for specific dataset questions

Issue: Sample submission templates not downloading

Solution: Check browser settings to allow downloads
Alternative: Try different browser or contact support
Contact: LIMS support for template and submission issues

Issue: L7 Platform login or access issues

Solution: Verify EMSL credentials and project permissions
Alternative: Clear browser cache and retry login
Contact: L7 administrator for platform-specific issues

Issue: Cannot access environment

Solution: Clear browser cache and try again
Alternative: Try different browser or incognito mode
Contact: sc.support@pnnl.gov if problems persist

Issue: Kernel connection problems

Solution: Restart kernel from Kernel menu
Alternative: Refresh browser page
Prevention: Save work frequently

Issue: Out of memory errors

Solution: Process data in smaller chunks
Alternative: Use Tahoma OnDemand for larger datasets
Optimization: Remove unnecessary variables and objects

Issue: Package not available

Solution: Install using pip or conda in terminal
Alternative: Request package installation from support
Documentation: Check environment-specific package lists

Performance Tips

For Data Science Environment

Memory Management: Clear unused variables with del variable_name
Chunk Processing: Process large datasets in smaller pieces
Vectorization: Use pandas/numpy vectorized operations
Visualization: Use sample data for initial plot development

For TensorFlow Environment

GPU Usage: Monitor GPU memory utilization
Batch Sizes: Adjust batch sizes based on available memory
Model Checkpoints: Save model checkpoints regularly
Data Loading: Use efficient data loading pipelines

For MAP Applications

Data Preparation: Ensure data is in correct format before upload
Workflow Planning: Design complete workflow before execution
Resource Estimation: Consider computational requirements
Result Management: Organize outputs systematically

Best Practices

Proposal Management

Preparation: Complete ORCID profile before submitting proposals
Documentation: Maintain clear project descriptions and objectives
Deadlines: Submit proposals well before deadline dates
Follow-up: Regularly check proposal status and respond to reviews
Training: Complete required safety and instrument training

Data Management

Discovery: Use Data Portal to avoid duplicating existing research
Citation: Properly cite datasets used in your research
Metadata: Provide comprehensive metadata for your own datasets
Access: Understand data policies before downloading datasets
Sharing: Follow EMSL guidelines for data sharing and publication

Sample Management

Templates: Always use current metadata templates for submissions
Preparation: Prepare samples according to EMSL guidelines
Tracking: Monitor sample status through submission system
Communication: Maintain contact with facility staff during processing
Quality: Ensure sample quality meets analysis requirements

Laboratory Information Management

Workflows: Design clear, reproducible analytical workflows
Documentation: Maintain detailed records of all procedures
Quality Control: Implement appropriate QC measures
Data Integrity: Ensure accurate data capture and storage
Compliance: Follow all facility and regulatory requirements

Collaboration

Communication: Use clear communication with team members
Sharing Protocols: Establish data sharing agreements
Attribution: Properly credit collaborators and data sources
Reproducibility: Ensure analyses can be reproduced by others

Advanced Features

Custom Environments

Package Installation: Install additional Python/R packages
Environment Configuration: Customize computing environments
Docker Integration: Use custom Docker containers when needed
Resource Scaling: Access additional computing resources as needed

API Access

Programmatic Access: Use APIs for automated workflows
Integration: Connect with external tools and platforms
Batch Operations: Automate repetitive tasks
Data Pipelines: Create automated analysis pipelines

Support Resources

Documentation

Platform Guides: Comprehensive documentation for each component
Tutorials: Step-by-step instructional materials
User Guides: Specific documentation for Proposal Management, LIMS, and Data Portal
Best Practices: Methodology recommendations
FAQ Resources: Answers to common questions at https://www.emsl.pnnl.gov/user-program/faqs

Contact Information

General Support: sc.support@pnnl.gov
User Office: uo@emsl.pnnl.gov (for account and proposal questions)
Data Management: Contact through Science Central platform
LIMS Support: Available through L7 platform help system
Emergency Contact: 24/7 facility operations support available

Getting Help

In-Platform Help: Use the “How can I help you?” chat feature
Documentation: Access comprehensive guides for each platform
Training Resources: Complete online training modules
User Community: Connect with other researchers through Circles
Direct Support: Contact appropriate support team for specific issues

Science Central™ provides integrated access to world-class scientific computing, data management, and collaboration tools. Start with the appropriate platform for your research needs and expand to other tools as your project develops.