MORPH |

Meta-Organized Research & Processing Hub

Empowering research with data, building the scientific foundation of the future.

Supporting “Digital Transformation to Accelerate Research”

We build sustainable data infrastructures that integrate seamlessly with on-site workflows, supporting the effective implementation and adoption of Electronic Lab Notebooks (ELNs).

Let’s start with a free consultation to discuss your current on-site challenges.

Vision.

Transforming Research Data into Assets.

Realizing a stress-free research environment where researchers can immerse themselves in their inherent creativity and critical thinking.

Mission.

Promoting “Effective DX” grounded in the reality of the experimental field.

By integrating with analytical instruments and laboratory automation, we provide next-generation infrastructure that balances “reducing the burden on researchers” with “strategic data utilization for management.”

Issue.

Are you facing difficulties balancing “Ideal DX” with “On-site Operations”?

While the importance of Research DX is understood by many companies, there are significant hurdles to establishing it in actual operations.

  • The Gap between Goals and Practice: Organizations aim for “data accumulation and utilization,” but daily experimental tasks take priority on-site, often causing data entry to be postponed.

  • Tool Adoption Challenges: Even with high-functionality systems, if operation rules burden the field, data fails to accumulate, or reliance on individual skills remains unresolved.

  • The Dilemma of DX Managers: Many DX managers struggle to design operational flows that bridge the gap between “organizational goals” and “on-site reality.”

Analysis.

Why is it difficult for general IT solutions to take root in the “Experimental Field”?

Because the chemical and materials research process is a “continuous trial and error,” unlike typical business flows that are easily standardized.

  • Specificity of Research Processes: In Materials Informatics and chemical experiments, condition screening and sudden changes are common, generating non-standardized data daily.

  • System Mismatch: General efficiency systems often assume “fixed procedures.” In research fields requiring flexibility, this can conversely increase data entry man-hours.

What is needed is not forcing people to fit IT systems, but an approach where digital tools adapt to the “researcher’s natural thinking and experimental flow.” We believe that system design based on this “on-site research intuition” is key to successful DX.

Solution.

DX design that “convinces the field,” made possible by active researchers working alongside you.

MORPH is a Research DX specialized solution partner born from a laboratory at the Nara Institute of Science and Technology (NAIST). A team well-versed in both “Experimental Science” and “Information Science” will accompany you in solving your challenges.

  • Researcher-Centric UI/UX Design: We design templates tailored to experimental processes so researchers can record data without stress.

  • Start Small, Grow Big: Instead of immediately introducing expensive systems, we utilize the open-source “eLabFTW” to realize a minimum and flexible start.

  • Data Design with the Future in Mind: We support the construction of reusable data structures (FAIR data) premised on future connection to Materials Informatics (MI) and laboratory automation.

Service.

Phase-based Support & Integrated Solutions using the Electronic Lab Notebook “eLabFTW” 

We provide insights from NAIST in clear packages that are easy to utilize in business settings.

Member.

Owner: Shogo Takasuka

  • < Experimental Scientist > Assistant Professor, NAIST / Former Researcher at a Resin Manufacturer / Ph.D. (Engineering)

  • Promoting Research DX using eLabFTW. Engaged in machine learning using automated experimental equipment.

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ORCID

Technical Partner: Jemyung Lee 

  • < Information Scientist > Postdoctoral Researcher, DSC / Ph.D. (Engineering)

  • In charge of overall system development using the eLabFTW API. A specialist in optimizing research through data management and machine learning.

researchmap
ORCID

Contact.

Send us mail