Data spaces require the federation of open data from diverse providers. To support this, data catalogs play a critical role in managing and exposing metadata that enables dataset discovery from open data portals. However, most existing catalogs rely heavily on high-level metadata at the dataset level (such as title, license, and keywords) often aligned with standards like DCAT (Data Catalog Vocabulary). While useful, this coarse-grained metadata often falls short in supporting discoverability. To address this limitation, this paper proposes a novel extension to the DCAT standard specifically designed to discover relevant open data to be federated in data spaces. The extension enriches dataset descriptions with fine-grained, content-level metadata, including field-level details, descriptions, and representative samples of values. These additional metadata elements provide critical context for understanding the structure and semantics of datasets, enhancing their discoverability.