Human Access First
Maintain dependable access for researchers, participants, authors, libraries, and the public.
The JR Institute intends to support human readers, libraries, search engines, researchers, developers, and responsible automated systems while protecting repository availability, security, privacy, and the integrity of the scholarly record.
This page presents a planned public standard. Final API terms, rate limits, account controls, security-reporting channels, automated-access methods, and enforcement procedures should be established before the repository becomes operational.
Automated discovery, indexing, preservation, citation analysis, and text mining can expand the value of a repository.
Uncontrolled traffic, credential misuse, deceptive automation, destructive testing, and attempts to bypass restrictions can impair access for everyone.
Maintain dependable access for researchers, participants, authors, libraries, and the public.
Identify automated clients, follow published interfaces, and avoid unnecessary load.
Protect credentials, use accurate identities, and do not impersonate authors, institutions, or services.
Do not interfere with systems, bypass controls, exploit vulnerabilities, or access restricted records.
Follow licenses, privacy requirements, attribution duties, embargoes, and record-specific restrictions.
Use warnings, rate controls, temporary restrictions, and appeals before permanent exclusion where practical.
This policy is intended to apply to public browsing, authenticated accounts, submissions, downloads, APIs, feeds, metadata harvesting, indexing, automated agents, bulk access, security testing, and other interaction with the future JR Research Archive.
Users should provide accurate information when identity or affiliation is required for submission, moderation, restricted access, or administrative activity.
Credentials should not be shared, sold, transferred, or used to conceal the person or organization responsible for repository activity.
Responsible automated access may be permitted for indexing, preservation, research, accessibility, citation analysis, metadata exchange, and other legitimate uses.
Automated clients should use descriptive user-agent information, respect published instructions, avoid excessive concurrency, and provide contact information when requested.
Public availability does not create an unlimited right to overwhelm the service, bypass controls, or ignore record-specific licenses.
The Institute may provide APIs, feeds, export files, or scheduled bulk-access methods to reduce unnecessary scraping and improve consistency.
Repository content may be used for machine learning or automated analysis only when the record’s license, access conditions, privacy status, and applicable law permit that use.
Users should preserve attribution, version and withdrawal information, and should not imply that the Institute, authors, or repository endorse a resulting model, product, or analysis.
Security testing should occur only within published authorization, defined scope, and safe-harbor terms.
Researchers should avoid privacy harm, service disruption, destructive actions, persistent access, credential exposure, or public disclosure before reasonable remediation.
Users should not attempt to disrupt, degrade, deceive, compromise, or misuse the repository or its users.
Public metadata should not be combined, enriched, or republished in ways that create unlawful, deceptive, discriminatory, or materially harmful profiles of individuals.
Restricted, embargoed, confidential, or accidentally exposed information should not be accessed, retained, redistributed, or used beyond authorized purposes.
The Institute may monitor service health, authentication events, request patterns, abuse indicators, and security activity to protect the repository and its users.
Responses may include warnings, lower rate limits, revoked tokens, temporary account suspension, blocked traffic, content removal, preservation of evidence, or referral for legal or institutional review.
When practical and safe, affected users should receive notice of the restriction, principal reason, duration, and available corrective action.
Appeals may address mistaken identity, inaccurate detection, disproportionality, corrected technical behavior, or other relevant evidence.
Access may be restored with conditions such as lower limits, new credentials, verified contacts, monitoring, or an approved technical integration.
Framework date: July 2026
Inquiries may concern automated harvesting, search indexing, preservation copies, machine learning, account restrictions, responsible disclosure, or technical integration.
Identify the organization, intended use, data volume, access method, expected request rate, technical contact, and timeline.
Contact the Institute