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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Causality and the Semantics of Provenance · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/1006.1429/</link><description>Collected HN comments and submissions linking this paper.</description><language>en</language><lastBuildDate>Mon, 02 Nov 2026 11:16:22 GMT</lastBuildDate><atom:link href="https://hackerpaper.kaipfister.de/p/1006.1429/feed.xml" rel="self" type="application/rss+xml" /><item><title>Causality and the Semantics of Provenance — mentioned by 6gvONxR4sf7o</title><link>https://news.ycombinator.com/item?id=21108846</link><guid isPermaLink="false">urn:hackerpapers:mention:1006.1429:21108846</guid><pubDate>Sun, 29 Sep 2019 18:44:53 GMT</pubDate><description>&lt;p&gt;I&amp;#x27;m beginning to suspect that it could be relevant soon. If you wait for such advanced AI that can understand your documentation, you&amp;#x27;re making it harder than it has to be, kinda like Marcus is saying in OP. You could solve this with just tons of raw data, but that seems unnecessarily hard. For a firm with the usual small dataset, maybe even unrealistically hard. Anyways, with some naive googling I found these references which seem interesting with regards to lineage and causality (for the query &amp;quot;lineage causal database schema&amp;quot;): [0] Causality and Explanations in Databases. The &amp;quot;Related…&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/1006.1429/"&gt;Paper and discussion history&lt;/a&gt;. A mention is not an endorsement.&lt;/p&gt;</description><category>cs.LO</category></item></channel></rss>
