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  • 40 Announcements

Coming soon: your dataset table view will change on August 31 ⏳

 In the legacy version of the platform, it is possible to provide a simplified view of your datasets (by hiding or reordering fields).However, these adjustments are purely visual: hidden fields remain accessible via exports and APIs, which can lead to confusion.   📆 August 31: full deprecation of table view configurationThe table view configuration will be deprecated (whether you are using the legacy or the new platform experience). The table view will automatically reflect your dataset schema (same fields, same field order). As a result, explored, exported, and queried data will be fully consistent. ✅ 📆 June 23: switch to ‘read-only’ mode for the current configuration (intermediate step)You will no longer be able to edit it, but it will remain visible in your back office as a reference (the change will take full effect on August 31).👉 Preview of your back office on June 23, depending on your setup:Case #1 - you are on the legacy experience (or have only migrated your back office to the new experience):            Case #2 - you are on the new experience (back office and front office):             3 ways to keep providing simplified views 🚀1. Update your schema: align it with your current table view (reordering or removing fields)          2. Configure the dataset “Security” tab: define field visibility based on users or groups            3. Create custom views (new experience only): design table views with filtered, sorted, or limited columns. The full schema-based view remains available, but you choose which one to highlight             Need more information? Check out the documentation. 

Related product area:Asset views

Turn your data assets into real data products 📦

"Data product" is a term you've probably increasingly heard over the past few months. In an article, at a conference… or perhaps even within your own organization.But concretely, what is a data product? How does it differ from a simple data asset? And most importantly, how can you showcase it in your Huwise portal? What sets a data product apart from a simple data asset? High usage 📈: widely and regularly consumed by users Careful packaging 📦: enriched with associated resources to make it more readable, engaging, and actionable Stronger trust ✅: includes an identified, accessible data product owner, and clear commitments through a data contract (SLA, update frequency) Ready-to-use data ✨: adapted formats, enriched views, and business-focused structure to foster user independence and self-service👉 In short, a data product is a high-usage data asset, comparable to a best selling item on an e-commerce site: it captures attention, requires ongoing care and engaging presentation (just like a real product) to sustain its success over time. 🌟 Key features to turn your data assets into data products 📦 Visibility: highlight your data products in a dedicated category with a thumbnail to make them easier to spot.     Context: enrich entries with associated resources (prepared views, business definitions, data contract, use cases).      Scalability: continuously improve usage through conversion funnel insights.     

Related product area:Portal interface

The old join processor will be permanently removed on November 30 (recommended actions) ⏳

A few months ago, we introduced the new join processor, designed to handle joins on large datasets with no size limits.          On November 30, all joins using the old processor will be automatically migrated to the new one, which will permanently replace it.Recommended actions before November 30 ⚠️ Automatic migrations by Huwise will trigger a full reprocessing of the affected datasets at their next manual or scheduled publication. If you have datasets that are updated regularly and require a long processing time, we recommend anticipating the automatic migration by updating your joins with the new processor now. We’re here to help if you need support. Since the new processor does not behave exactly the same as the old one due to the improvements made, we encourage you to check how it works on your datasets using older joins, especially those with keys starting with “0.” If you notice differences in results with the new join, you can adapt your data by adding back the missing leading zeros. If you use spreadsheet tools (Excel, etc.) to prepare your data, make sure to format your codes as “text” to avoid losing the leading zero. Have questions or need help?Reach out to your Customer Success Manager or post your questions directly on this Community post. We’ll be happy to respond and guide you through the process. 

Related product area:Processing & Enrichment

The Swiss DCAT-AP-CH interoperability metadata template and its DCAT export have been updated 🇨🇭

They are now fully compatible with the latest version of DCAT-AP-CH (v2) and its recent updates.🚀 By using this metadata template, your portals will be fully harvestable by opendataswiss, the Swiss national portal. Indeed, opendataswiss has recently updated its metadata validation system in line with DCAT-AP-CH v2.⚠️ Until opendataswiss migrates to opendata.swiss next (planned for 2026), importing non-compliant metadata on opendataswiss will remain possible but will trigger error emails. We therefore recommend updating your DCAT-AP-CH metadata now for optimal harvesting.💡 What should you pay particular attention to?opendataswiss checks are now more thorough. All mandatory metadata must be present and accurate. The compliance of recommended and optional properties, if provided, is also checked. Make sure to review the completeness and accuracy of your metadata.  the dct:license metadata replaces dct:rights. The dct:license metadata refers to the terms of use of datasets on opendataswiss. It is mandatory and can only take four values (defined here). We have integrated this new metadata into our Opendatasoft DCAT-AP-CH template, and you can directly choose from the four possible values in the back office. the dct:rights metadata now serves to specify the dataset’s license only in the specific case where it falls under one of the three Creative Commons licenses defined here. The dct:rights metadata is displayed when the dataset is published on data.europa.eu but not on opendataswiss. In the Opendatasoft DCAT-AP-CH export, dct:rights will be generated from the license metadata in the Dataset template, if it matches one of the three allowed CC licenses. The former dct:rights field in the Opendatasoft DCAT-AP-CH template is deprecated and should no longer be used.📖 ResourcesFor full details on the DCAT-AP-CH v2 template, see the official documentation. For full details on the metadata validation system implemented by opendataswiss, see their handbook.

Related product area:Asset Management