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Your Environment. Your Health.

Laboratory I&IT

Rationale

DNA helix on blue background with lines of code

Laboratory I&IT is an integral component of science, and its infrastructure and policy impacts experimental, in silico, and clinical practice. I&IT systems compose, manage, and coordinate laboratory instrumentation, as well as laboratory processes. I&IT is also essential to generate, manage, and organize raw and derived data, as well as metadata that is critical for experimental reproducibility, research collaboration, and scientific innovation. Goals for laboratory data and metadata include robust backup and integrity, and governing principles that foster FAIR+ models. I&IT systems frequently have extended lifecycles, which demand legacy systems support. This delayed end of life impacts risk and change management policy and implementation, and demands robust asset management systems.

Goals

Support Diverse Lab I&IT Needs

  • Scientific needs, demands, and innovation will drive laboratory I&IT policy and implementation.
  • Laboratory I&IT systems and policy will support diverse NIEHS scientific needs, including heterogeneous infrastructure and data systems that support scientific innovation, productivity, and cross-platform integration.
  • Laboratory I&IT will support the scientific computing, instrumentation, and data needs of researchers separate from standard desktop support models.

Fit With I&IT Ecosystem

  • I&IT, infrastructure, and other support providers will communicate and collaborate with scientific stakeholders across laboratory I&IT project planning and systems implementation.
  • Laboratory I&IT systems will respond to, and integrate, scientific needs, including planning across I&IT security, the network, local and remote hardware, and software layers, to minimize system and maintenance costs and ensure that I&IT staff can deliver timely support. Agile support will be based on scientific needs.
  • Laboratory I&IT hardware, software, and integrated change and risk management will inform lifecycle planning, including end of life. Design and policy will accommodate legacy infrastructure.

Optimize Laboratory Data Practices

  • Laboratory I&IT data infrastructure and policy will ensure data accessibility, security, integrity, and provenance, and support and foster FAIR+ data principles.

Strategic Capability Priorities

Laboratory I&IT Support Systems Alignment

LAB-01

NIEHS will improve alignment of the network, data center, and other systems to diverse and domainspecific laboratory I&IT needs, including legacy systems, emphasizing usability, agility, and flexibility. I&IT instruments and systems depend on a well-designed and highly functional ecosystem. Scientific user satisfaction of support systems alignment will be evaluated. Status of current alignment is significantly heterogeneous, ranging from excellent to only partially existent.

Laboratory I&IT Facilities Alignment

LAB-02

NIEHS will enhance laboratory I&IT alignment and integration with laboratory facilities and space planning, renovation, and design. I&IT and laboratory space planning will be integrated under 360-degree understanding models. Strategic alignment of I&IT systems across lab space planning will ensure improved flexibility and effectiveness. I&IT and space alignment will be measured by scientific user acceptance and satisfaction, as well as cost-benefit optimization. Currently, NIEHS has little centralized understanding of the alignment of laboratory I&IT and laboratory space.

Laboratory Equipment Lifecycle

LAB-03

NIEHS will enhance support and responsiveness, proactive risk, and change management for laboratory instruments. Scientific instruments are increasingly computer-dependent and are at risk from changes to industry and technology practices, as well as government compliance mandates (operating system obsolesce, network security requirements, FITARA compliance). Ensuring continuity of scientific equipment functions is essential to laboratory operations and NIEHS strategic plan goals. Essential steps include strategic capacity planning and central determination, and management of costs, liabilities, and risks, as currently scientists and scientific management have little concept of the financial liability associated with obsolescence of systems running scientific instruments. Assessment will include an estimate of the institutional and individual laboratory cost of replacing or updating computer systems. NIEHS is insufficiently aware of these issues and is just beginning to work with lab staff to estimate scope. Significant effort remains.

Laboratory I&IT Asset Management

LAB-04

NIEHS will develop, deploy, and manage laboratory hardware and software asset management systems and associated infrastructure. Laboratory asset management systems will be aligned with enterprise asset management systems and include understanding of physical and logical relatedness and dependencies. Asset management is essential for I&IT support staff allocation, lifecycle planning, I&IT security management, and centralized auditing and reporting compliance. Asset management systems will be evaluated by improved I&IT support and scientific user efficiency and efficacy. Centralized laboratory asset management is currently operating under different systems that are not integrated and do not report consistent information. NIEHS has no current authoritative asset understanding.

Laboratory I&IT Support Optimization

LAB-05

Laboratory I&IT support staff will be optimized, including distributed domain expertise and incentivized retention. Proactive engagement, including I&IT wellness understanding will enhance support. I&IT needs must be understood and managed under different models than enterprise commodity I&IT. Domain expert I&IT support staff are critical for effective laboratory operations. Diverse experimental systems, instruments, and data needs are optimally supported under a collaborative expert support model. Staff support optimization will be assessed by scientific user satisfaction, in addition to standard quantitative metrics. A designated laboratory I&IT support staff system has been implemented. I&IT support delivery quality is heterogeneous, depending heavily on provider experience and training.

Laboratory I&IT Data Backup

LAB-06

Laboratory data backup and storage infrastructure will be aligned with laboratory I&IT practices and I&IT security and compliance mandates. Data backup practices will be enhanced, including systems modernization and scientific user training. Data backup will be auditable, and includes enhanced reporting of backup status, scientific user training, and backup wellness checks. Data backup strategies will be multifaceted, including system disaster mitigation and user error prevention. I&IT support staff will routinely inspect instrumentation for backup status. Laboratory data integrity is essential and integral to the scientific process. Backup systems and process status will be evaluated, by diminishing realized data loss and recovery efforts. Backup systems are currently technically robust but rely on user compliance with best practices. User training and wellness evaluations must be enhanced.

Laboratory I&IT Technology 360-Degree Training

LAB-07

head with colored gears insideNIEHS will implement 360-degree training for laboratory I&IT support staff and the scientific community. Expanded opportunities will be provided for relevant scientific domain-specific training for I&IT support staff, and technology training for scientists. Diverse cross-training will enhance I&IT support and improve scientific best practices. Training efficacy will be evaluated by quantitative surveys and trainee satisfaction. Training will be prioritized by cost-benefit analyses. Current cross-training opportunities are heterogeneous, but limited. Communication of existing training opportunities will be expanded.

Laboratory I&IT Analytics Training

LAB-08

NIEHS will enhance and expand laboratory data analytic methods training, as well as improve coordination with other groups providing training, including NIH. NIEHS-wide development methods and best practice training, including a recommended common framework(s), is critical (software engineering). Enhanced lab data analytic training is needed to provide researchers with specialized knowledge and skills to make the most of scientific data, and to foster effective and appropriate I&IT support of research. End user satisfaction will be measured by post-training surveys, program evaluation by divisional representatives, acceptance of best practices, standardization, and institution-wide coordination of development approaches. Training is currently heterogeneous and primarily ad hoc.

Improve Commercial Scientific Software Program

LAB-09

NIEHS will continue improvement of the commercial scientific software program, by modernizing titles and expanding scientist access to the software suite. Open source alternatives will be emphasized as appropriate. Training opportunities, improved communications, and fostering communities of practice will be enhanced. The increasing complexity of biomedical and environmental health science research data requires that scientists in all divisions have access to a wide range of scientific software tools, including commercial software to conduct critical research, as well as manage and interpret data. Total cost of ownership, specific use, and scientific user satisfaction will be evaluated.

Laboratory I&IT Data Practices

LAB-10

NIEHS will standardize laboratory I&IT metadata terms to ensure that appropriate experimental data sets can be readily interpreted, shared, and integrated (FAIR+) where applicable, particularly in core labs. A metadata catalog(s) that will serve as a central reference source for these terms will be implemented. Infrastructure supporting enhanced data sharing and interpretation will improve institute science by expanding data utility. Implementation will be initially evaluated on selected systems and then expanded based on user adoption and continuous feedback. Although some labs and cores are using standard metadata fields, NIEHS has inconsistencies in adoption of standard metadata terms within and across labs. Active collaborative support and intervention will be critical for success.

LIMS Implementation

LAB-11

NIEHS will expand and integrate Laboratory Information Management Systems (LIMS) for core Labs with an application programming interface(s) (API). Scientists, including core staff, will optimize time and effort spent on understanding, tracking, and reporting data. Enhanced data analytics, process optimization, and business logic will improve core efficiency, improve core resource allocation, ensure metadata retention, and enhance core accountability, transparency, and governance. Commercial LIMS supports diverse functions with differential utility and the institute is just getting started in LIMS implementation. NIEHS is lacking broader infrastructure, including granular sample tracking, barcoding, and label printing. LIMS implementation success will be evaluated by adoption and user satisfaction. For several cores, NIEHS has a reasonable understanding of differential requirements and how available tools can be applied before venturing into custom development.

Electronic Laboratory Notebook Implementation

LAB-12

NIEHS will implement user-friendly electronic laboratory notebooks (ELNs) that are integrated with other hardware and data resources. ELN adoption by individual researchers will improve data management and search, enable direct incorporation of instrument-generated data, improve metadata accuracy, and maximize data and metadata retention. Scientific user acceptance and satisfaction will drive ELN adoption, inform practices, and help determine status. NIEHS has not yet begun implementing ELNs, including market research and needs analysis that will align ELN implementation with institute needs.

Clinical/CRU I&IT Theme Map

I&IT Landscape Agility Analytics Communications & Transparency Foster Collaboration Governance Optimize Resources Workforce Development

Laboratory I&IT

LAB-02

LAB-03

LAB-09

LAB-10

LAB-12

LAB-06

LAB-01

LAB-04

LAB-11

LAB-05

LAB-07

LAB-08

See Appendix A: I&IT Priorities Support NIEHS Strategic Themes

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