Short answer

Prioritize stable, core data elements and streamline data management processes to improve operational efficiency and the frequency of updates in complex systems.

Field: Commercial Production
Source: Nucleic Acids Research (2015)
Method: Database re-organization and comparative analysis.
Evidence: Strong effect

Reorganizing a large-scale biological database around reference proteomes significantly reduces manual curation effort and enables more frequent, sustainable releases. This commercial production research insight is drawn from a 2015 study published in Nucleic Acids Research. Using Database re-organization and comparative analysis., researchers explored how this design variable affects real-world outcomes. The key design takeaway: Prioritize stable, core data elements and streamline data management processes to improve operational efficiency and the frequency of updates in complex systems.

Study

Commercial ProductionHigh ImpactStrong effect

Streamlining Database Releases Enhances Efficiency and Sustainability

Reorganizing a large-scale biological database around reference proteomes significantly reduces manual curation effort and enables more frequent, sustainable releases.

Nucleic Acids Research · 2015

Key Findings

01Building families on reference proteomes provides greater stability, reducing manual curation needs.
02Restricting reported data to reference proteomes decreases website complexity while retaining access to key model organisms.
03Removal of the Pfam-B supplement streamlined the database.
04The re-organization enabled more frequent releases.

Application

Design takeaway

Prioritize stable, core data elements and streamline data management processes to improve operational efficiency and the frequency of updates in complex systems.

How to apply

Evaluate your project's data architecture. Identify core, stable data elements and explore ways to reduce the maintenance burden associated with less stable or redundant data. Consider streamlining reporting to focus on essential information.

Project actions

01When designing a system, think about which data is most critical and stable.
02Consider how to simplify the system by removing unnecessary features or data.

Method & Evidence

AimHow can the organizational structure of a large, complex database be optimized to reduce maintenance overhead and facilitate more frequent updates?

MethodDatabase re-organization and comparative analysis.

ProcedureThe Pfam database was re-organized to primarily utilize UniProtKB reference proteomes. This involved restricting the reported counts of matched sequences and species to this curated subset, while still maintaining access to the full UniProtKB database. The automatically generated Pfam-B supplement was also removed.

ContextBioinformatics and biological database management.

Variables

IVDatabase re-organization strategy (focus on reference proteomes, removal of Pfam-B).

DVFrequency of releases, manual curation effort required.

Strengths & Limitations

Strengths

+Demonstrates a clear link between structural changes and improved efficiency.
+Addresses the practical challenge of maintaining large, evolving datasets.

Limitations

The specific context of biological databases might limit direct application to other fields. The process of re-organization itself requires significant upfront effort.

Reliability & validity

The study's findings are based on the internal re-organization of a specific database, making direct replication challenging. However, the principles of data management efficiency are generally applicable.

Think critically

What are the potential trade-offs of focusing solely on reference proteomes, and how might this impact users who rely on the full, broader dataset?

Design Principles

"Data system efficiency is enhanced by focusing on stable core datasets and eliminating redundancy."

This approach demonstrates how strategic data management and a focus on core, stable datasets can lead to more efficient operational workflows. By reducing the complexity and volume of data requiring constant maintenance, organizations can allocate resources more effectively and improve the timeliness of their outputs.

What This Means for Your Design

Making a big database easier to manage by focusing on the most important, stable parts means it can be updated more often and requires less work.

How to use in your project

1.Use this to justify decisions about data management or system simplification in your design project.

Add to My Project

Quick Cite

Paragraph starter

The re-organization of the Pfam database, by focusing on UniProtKB reference proteomes and removing redundant components, demonstrated a significant improvement in operational efficiency. This strategic data management approach reduced manual curation effort and enabled more frequent releases, highlighting the benefits of prioritizing stable core datasets in complex information systems.

Source

Nucleic Acids Research

The Pfam protein families database: towards a more sustainable future

journal · 2015

View source

Questions About This Research

What does the research say about streamlining database releases enhances efficiency and sustainability?: Prioritize stable, core data elements and streamline data management processes to improve operational efficiency and the frequency of updates in complex systems. Evidence: Nucleic Acids Research (2015).
Why does "Streamlining Database Releases Enhances Efficiency and Sustainability" matter for design?: This approach demonstrates how strategic data management and a focus on core, stable datasets can lead to more efficient operational workflows. By reducing the complexity and volume of data requiring constant maintenance, organizations can allocate resources more effectively and improve the timeliness of their outputs.
How can designers apply this research?: Prioritize stable, core data elements and streamline data management processes to improve operational efficiency and the frequency of updates in complex systems.
What were the main findings?: Building families on reference proteomes provides greater stability, reducing manual curation needs.. Restricting reported data to reference proteomes decreases website complexity while retaining access to key model organisms.. Removal of the Pfam-B supplement streamlined the database.. The re-organization enabled more frequent releases.
What research method was used?: Database re-organization and comparative analysis..
How strong is the evidence?: Evidence strength is rated Strong effect, based on a 2015 journal from Nucleic Acids Research.
What should I do differently in my next project?: Evaluate your project's data architecture. Identify core, stable data elements and explore ways to reduce the maintenance burden associated with less stable or redundant data. Consider streamlining reporting to focus on essential information.
What are the limitations?: The study focuses on a specific type of database (biological sequence data) and may not be directly applicable to all data management contexts. Some entries with no matches to reference proteomes remained, requiring ongoing work.