'admin/dashboard.php', 'Data Owner' => 'data_owner/dashboard.php', 'Data Contributor' => 'data_hybrid/dashboard.php', 'Data User' => 'data_user/dashboard.php', ]; $homeLink = $homeMap[$role] ?? 'index.php'; $username = $_SESSION['username'] ?? null; $isDacStaff = ($role === 'DAC Staff'); ?>
User Guide

NIPH Data Sharing Platform

This guide walks you through the core workflows and responsibilities for all roles on the platform. Use the navigation bookmarks below to jump to the section that best matches your access level.

Quick Navigation

Getting Started

Account set-up, password resets, and general navigation.

DAC Staff Workflow

Managing users, data sources, permissions, and content.

Data Owner Workflow

Publishing datasets and reviewing contributor requests.

Data Contributor Workflow

Hybrid role balancing owner uploads with user-level data access.

Data User Workflow

Browsing catalogues and working with approved files.

R in JupyterHub

Running reproducible analyses inside the embedded notebook.

Getting Started

  1. Log in with the credentials issued by the Data Access Committee. Password resets are handled by DAC Staff from Manage Users.
  2. Review your dashboard. Every role receives a dedicated summary of tasks, quick actions, and usage trends.
  3. Use the left sidebar to switch between data management activities (such as permissions or uploads) and content pages (announcements, FAQ).
  4. Need assistance? Use the Contact Us administration page or the feedback tools to reach the support team.

DAC Staff Workflow

User Onboarding

  • Navigate to Manage Users > Add New User. Capture personal details, institutional affiliation, and select the appropriate role.
  • Assign R in JupyterHub access if analytical notebooks should be available to the account and confirm storage limits.
  • Record the requester or approving authority in the notes field to maintain an audit trail for each new account.
  • Reset passwords via the Reset Password action whenever necessary and confirm via email or phone for security.

Data Source Oversight

  • Use Manage Data Sources to view every dataset, inspect uploaded files, adjust statuses, or delete outdated content.
  • Curate classifications (data types, categories) in Manage Classifications so owners have consistent taxonomy options.
  • Review pending permission requests and audit usage from Manage Permissions. Tag sensitive requests for additional review.
  • Periodically export data source inventories as CSV/Excel for offline review with governance teams.

Content & Communication

  • Announcements, FAQs, slides, About Us copy, Contact Us responses, and (optionally) this user guide are edited from the Content Management section.
  • Utilize analytics on the admin dashboard to understand which owners and contributors are most active.
  • Create quarterly reports by combining dashboard analytics, download logs, and request approvals to support stewardship reviews.

Governance & Compliance

  • Ensure mandatory data sharing agreements are uploaded to the Documents repository and linked to relevant owners.
  • Monitor inactivity alerts to deactivate accounts that have not logged in within policy-defined windows.
  • Coordinate security reviews with IT—for example, confirming backups and retention policies align with institutional standards.

Data Owner Workflow

  1. Add or edit data sources from My Data Sources. Upload multiple supporting documents (questionnaires, protocols, etc.) and manage statuses.
  2. Monitor permissions in Data Permissions. Approve, reject, or revoke contributor access. All decisions are logged for auditing.
  3. Analyze usage using the owner dashboard’s cards and R in JupyterHub workspace. Only approved files are synchronized to your notebook folder.
  4. Keep metadata current so contributors can quickly understand dataset contents and documentation.

Before Publishing

  • Review data dictionaries for completeness and include variable-level descriptions where possible.
  • Confirm that personally identifiable information (PII) is removed or obfuscated consistent with ethics approvals.
  • Attach governance documents (IRB approvals, data sharing agreements) so contributors can quickly assess compliance requirements.

Ongoing Stewardship

  • Set reminders to review each active dataset quarterly, checking for updated versions or new documentation.
  • Collaborate with DAC Staff to respond to contributor questions logged through the platform.
  • Track downstream publications using your data and log citations in the dataset description for future users.

Data Contributor Workflow

Data Contributors operate as a hybrid between Data Owners and Data Users—they can publish datasets when delegated while also requesting, downloading, and analyzing data like a user.

  1. Browse or upload data depending on your remit. When uploading, include questionnaires, protocols, and supporting documents to aid reviewers.
  2. Track permission requests from My data Request. Status changes (Approved, Pending, Rejected) are visible at a glance.
  3. Review downloads in My Downloads to document how datasets are being used.
  4. Leverage R in JupyterHub when enabled. Approved files appear under datasources/user_{your_id} in the notebook workspace.

Acting as a Publisher

  • Coordinate with the designated Data Owner to ensure uploads follow agreed quality standards and naming conventions.
  • Use the Version Notes field to capture what changed with each upload so that reviewers understand the dataset evolution.
  • Flag sensitive variables in the metadata so DAC Staff can apply additional access controls if necessary.

Acting as a Data User

  • Prepare clear justifications when requesting access—describe the intended analysis, timelines, and expected outputs.
  • Maintain personal notes in My data Request to track correspondence or follow-up tasks for each dataset.
  • Document analytical steps in shared notebooks or reports so owners can understand how their data is being used.

Data User Workflow

  • Use Browse All Data to inspect catalogues, metadata, and available documentation before submitting requests.
  • Submit requests through My data Request and monitor approvals. Attach research proposals or ethics approvals when required.
  • Downloaders are tracked in My Downloads to aid reproducibility and reporting.
  • When notebook access is granted, approved datasets synchronize to the R in JupyterHub workspace automatically.
  • Share summaries or publications with Data Owners so they can evidence impact and update dataset narratives.

Responsible Use

  • Restrict downloads to secure, institutionally approved devices and storage locations.
  • Respect embargo periods or usage limitations noted in the dataset metadata.
  • Notify DAC Staff immediately if you suspect unauthorized access or data leakage.

Working with R in JupyterHub

  1. Launch the notebook from the sidebar entry. The interface opens inside the portal and can also be opened in a new tab.
  2. Approved files are mirrored (via symlink/copy) into your personal datasources/user_{id} directory. Review manifest.json to see which files were synced.
  3. Create new R notebooks via the Launcher, install libraries as needed, and export results back to the platform if required.
  4. Contact DAC Staff if additional packages or larger storage quotas are required for analysis.

Notebook Best Practices

  • Create a dedicated project folder per study and keep raw data read-only to avoid accidental overwrites.
  • Use renv or packrat to lock package versions for reproducibility.
  • Export cleaned datasets or figures back to the platform using the upload tools so collaborators can access them.
  • Set up scheduled clean-up of temporary files to stay within storage limits and keep the workspace responsive.

Data Lifecycle Overview

  1. Plan – Identify required datasets, confirm governance approvals, and align timelines across owners and contributors.
  2. Publish – Owners or contributors upload data, finalize metadata, and set initial access rules.
  3. Review & Approve – DAC Staff validate requests, confirm consent documents, and document decisions.
  4. Analyze – Users download, analyze in R in JupyterHub, and generate outputs while adhering to policy.
  5. Report – Teams share findings, update dataset records with impact summaries, and archive superseded files.

Support & Additional Resources

User Guide

Jump back to the top of this guide for role walkthroughs and checklists.

Need help?

Use the Contact Us administration page or reach out to the Data Access Committee via the official communication channels.

Security & Compliance

Follow institutional policies when handling restricted datasets. Audit trails (downloads, approvals) are logged for every action.

Training & Knowledge Base

Access recorded webinars, SOPs, and quick-reference guides from the Resources page in the portal.

Incident Response

For suspected breaches or data quality issues, escalate immediately through the Incident Report form so the DAC can coordinate remediation.