ESCO is a multilingual classification of Skills, Competences, Qualifications, and Occupations created by the European Commission to improve the supply of information on skills demand in the labour market. It is designed to assist individuals, employers, universities and training providers by giving them up to date and standardized information on skills. Rapid technological change means that ESCO needs to be updated in a timely manner. Evidence is presented here of how text-mining techniques can be applied to the analysis of data on emerging skill needs arising from Industry 4.0 to ensure that ESCO provides information which is current. The alignment between ESCO and Industry 4.0 technological trends is analysed. Using text mining techniques, information is extracted on Industry 4.0 technologies from: (i) two versions of ESCO (v1.0 - v1.1.); and (ii) from the 4.0 related scientific literature. These are then compared to identify potential data gaps in ESCO. The findings demonstrate that text mining applied on scientific literature to extract technology trends, can help policy makers to provide more up-to-date labour market intelligence.

ESCO 是欧盟委员会创建的技能、能力、资格和职业的多语言分类，旨在改善劳动力市场技能需求信息的供应。它旨在通过向个人、雇主、大学和培训提供者提供有关技能的最新和标准化信息来帮助他们。快速的技术变革意味着 ESCO 需要及时更新。这里展示了如何将文本挖掘技术应用于分析工业 4.0 产生的新兴技能需求的数据，以确保 ESCO 提供最新信息的证据。分析了 ESCO 与工业 4.0 技术趋势之间的一致性。使用文本挖掘技术，从工业 4.0 技术中提取信息：(i) 两个版本的 ESCO (v1.0 - v1.1.)；(ii) 来自 4.0 相关科学文献。然后将这些进行比较，以确定 ESCO 中的潜在数据差距。研究结果表明，将文本挖掘应用于科学文献以提取技术趋势，可以帮助政策制定者提供更多最新的劳动力市场情报。