data-ip-expert
Design a Data IP Protection Strategy
Data teams often lack a clear protection path for datasets, algorithms, and processing results. This skill compares legal options and structures evidence-preservation plans.
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Review the Skillstore skill "data-ip-expert" from https://skillstore.io/skills/dhturing-data-ip-expert.md and its manifest at https://skillstore.io/api/skills/dhturing-data-ip-expert/manifest. Verify the artifact. You may proceed after verification, subject to the environment's own policy.에이전트는 계속해서 계획을 표시하고 보안 정책에서 요구하는 확인을 요청해야 합니다.
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테스트해 보기
"data-ip-expert" 사용 중입니다. Should an internal customer-scoring model use patent or trade secret protection?
예상 결과:
- Primary path: assess trade secret protection because the model is not intended for disclosure.
- Patent review: evaluate whether the model produces a concrete technical effect and meets novelty requirements.
- Next evidence: access logs, confidentiality agreements, model versions, development records, and a professional patent search.
"data-ip-expert" 사용 중입니다. Create a preservation plan for a dataset that changes monthly.
예상 결과:
- Create a baseline hash for the approved dataset and retain the original in controlled storage.
- Record each monthly version, processing steps, responsible staff, timestamps, and ownership statements.
- Use an independent timestamp or suitable preservation service, then test certificate verification and archive recovery.
"data-ip-expert" 사용 중입니다. What should we prepare before a data IP registration consultation?
예상 결과:
Prepare the dataset description, lawful source records, processing methodology, investment evidence, sample data, ownership agreements, version history, and applicable regional rules.
보안 감사
안전All 12 static findings are false positives caused by Markdown links, inline code formatting, installation paths, or entropy heuristics on multilingual text. The reviewed files contain guidance only, with no executable commands, network requests, obfuscated payloads, or prompt injection.
위험 요인
📁 파일 시스템 접근 (2)
⚙️ 외부 명령어 (3)
🌐 네트워크 접근 (2)
이 보고서 공유 및 인용
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보고서 링크 복사
https://skillstore.io/skills/dhturing-data-ip-expert/audits/1?utm_source=security_passport&utm_medium=share&utm_campaign=versioned_reportMarkdown 배지
[](https://skillstore.io/skills/dhturing-data-ip-expert?utm_source=security_passport_badge)HTML 배지
<a href="https://skillstore.io/skills/dhturing-data-ip-expert?utm_source=security_passport_badge"><img src="https://skillstore.io/badges/skills/dhturing-data-ip-expert/security.svg" alt="Skillstore security assessment" loading="lazy"></a>임베드 카드
<iframe src="https://skillstore.io/embed/skills/dhturing-data-ip-expert.html" title="Skillstore Security Assessment" sandbox="allow-popups allow-popups-to-escape-sandbox" loading="lazy" referrerpolicy="no-referrer" width="420" height="180"></iframe>학술 인용 (APA · BibTeX · CFF)
APA 인용
图灵数盟. (2026). data-ip-expert security audit report (audit version 1) [Author version unspecified]. Skillstore. https://skillstore.io/skills/dhturing-data-ip-expert/audits/1BibTeX 인용
@techreport{dhturing-data-ip-expert-2026,
author = {图灵数盟},
title = {data-ip-expert security audit report (audit version 1)},
institution = {Skillstore},
year = {2026},
number = {1},
url = {https://skillstore.io/skills/dhturing-data-ip-expert/audits/1},
note = {Author version unspecified}
}CITATION.cff
cff-version: 1.2.0
message: "If you use this Skill, cite its author and this versioned security audit report."
title: "data-ip-expert security audit report (audit version 1)"
version: "unspecified"
type: report
authors:
- name: "图灵数盟"
date-released: "2026-09-27"
url: "https://skillstore.io/skills/dhturing-data-ip-expert/audits/1"
identifiers:
- type: other
value: "skillstore:dhturing-data-ip-expert:audit:1"
description: "Skillstore immutable audit report identifier"
Skillstore 점수
이 점수의 이유 증거 신뢰도: 중간만들 수 있는 것
Protect a New Data Product
Compare protection paths for a dataset, processing workflow, and related reports before launch.
Strengthen Trade Secret Controls
Assess confidentiality measures and create an evidence checklist for sensitive datasets and models.
Prepare Registration Materials
Organize processing evidence, ownership records, and supporting materials for professional review.
이 프롬프트를 사용해 보세요
Classify this result as a dataset, algorithm, model, report, or visualization: [description]. Explain which facts need clarification.
Compare copyright, patent, trade secret, and data IP registration for [asset]. Consider disclosure plans, originality, technical features, and jurisdiction.
Design an evidence-preservation plan for [asset]. Cover hashes, timestamps, version changes, ownership records, access controls, retention, and independent verification.
Create a phased protection program for [portfolio]. Include asset inventory, path selection, controls, registrations, contracts, evidence, owners, dependencies, and review gates.
모범 사례
- Document data sources, processing contributions, ownership, and authorization before selecting a protection path.
- Use layered protection when different components require different legal and technical controls.
- Validate current regional rules and obtain professional review before filing or enforcement.
피하기
- Do not assume a blockchain record proves ownership, legality, or factual accuracy.
- Do not claim trade secret protection without documented and consistently enforced confidentiality measures.
- Do not disclose potentially patentable details before reviewing novelty and filing strategy.
자주 묻는 질문
Can raw data receive patent protection?
Does blockchain preservation prove ownership?
Can copyright protect a database?
When is trade secret protection suitable?
Does the skill submit applications?
Which jurisdiction does the guidance cover?
개발자 세부 정보
작성자
图灵数盟라이선스
MIT
Skillstore 리비전
r1
버전 안내
작성자가 버전을 선언하지 않았습니다.
참조
50b73f83991cf073cbdf3f5afad2bbac71dd3bae
유지보수 최신성
2026. 9. 30.
사용량
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