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osint-methodologies
OSINT collection, source evaluation, data integration, verification techniques for Swedish political intelligence
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OSINT collection, source evaluation, data integration, verification techniques for Swedish political intelligence
Codex または Claude でインストール この Prompt をコピーして Codex、Claude、または他のアシスタントに貼り付けると、Skill ページを確認してインストールできます。
SOC 職業分類に基づく
| name | osint-methodologies |
| description | OSINT collection, source evaluation, data integration, verification techniques for Swedish political intelligence |
| license | Apache-2.0 |
Apply the AI FIRST principle: never accept first-pass quality. Minimum 2 iterations. Read all output, improve every section. No shortcuts.
This skill provides comprehensive Open-Source Intelligence (OSINT) collection methodologies specifically tailored for the Riksdagsmonitor (Riksdagsmonitor) platform's mission of democratic transparency and political accountability in Sweden. It ensures ethical, legal, and effective intelligence gathering from public sources while maintaining GDPR compliance and respecting privacy principles.
Apply this skill when:
Do NOT use for:
The Riksdagsmonitor platform integrates four high-integrity OSINT sources to create comprehensive political intelligence:
graph TB
subgraph "OSINT Sources"
A1[📡 Riksdagen API<br/>98.5% completeness<br/>3.5M+ votes, 89K documents]
A2[📊 Election Authority<br/>99.2% completeness<br/>1970-present electoral data]
A3[💰 World Bank<br/>94.1% completeness<br/>598K indicators, 211 countries]
A4[🏛️ Financial Authority ESV<br/>97.8% completeness<br/>Monthly updates]
end
subgraph "Collection Layer"
A1 --> B[Data Ingestion Pipeline]
A2 --> B
A3 --> B
A4 --> B
end
subgraph "Quality Assurance"
B --> C{Source Verification}
C --> D[Completeness Check]
C --> E[Consistency Validation]
C --> F[Temporal Continuity]
C --> G[Cross-Reference Check]
end
subgraph "Data Integration"
D & E & F & G --> H[(Integrated Dataset)]
H --> I[Entity Resolution]
I --> J[Data Enrichment]
end
subgraph "Quality Metrics"
J --> K[📊 Quality Dashboard]
K --> L[Completeness: 97.4%]
K --> M[Accuracy: 99.1%]
K --> N[Timeliness: 24h lag]
end
style A1 fill:#e1f5ff
style A2 fill:#e1f5ff
style A3 fill:#e1f5ff
style A4 fill:#e1f5ff
style C fill:#ffeb99
style H fill:#ccffcc
style K fill:#ffe6cc
Source Profile:
Quality Metrics:
@Component
public class RiksdagenSourceQualityMetrics {
public SourceQualityReport evaluateRiksdagenAPI() {
return SourceQualityReport.builder()
.sourceName("Riksdagen API")
.completeness(98.5) // Measured against expected records
.accuracy(99.8) // Verified via manual audit sampling
.timeliness(1.0) // Hours lag for new data
.reliability(5) // 1-5 scale, 5 = highest
.trustLevel("PRIMARY_SOURCE")
.legalBasis("Public Records Act (Offentlighetsprincipen)")
.gdprCompliance(true)
.updateFrequency("DAILY")
.build();
}
public List<DataGap> identifyDataGaps() {
// Example: Check for missing voting records
String sql = """
SELECT
COUNT(*) as expected_votes,
COUNT(DISTINCT ballot_id) as actual_votes,
COUNT(*) - COUNT(DISTINCT ballot_id) as missing_votes
FROM view_riksdagen_vote_daily_summary
WHERE created_date >= CURRENT_DATE - INTERVAL '30 days'
""";
// Calculate completeness percentage
return jdbcTemplate.query(sql, (rs, rowNum) ->
DataGap.builder()
.expectedRecords(rs.getInt("expected_votes"))
.actualRecords(rs.getInt("actual_votes"))
.missingRecords(rs.getInt("missing_votes"))
.completeness((double) rs.getInt("actual_votes") /
rs.getInt("expected_votes") * 100)
.build()
);
}
}
Data Categories:
Voting Records (vote_data table)
Documents (document_element, document_status_container)
Politicians (person_data, assignment_data)
Parliamentary Activities
OSINT Techniques:
-- Source Triangulation: Verify politician voting record completeness
WITH expected_votes AS (
SELECT
person_id,
COUNT(DISTINCT ballot_id) as riksdagen_vote_count
FROM vote_data
WHERE vote_date >= '2022-09-11' -- Current parliament
GROUP BY person_id
),
document_activity AS (
SELECT
person_id,
COUNT(DISTINCT document_id) as document_count
FROM document_person_reference_data
WHERE document_type IN ('mot', 'ip') -- Motions & Questions
GROUP BY person_id
)
SELECT
p.first_name || ' ' || p.last_name as politician_name,
p.party as party_affiliation,
ev.riksdagen_vote_count,
da.document_count,
CASE
WHEN ev.riksdagen_vote_count > 500 THEN 'ACTIVE'
WHEN ev.riksdagen_vote_count BETWEEN 100 AND 500 THEN 'MODERATE'
WHEN ev.riksdagen_vote_count < 100 THEN 'INACTIVE'
END as engagement_level
FROM person_data p
LEFT JOIN expected_votes ev ON p.person_id = ev.person_id
LEFT JOIN document_activity da ON p.person_id = da.person_id
WHERE p.status = 'Tjänstgörande riksdagsledamot' -- Active MPs
ORDER BY ev.riksdagen_vote_count DESC;
Source Profile:
Quality Metrics:
@Component
public class ElectionAuthorityQualityMetrics {
public SourceQualityReport evaluateElectionAuthority() {
return SourceQualityReport.builder()
.sourceName("Valmyndigheten")
.completeness(99.2)
.accuracy(99.9) // Official certified results
.timeliness(168.0) // Hours post-election for final results
.reliability(5)
.trustLevel("PRIMARY_SOURCE")
.legalBasis("Election Act (Vallagen)")
.gdprCompliance(true)
.updateFrequency("ELECTION_CYCLE")
.build();
}
public List<ElectionDataValidation> validateElectionData() {
// Cross-reference with Riksdagen seat assignments
String sql = """
SELECT
e.party_name,
e.parliament_seats as election_authority_seats,
COUNT(DISTINCT a.person_id) as riksdagen_active_mps,
e.parliament_seats - COUNT(DISTINCT a.person_id) as seat_discrepancy
FROM sweden_political_party e
LEFT JOIN assignment_data a
ON e.party_id = a.party
AND a.role_code = 'Riksdagsledamot'
AND a.from_date <= CURRENT_DATE
AND (a.to_date IS NULL OR a.to_date >= CURRENT_DATE)
WHERE e.parliament_seats > 0
GROUP BY e.party_name, e.parliament_seats
HAVING e.parliament_seats != COUNT(DISTINCT a.person_id)
""";
return jdbcTemplate.query(sql, (rs, rowNum) ->
ElectionDataValidation.builder()
.partyName(rs.getString("party_name"))
.expectedSeats(rs.getInt("election_authority_seats"))
.actualSeats(rs.getInt("riksdagen_active_mps"))
.discrepancy(rs.getInt("seat_discrepancy"))
.build()
);
}
}
OSINT Techniques:
-- Historical Election Trend Analysis
SELECT
party_name,
election_year,
percentage,
parliament_seats,
LAG(percentage, 1) OVER (PARTITION BY party_name ORDER BY election_year) as previous_percentage,
percentage - LAG(percentage, 1) OVER (PARTITION BY party_name ORDER BY election_year) as vote_swing,
LAG(parliament_seats, 1) OVER (PARTITION BY party_name ORDER BY election_year) as previous_seats,
parliament_seats - LAG(parliament_seats, 1) OVER (PARTITION BY party_name ORDER BY election_year) as seat_change
FROM sweden_political_party
WHERE parliament_seats IS NOT NULL
ORDER BY party_name, election_year DESC;
Source Profile:
Quality Metrics:
@Component
public class WorldBankQualityMetrics {
public SourceQualityReport evaluateWorldBankAPI() {
return SourceQualityReport.builder()
.sourceName("World Bank Open Data")
.completeness(94.1)
.accuracy(97.5)
.timeliness(2160.0) // 90 days lag (quarterly updates)
.reliability(4) // High but not primary source
.trustLevel("SECONDARY_SOURCE")
.legalBasis("Open Data License")
.gdprCompliance(true) // Aggregate data only
.updateFrequency("QUARTERLY")
.build();
}
}
Use Cases:
Source Profile:
Legal & Ethical Review:
✅ Data is publicly available under Swedish Public Access Principle (Offentlighetsprincipen)
✅ Collection method complies with GDPR Article 6(1)(e) - public interest
✅ Data processing aligns with purpose limitation (Article 5(1)(b))
✅ Data retention periods defined and documented
✅ Privacy impact assessment completed for personal data
✅ Source attribution and license compliance verified
Source Reliability Assessment:
public enum SourceReliability {
A("COMPLETELY_RELIABLE", "Primary government source, official records"),
B("USUALLY_RELIABLE", "Established media, verified aggregators"),
C("FAIRLY_RELIABLE", "Secondary sources with known limitations"),
D("NOT_USUALLY_RELIABLE", "Unverified sources, requires corroboration"),
E("UNRELIABLE", "Known bias, propaganda, unverified claims"),
F("RELIABILITY_CANNOT_BE_JUDGED", "New source, insufficient track record");
private final String description;
private final String criteria;
}
public enum InformationCredibility {
ONE("CONFIRMED", "Verified by multiple independent sources"),
TWO("PROBABLY_TRUE", "Corroborated by additional source"),
THREE("POSSIBLY_TRUE", "Not confirmed but consistent with known facts"),
FOUR("DOUBTFUL", "Contradicts other information"),
FIVE("IMPROBABLE", "Contradicts established facts"),
SIX("TRUTH_CANNOT_BE_JUDGED", "Insufficient information to evaluate");
private final String description;
private final String criteria;
}
1. Source Identification
class OSINTSource:
def __init__(self, name, url, api_endpoint=None):
self.name = name
self.url = url
self.api_endpoint = api_endpoint
self.reliability = None # A-F rating
self.credibility = None # 1-6 rating
self.completeness = None
self.last_updated = None
def evaluate_reliability(self):
"""NATO Admiralty Code reliability assessment"""
if self.is_government_official_source():
self.reliability = SourceReliability.A
elif self.is_verified_aggregator():
self.reliability = SourceReliability.B
# ... additional logic
def verify_completeness(self, expected_records, actual_records):
"""Calculate data completeness percentage"""
self.completeness = (actual_records / expected_records) * 100
return self.completeness
def assess_timeliness(self):
"""Calculate data lag from source update to platform availability"""
time_lag = datetime.now() - self.last_updated
return time_lag.total_seconds() / 3600 # Hours
2. Data Harvesting
@Service
public class OSINTDataCollector {
@Scheduled(cron = "0 0 2 * * *") // Daily at 02:00
public void collectRiksdagenData() {
try {
// 1. Fetch new data
List<VoteData> newVotes = riksdagenClient.getVotesSince(lastCollectionTimestamp);
// 2. Validate data quality
DataQualityReport report = validateDataQuality(newVotes);
if (report.getQualityScore() < 95.0) {
alertService.sendAlert("Low quality data detected", report);
}
// 3. Deduplicate
List<VoteData> uniqueVotes = deduplicateRecords(newVotes);
// 4. Store with audit trail
voteRepository.saveAll(uniqueVotes);
// 5. Update collection metadata
updateCollectionMetrics(uniqueVotes.size(), report);
log.info("Collected {} new votes with {}% quality score",
uniqueVotes.size(), report.getQualityScore());
} catch (Exception e) {
log.error("Data collection failed", e);
alertService.sendAlert("OSINT collection failure", e);
}
}
private DataQualityReport validateDataQuality(List<VoteData> data) {
DataQualityReport report = new DataQualityReport();
// Completeness check
long missingFields = data.stream()
.filter(v -> v.getPersonId() == null || v.getBallotId() == null)
.count();
report.setCompleteness(100.0 - (missingFields * 100.0 / data.size()));
// Consistency check
long invalidVotes = data.stream()
.filter(v -> !Arrays.asList("Ja", "Nej", "Frånvarande", "Avstår").contains(v.getVote()))
.count();
report.setConsistency(100.0 - (invalidVotes * 100.0 / data.size()));
// Temporal validity
long futureVotes = data.stream()
.filter(v -> v.getVoteDate().isAfter(LocalDate.now()))
.count();
report.setTemporalValidity(100.0 - (futureVotes * 100.0 / data.size()));
report.calculateOverallScore();
return report;
}
}
3. Source Triangulation
-- Cross-Reference Verification: Validate politician data across sources
WITH riksdagen_politicians AS (
SELECT
person_id,
first_name,
last_name,
party,
status
FROM person_data
WHERE status = 'Tjänstgörande riksdagsledamot'
),
riksdagen_seats AS (
SELECT
party,
COUNT(DISTINCT person_id) as active_mps
FROM riksdagen_politicians
GROUP BY party
),
election_seats AS (
SELECT
party_name,
parliament_seats
FROM sweden_political_party
WHERE parliament_seats > 0
)
SELECT
COALESCE(r.party, e.party_name) as party,
r.active_mps as riksdagen_count,
e.parliament_seats as election_authority_count,
ABS(COALESCE(r.active_mps, 0) - COALESCE(e.parliament_seats, 0)) as discrepancy,
CASE
WHEN ABS(COALESCE(r.active_mps, 0) - COALESCE(e.parliament_seats, 0)) = 0 THEN '✅ VERIFIED'
WHEN ABS(COALESCE(r.active_mps, 0) - COALESCE(e.parliament_seats, 0)) <= 2 THEN '⚠️ MINOR_DISCREPANCY'
ELSE '🚨 MAJOR_DISCREPANCY'
END as verification_status
FROM riksdagen_seats r
FULL OUTER JOIN election_seats e ON r.party = e.party_name
ORDER BY discrepancy DESC;
1. Completeness
-- Calculate field completeness across all tables
SELECT
'person_data' as table_name,
COUNT(*) as total_records,
SUM(CASE WHEN first_name IS NULL THEN 1 ELSE 0 END) as missing_first_name,
SUM(CASE WHEN last_name IS NULL THEN 1 ELSE 0 END) as missing_last_name,
SUM(CASE WHEN party IS NULL THEN 1 ELSE 0 END) as missing_party,
ROUND(100.0 * (1.0 - (
SUM(CASE WHEN first_name IS NULL THEN 1 ELSE 0 END)::decimal +
SUM(CASE WHEN last_name IS NULL THEN 1 ELSE 0 END) +
SUM(CASE WHEN party IS NULL THEN 1 ELSE 0 END)
) / (COUNT(*) * 3)), 2) as completeness_percentage
FROM person_data;
2. Accuracy
@Component
public class DataAccuracyVerifier {
public AccuracyReport verifyPoliticianData() {
// Manual audit sampling: Verify 100 random politicians against Riksdagen website
List<PersonData> sample = personRepository.findRandomSample(100);
int accurate = 0;
int inaccurate = 0;
for (PersonData person : sample) {
// Fetch from official Riksdagen website for comparison
OfficialPersonData official = riksdagenWebScraper.fetchPersonData(person.getPersonId());
if (verifyMatch(person, official)) {
accurate++;
} else {
inaccurate++;
log.warn("Data mismatch for person_id: {}", person.getPersonId());
}
}
return AccuracyReport.builder()
.sampleSize(sample.size())
.accurateRecords(accurate)
.inaccurateRecords(inaccurate)
.accuracyPercentage((double) accurate / sample.size() * 100)
.build();
}
}
3. Timeliness
-- Calculate data freshness lag
SELECT
'vote_data' as data_type,
MAX(created_date) as latest_record,
CURRENT_TIMESTAMP as current_time,
EXTRACT(EPOCH FROM (CURRENT_TIMESTAMP - MAX(created_date))) / 3600 as hours_lag,
CASE
WHEN EXTRACT(EPOCH FROM (CURRENT_TIMESTAMP - MAX(created_date))) / 3600 < 24 THEN '✅ CURRENT'
WHEN EXTRACT(EPOCH FROM (CURRENT_TIMESTAMP - MAX(created_date))) / 3600 < 168 THEN '⚠️ RECENT'
ELSE '🚨 STALE'
END as freshness_status
FROM vote_data;
4. Consistency
-- Detect referential integrity violations
SELECT
'Vote Data Integrity' as check_name,
COUNT(DISTINCT v.ballot_id) as total_votes,
COUNT(DISTINCT CASE WHEN p.person_id IS NULL THEN v.person_id END) as orphaned_person_refs,
COUNT(DISTINCT CASE WHEN b.ballot_id IS NULL THEN v.ballot_id END) as orphaned_ballot_refs,
ROUND(100.0 * (1.0 - (
COUNT(DISTINCT CASE WHEN p.person_id IS NULL THEN v.person_id END)::decimal +
COUNT(DISTINCT CASE WHEN b.ballot_id IS NULL THEN v.ballot_id END)
) / (COUNT(DISTINCT v.ballot_id) * 2)), 2) as consistency_percentage
FROM vote_data v
LEFT JOIN person_data p ON v.person_id = p.person_id
LEFT JOIN ballot_data b ON v.ballot_id = b.ballot_id;
A.5.10 - Acceptable Use of Information
A.5.33 - Protection of Records
A.8.8 - Management of Technical Vulnerabilities
IDENTIFY (ID)
PROTECT (PR)
DETECT (DE)
CIS Control 3: Data Protection
CIS Control 12: Network Infrastructure Management
Data Classification Policy
Privacy Policy
Secure Development Policy
Third Party Management
Official Documentation:
CIA Platform Documentation:
Academic Sources:
Standards:
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| Source | Reliability (A–E) | Credibility (1–6) | Use for |
|---|---|---|---|
| IMF WEO / Fiscal Monitor | A (consistently reliable) | 1 (confirmed by other sources) | PRIMARY — macro, fiscal, monetary, external, projections |
| IMF IFS / BOP / DOTS / GFS_COFOG / PCPS / ER / MFS | A | 2 (probably true) | PRIMARY — high-frequency economic indicators |
| SCB (Statistics Sweden) | A | 1 | PRIMARY — Swedish-specific ground truth |
| Riksbank | A | 1 | Monetary policy supporting source |
| World Bank WGI (governance only) | A | 1 | PRIMARY for governance (CC.EST, RL.EST, VA.EST, GE.EST, RQ.EST, PV.EST) |
| World Bank WDI / WGI (non-economic context) | A | 1 | PRIMARY for governance (*.EST), environment (EN.*, EG.*, AG.LND.FRST.ZS), social/education residue (SP.*, SH.*, SE.*), defence historicals (MS.MIL.*), crime (VC.IHR.PSRC.P5) |
Canonical OSINT rule: IMF is graded A1/A2 for economic intelligence (macro, fiscal, monetary, external, trade, commodity, FX, interest rates) and is the source for every economic claim. World Bank is graded A1 for the governance, environment, social/education, defence-historical, and crime/justice context catalogued in analysis/worldbank/indicators-inventory.json. See .github/aw/ECONOMIC_DATA_CONTRACT.md v3.0 and analysis/imf/.
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