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Guide To German Online Job Ad Data
Impressum
  • A Guide to Collecting, Processing and Analyzing Online Job Ad Data
  • Navigation
    • Lifecycle
    • Overview - Challenges
    • Overview - Methods
  • Steps
    • Data Collection
    • Data Enrichment
    • Extraction Methods
    • Evaluation and Quality Control
    • Taxonomies and Ontologies
    • Dataset Curation and Representativity Analysis
  • In Practice
    • Literature and Projects
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  • Data Collection
  • Data Enrichment
  • Evaluation and Quality Control
  • Taxonomies and Ontologies
  • Dataset Curation and Representativity Analysis
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  1. Navigation

Overview - Challenges

This page gives an overview of common challenges you could encounter when analyzing OJAs. Next to each challenge is the relevant section in the guide.

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Last updated 1 year ago

If you have identified any challenges not listed here, please let us know by making a pull request in our GitHub Repository or contact us directly.

Data Collection

  • Where to find OJA data?

  • How to collect OJA data?

  • How to store OJA data?

Data Enrichment

  • How to segment a job ad?

  • How to identify duplicates?

  • How to extract occupations?

  • How to extract skills and competences?

Evaluation and Quality Control

  • How to evaluate extraction and classification algorithms?

  • How to create a gold standard for evaluation?

Taxonomies and Ontologies

Dataset Curation and Representativity Analysis

Which taxonomies are there (ISCO, ESCO, KLDB, etc.)?

How to develop a taxonomy?

How to evaluate a taxonomy?

How to deal with duplicates?

How to validate an OJA dataset/sample?

What to report?

Text Segmentation
Identifying Duplicates
Data Enrichment
Extracting Skills
Deduplication
Representativity Analysis
Reporting Results
Evaluation Metrics
Gold Standard Annotation and Quality
Data Sources and OJA Landscaping
Web Scraping
Job Posting Data Schema
Taxonomies and Ontologies
Developing a Taxonomy
Data Standards for Taxonomies and Ontologies