数据治理
与 CAS Custom Services℠ 合作,理清贵组织的数据布局,并为强大的数据分析建立安全的基础。
与 CAS Custom Services℠ 合作,理清贵组织的数据布局,并为强大的数据分析建立安全的基础。

Scientific organizations accumulate decades of valuable data, but without a structured governance framework, that data becomes a liability rather than an asset.
Inconsistent standards, restricted access, poor version control, and ungoverned data flows create compliance risk, slow decision-making, and undermine the reliability of AI and analytics initiatives.
CAS brings scientific expertise and proven knowledge management capabilities to help organizations build data governance frameworks that are structured, secure, and scalable.
We evaluate your current data landscape, identifying governance gaps, compliance exposures, and opportunities to improve data discoverability.
按钮文本We design and implement custom knowledge management platforms, data standards, and access control frameworks for your unique data environment. This includes digitizing physical documents and static files into searchable assets and creating tailor-made retrieval systems.
按钮文本Through tailored training, consultation, and ongoing support, your teams are set to succeed. Good data governance practices in day-to-day operations ensure a data-driven future.
按钮文本Most data governance providers bring technology frameworks and policy templates. We bring something harder to replicate: a century of curating the world's most authoritative collection of scientific data.
CAS understands the technology, the data, and the science.
We apply the same content and knowledge-management expertise behind CAS REGISTRY®, the world's largest collection of human-curated disclosed chemical substances, to your proprietary data.
Our scientists validate data quality, accuracy, and integrity at the point of ingestion, building a solid foundation for your knowledge management platform before governance frameworks are applied.
Well-governed data is necessary for a reliable AI model. Our data governance services ensure your scientific datasets are structured, standardized, and access-controlled, ready to power high-performing models and trustworthy analytics.
We provide the technical skills and ongoing guidance your teams need to maintain governance standards independently, ensuring long-term success beyond our partnership.
The challenge: Toray Industries' research scientists were spending significant time on data handling they weren’t equipped to manage. Without a strong data governance framework, insights were locked in silos across the organization, slowing R&D innovation and limiting informatics capabilities.
The solution: We delivered a tailored training program led by scientific and technical experts, educating Toray's researchers on the core principles of curating and managing complex scientific data. Through deep consultative engagement, we helped Toray shift from indiscriminate data collection to a deliberate, structured approach, laying the foundation for predictive R&D.

“清楚地了解哪些数据可以使用至关重要。你需要能够利用可用信息来减少工作量和加快流程。”
Every science-driven industry faces its own data governance pressures. We deliver data governance services built around the specific regulatory requirements, data complexity, and knowledge management challenges your sector faces.
Establish structured frameworks that ensure data integrity across the R&D lifecycle, support audit-ready regulatory submissions, and protect sensitive clinical and preclinical knowledge assets.
Govern complex, high-value genomics, diagnostics, and therapeutic data consistently, ensuring it is accessible, protected, and ready to accelerate discovery.
Bring structure and consistency to large volumes of trial, regulatory, and research data to support compliance and enable faster, more confident R&D decisions.
利用完全集成的数据提高可发现性,从而加快突破速度。欢迎与 CAS 定制服务专家合作,找到契合您的解决方案。
Data governance is the framework of policies, processes, and standards that organizations use to ensure their data is accurate, accessible, consistent, and secure. It defines who can access data, how it is structured and maintained, and how data quality is monitored over time, providing the organizational foundation on which reliable analytics, regulatory compliance, and AI initiatives depend.
Scientific research generates complex, high-value data that accumulates over decades across multiple systems, formats, and teams. Without a governance framework, that data becomes difficult to find, trust, and reuse, leading to duplicated experiments, compliance risk, and missed discoveries. Effective data governance ensures scientific knowledge is preserved, accessible, and reliable to support confident decision-making and regulatory submissions.
AI models require clean, consistently structured, and well-documented data to produce reliable outputs. Poor governance leads to inconsistent data standards, ungoverned data flows, and unreliable training datasets, all of which undermine AI performance regardless of model sophistication. Data governance services establish the structured, standardized foundation that high-performing AI and analytics initiatives require.
Data governance services typically include data landscape assessment, governance framework design, knowledge management platform implementation, access control and data security protocols, legacy document digitization, custom data curation, and staff training. CAS also provides ongoing consultation and support to ensure governance standards are maintained as organizations and their data environments evolve.
Data management covers the technical processes of collecting, storing, and maintaining data. Data governance defines the policies, standards, and accountability structures that govern how data is managed. In practice, data management handles the how, and data governance defines the what, who, and why. Strong governance ensures data management processes consistently produce data that is accurate, secure, and fit for use.
CAS combines proven governance frameworks with a century of scientific knowledge management expertise and the world's most authoritative collection of curated scientific data. Unlike generalist providers, CAS understands the underlying science, ensuring governance frameworks reflect the complexity of scientific data, not just the technical requirements of enterprise IT.


