Notice2026-20023
Request for Information (RFI) Regarding the Digitization and Modernization of the National Technical Reports Library (NTRL) and the Leveraging of Scientific, Technical and Engineering Information (STEI) Stored in the NTRL
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Published
September 30, 2026
Issuing agencies
Commerce DepartmentNational Technical Information Service
Abstract
The National Technical Information Service (NTIS) is seeking general information, feedback, suggestions, and experiential and technical insights from stakeholders to inform NTIS's goal of fully digitizing, modernizing, and enhancing the utility of the National Technical Reports Library (NTRL). NTIS has historically collected, indexed, abstracted, and stored U.S. Government-sponsored technical reports and made them available to the public through the NTRL. To further unlock the NTRL's intrinsic value, NTIS aims to digitize records that are part of the NTRL but currently exist only in physical formats. Leveraging the information archived within the NTRL may include making the data more accessible to AI and advanced computing applications. NTIS seeks to understand the opportunities, challenges, and priorities that may attend NTRL's efforts to modernize and make any resultant high-quality technical federal data sets publicly available.
Full Text
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<title>Federal Register, Volume 91 Issue 188 (Wednesday, September 30, 2026)</title>
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[Federal Register Volume 91, Number 188 (Wednesday, September 30, 2026)]
[Notices]
[Pages 61835-61837]
From the Federal Register Online via the Government Publishing Office [<a href="http://www.gpo.gov">www.gpo.gov</a>]
[FR Doc No: 2026-20023]
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DEPARTMENT OF COMMERCE
National Technical Information Service
[Docket No.: 260924-0004]
Request for Information (RFI) Regarding the Digitization and
Modernization of the National Technical Reports Library (NTRL) and the
Leveraging of Scientific, Technical and Engineering Information (STEI)
Stored in the NTRL
AGENCY: National Technical Information Service (NTIS), U.S. Department
of Commerce.
ACTION: Notice; request for information.
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SUMMARY: The National Technical Information Service (NTIS) is seeking
general information, feedback, suggestions, and experiential and
technical insights from stakeholders to inform NTIS's goal of fully
digitizing, modernizing, and enhancing the utility of the National
Technical Reports Library (NTRL). NTIS has historically collected,
indexed, abstracted, and stored U.S. Government-sponsored technical
reports and made them available to the public through the NTRL. To
further unlock the NTRL's intrinsic value, NTIS aims to digitize
records that are part of the NTRL but currently exist only in physical
formats. Leveraging the information archived within the NTRL may
include making the data more accessible to AI and advanced computing
applications. NTIS seeks to understand the opportunities, challenges,
and priorities that may attend NTRL's efforts to modernize and make any
resultant high-quality technical federal data sets publicly available.
DATES: Comments must be received by 11:59 p.m. Eastern Time on November
16, 2026. Submissions received after that date may not be considered.
ADDRESSES: Comments must be submitted electronically via the Federal e-
Rulemaking Portal (<a href="http://regulations.gov">regulations.gov</a>):
<bullet> To submit electronic public comments via the Federal e-
Rulemaking Portal.
1. Go to <a href="http://www.regulations.gov">www.regulations.gov</a> and enter NIST-2026-0166 in the search
field.
2. Click the ``Comment Now!'' icon and complete the required
fields.
3. Enter or attach your comments.
Comments containing references, studies, research, and other
empirical data that are not widely published should include copies of
the referenced materials. All submissions, including comments,
attachments and other supporting materials, will become part of the
public record and subject to public disclosure. Relevant comments will
generally be available on the Federal e-Rulemaking Portal at
<a href="http://www.regulations.gov">www.regulations.gov</a>. NTIS will not accept comments accompanied by a
request that part or all of the material be treated confidentially
because of its business proprietary nature or for any other reason.
Therefore, do not submit confidential business information or otherwise
sensitive, protected, or personal information, such as account numbers,
Social Security numbers, or names of other individuals.
NTIS will not accept comments for this notice by postal mail, fax,
or email. To ensure that NTIS does not receive duplicate copies, please
submit your comments only once.
Additional information on the use of <a href="http://regulations.gov">regulations.gov</a>, including
instructions for accessing agency documents, submitting comments, and
viewing the docket is available at: <a href="http://www.regulations.gov/faq">www.regulations.gov/faq</a>.
FOR FURTHER INFORMATION CONTACT: For questions about this notice please
contact: Bobby Khondker via email at <a href="/cdn-cgi/l/email-protection#11737e7373683f7a797e7f757a7463517f7862653f767e67"><span class="__cf_email__" data-cfemail="b2d0ddd0d0cb9cd9dadddcd6d9d7c0f2dcdbc1c69cd5ddc4">[email protected]</span></a> and
<a href="/cdn-cgi/l/email-protection#fd93898f91bd93948e89d39a928b"><span class="__cf_email__" data-cfemail="016f75736d416f6872752f666e77">[email protected]</span></a>, or by phone at (301) 873-2127.
SUPPLEMENTARY INFORMATION: NTIS operates the NTRL as a clearinghouse
for the collection and dissemination of federally-funded scientific,
technical, and engineering information (STEI). The NTRL hosts the
largest collection of U.S. government-sponsored technical reports, and
historically has collected, authenticated, indexed, preserved, and made
available to the public technical information generated through federal
research, contracts, grants, laboratories, and other government-
sponsored activities--including material that may never be published in
conventional academic journals.
Reports in the NTRL include detailed results of federally funded
research and development (R&D), which can contain technical details
that are often omitted from journal publications, such as: experimental
configurations and methods; performance characteristics and failure
modes; material properties and measurement results; prototype designs;
field-test results; engineering tolerances and assumptions; cost,
reliability, and manufacturability assessments; negative or
inconclusive results; contractor-developed methods and tools; and
recommendations for follow-on R&D. For technology developers, the
detailed results found in the reports can help establish the existing
state of the art, identify prior government investment, reproduce
earlier experiments, locate promising
[[Page 61836]]
but unfinished technology, and avoid repeating approaches that federal
research has already shown to be impractical.
Other available and valuable data in the NRTL include emerging-
technology assessments and horizon scanning (for example, the NTRL has
the Army's Emerging Science and Technology Trends: 2017-2047, which
examines artificial intelligence, quantum computing, additive
manufacturing, materials science, renewable energy, biotechnology, and
other emerging areas to inform strategic dialogue and future R&D
investments); technology-feasibility and technology-limitation studies;
materials science and advanced-manufacturing information; energy
technology and energy-infrastructure research; transportation,
aviation, and infrastructure engineering; computing, communications,
sensing, and control systems; health, environmental, and occupational-
safety research; standards, measurement, testing, and evaluation; and
historical technical baselines.
Currently the NTRL houses nearly 3 million records dating back to
the late 1920s and spanning more than 350 subject areas, from public
health and industrial medicine to aeronautics. Approximately 2 million
of these records were collected by NTIS prior to the widespread
adoption of the internet and related technologies and exist only in
non-digital formats, such as paper print, microform, tape, CDs and
DVDs. Due to budgetary constraints, NTIS has been unable to convert
many of these non-digital records into digital form. Bibliographic
information of all records contained within the NTRL and copies of the
reports that exist in digital format are available to the public free
of charge at: <a href="https://ntrl.ntis.gov/NTRL/">https://ntrl.ntis.gov/NTRL/</a>.
To advance its mission to make federally-funded STEI more
accessible to the public and unlock the maximum potential value of the
non-digitized records, NTIS is seeking input from the public on
processes and procedures for modernizing the NTRL, with a focus on
digitization.
NTIS is also seeking input on the various ways in which the
digitized NTRL and its technical data might be leveraged by the private
sector and scientific community to advance U.S. innovation, strengthen
America's cyber resilience, and spur economic growth.
This insight may inform NTIS' actions on increasing the efficiency,
scalability, automation, interoperability, and utility of the NTRL.
Respondents may choose to provide information on the topics below.
NTIS has provided the following non-exhaustive list of topics and
accompanying questions to guide respondents, and the submission of any
relevant information germane to the subject but that is not included in
the list of topics below is also encouraged. The inclusion of the
topics in this Notice is not intended to indicate a particular
relationship between them, nor are they intended to limit the topics
that may be addressed by the public. Respondents need not address all
questions in this Notice, though all responses should specify which
questions are being answered. All relevant responses that comply with
the requirements listed in the DATES and ADDRESSES sections of this
Notice will be considered.
I. Digitization Best Practices
A. General Logistics
1. When digitizing physical records, what chain-of-custody
frameworks or procedures might be utilized? How might the end-to-end
movement of physical records be managed in the travel from pickup,
transport to digitization site, digitization, quality verification, and
final destruction? What auditing or tracking procedures are helpful in
preventing loss, identifying poor digitization, and ensuring
regulation-compliant final destruction?
B. Physical Records (paper, microform, magnetic film, other legacy
media)
2. With regards to physical records that exist in the form of paper
documents, what technologies and processes might be utilized in the
digitization of a large-scale collection containing documents of
various ages? What factors inform the estimated cost of such an
endeavor, and at what speed might digitization occur?
a. What about in the case of microform (microfilm and microfiche)
records? How might these records differ from paper records in terms of
cost, throughput, and output quality?
b. What about for recovering data from legacy \1/2\-inch, 9-track
open-reel magnetic tapes? What are the primary risks of data loss or
degradation specific to this media type, and how should NTIS prioritize
recovery before further deterioration occurs?
3. What preparation steps might be necessary before digitizing
paper records of various ages? Are there certain preparation steps that
are necessary for documents from a particular era but not others? How
might these preparations steps, including deacidification, de-stapling,
and flattening, inform a project's overall cost and timeline?
a. In the case of microfilm, given variations in microfilm quality
over decades, what specialized pre-processing or image-enhancement
techniques are necessary to ensure high-accuracy OCR text extraction
from older or degraded film stock?
4. In dots per square inch (DPI), what image resolution settings
are recommended for paper documents, keeping in mind the balance
between file size, storage costs, and machine readability? Are
preferred image resolution settings different for documents intended
for AI training versus human readability?
5. When utilizing Optical Character Recognition (OCR) engines,
which document layout analysis tools or approaches have you found most
useful, and why? Are preferred tools and approaches different for
technical and scientific documents, such as those with mathematical
notation, chemical formulas, engineering diagrams, tables, headers,
footnotes, and multi-column layouts? What OCR confidence thresholds are
reasonable when digitizing paper records that are up to 60 plus years
old?
6. What tools and approaches are most useful when digitizing
documents containing complex technical diagrams, schematics, chemical
structures, or mathematical formulas, particularly with regard to
capturing both textual and visual elements? What are examples of the
practice of extracting tables and figures from such documents as
separate metadata objects, and under what circumstances is this
practice being utilized?
7. When digitizing a paper dataset for use in AI training, which
digital file formats have been found to be best-suited, and why?
8. Once data is recovered from magnetic tapes, what normalization
and conversion steps are typically required to make the content usable
within a modern document management or AI accessibility?
9. What key performance benchmarks have proven most useful or are
most often overlooked when evaluating vendor proposals for paper
digitization?
a. What about in the case of microform records? What performance
benchmarks are most useful to evaluate vendor proposals for microform
digitization at scale?
b. What about for magnetic tape formats? What performance
benchmarks or success metrics are most reliable?
10. Beyond paper, microfilm, microfiche, and magnetic tape, are
there other legacy media formats NTIS should anticipate encountering in
a collection
[[Page 61837]]
of this age and scope, and how should they be addressed?
II. General Digitization Infrastructure
11. What cloud storage architectures, on-premises solutions, or
hybrid approaches should NTIS consider for housing a collection of this
size, and what are the tradeoffs in terms of cost, security, access
speed, and long-term sustainability?
12. What quality assurance and quality control (QA/QC) frameworks--
including automated and human-in-the-loop review--should be applied to
ensure the accuracy and completeness of digitized records across all
media types?
13. What metadata schemas and standards (e.g., Dublin Core, MARC,
MODS, JATS XML) should be applied during digitization to maximize
interoperability, discoverability, and long-term preservation value, as
well as compatibility with existing AI data pipelines?
14. What strategies can be employed to harmonize legacy datasets
created under older metadata standards with newly digitized collections
that use more contemporary metadata schemas?
15. What hurdles to success commonly or surprisingly appear in
large-scale digitization projects, and how can they be minimized or
avoided?
III. Dataset Curation, Structuring & Preparation for Use
16. What data cleaning, normalization, and enrichment steps are
necessary to transform a raw digitized corpus of scientific and
technical documents into a useful tool for future scientific and
technical applications?
17. When encountering documents with low OCR confidence scores,
missing metadata, or damaged and illegible pages, is there value in
maintaining such documents as part of the NTRL? What thresholds or
remediation strategies are recommended?
18. What strategies might NTIS consider for handling multimodal
content (e.g., figures, charts, engineering diagrams, tables, and
equations) for both archival purposes and providing the highest utility
to the current research community?
19. What deduplication strategies are effective for identifying
multiple copies or versions of a document, including copies and
versions that may exist in multiple formats (e.g., paper, microfiche,
magnetic tape, digital)?
20. Are there recommended automated filtering or screening
mechanisms that can be deployed during digitization to ensure that no
restricted, export-controlled (e.g., ITAR/EAR), sensitive, or
personally identifiable information (PII) is inadvertently exposed,
given that the collection consists primarily of public, federally-
funded research?
21. What governance structures should NTIS establish to oversee
ongoing dataset curation, quality control, update cycles, and
stakeholder engagement after initial digitization is complete?
22. How might a fully digitized version of the NTRL be structured
and formatted (e.g., JSONL, Parquet, Markdown, raw text with metadata
sidecars) to maximize its usability across a range of CETs, including
AI training pipelines and frameworks?
23. What approaches to versioning and provenance tracking have
proven effective in large-scale digitization projects? When considering
the importance of reproducibility in AI research and compliance with
emerging AI transparency requirements, do different approaches suggest
themselves?
24. What existing mechanisms for distributing and accessing large-
scale data repositories (e.g., bulk download via cloud object storage,
streaming APIs, vector databases) offer the greatest advantages in
terms of efficiency, useability, and interoperability? How can
interoperability with existing data repositories be maximized?
IV. Value of a Fully Digitized NTRL for Furthering Future U.S.
Innovation
25. What characteristics of a fully digitized NTRL would be of the
greatest value in furthering US innovation?
26. How would a fully digitized NTRL compare in value for the
development of CETs, including AI models and tools, to other commonly
used scientific text databases? What unique gaps might the NTRL fill?
27. Are there specific technical domains within the NTRL (e.g.,
aeronautics, public health, materials science, energy, defense) that if
more accessible could produce outsized scientific or economic value?
Please identify priority domains and explain your reasoning.
28. To what extent could an AI model trained or fine-tuned on the
NTRL corpus help researchers, engineers, and scientists surface
insights, connections, and findings buried in decades of forgotten or
hard-to-search government research--including potentially identifying
overlooked scientific breakthroughs or cross-disciplinary connections?
V. Access Models, Licensing & Public Benefit
29. What data distribution and pricing framework (access model)--
encompassing technical delivery methods (e.g., bulk cloud downloads,
APIs), licensing terms (e.g., open source, commercial), and fee
structures (e.g., freemium, cost-recovery fees for high-volume
commercial users)--would best balance maximizing public benefit,
supporting U.S. competitiveness, and enabling NTIS to recover costs (or
eliminate government costs), while ensuring individual public users and
non-commercial researchers retain free access?
30. How should NTIS structure access to ensure that small
businesses, academic institutions, and non-profit researchers can
meaningfully participate alongside large companies?
31. Are there precedents from other government data release efforts
(e.g., NIH data sharing policies, NASA open data initiatives, the Pile
dataset) that NTIS should study when designing its access and licensing
framework?
VI. Partnerships & Implementation Models
32. Are there existing federal data infrastructure programs,
university consortia, or national laboratory networks that NTIS should
partner with to accelerate digitization and dataset curation?
33. What measures should NTIS take to ensure that tools, including
AI tools built on the NTRL dataset, are accessible and useful to a
broad range of users, including those without advanced technical
expertise?
34. How should NTIS approach transparency and documentation of the
dataset--for example, through dataset datasheets or model cards--to
support responsible AI development practices consistent with current
federal AI policy?
35. How can NTIS ensure that the NTRL dataset remains current and
continues to grow in value over time as new federally-funded STEI is
produced?
36. Are there international counterparts or foreign government
initiatives to digitize and make available large scientific and
technical corpora for AI development that NTIS should study or seek to
distinguish the NTRL from in terms of strategic positioning?
Authority: 15 U.S.C. 1151-1157, 3704b, 3704b-1, 3704b-2.
Alicia Chambers,
NIST Executive Secretariat.
[FR Doc. 2026-20023 Filed 9-29-26; 8:45 am]
BILLING CODE 3510-04-P
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