The　Object　Summary　(OS)　is　a　recently　proposed　tree　structure,　which　summarizes　all　data　held　in　a　relational　database　about　a　data　subject.　An　OS　can　potentially　be　very　large　in　size　and　therefore　unfriendly　for　users　who　wish　to　view　synoptic　information　about　the　data　subject.　In　this　paper,　we　investigate　the　effective　and　efficient　retrieval　of　concise　and　informative　OS　snippets　(denoted　as　size-l　OSs).　We　propose　and　investigate　the　effectiveness　of　two　types　of　size-l　OSs,　namely　size-l　OS(t)s　and　size-l　OS(a)s　that　consist　of　l　tuple　nodes　and　l　attribute　nodes　respectively.　For　computing　size-l　OSs,　we　propose　an　optimal　dynamic　programming　algorithm,　two　greedy　algorithms　and　preprocessing　heuristics.　By　collecting　feedback　from　real　users　(e.g.,　from　DBLP　authors),　we　assess　the　relative　usability　of　the　two　different　types　of　snippets,　the　choice　of　the　size-l　parameter,　as　well　as　the　effectiveness　of　the　snippets　with　respect　to　the　user　expectations.　In　addition,　via　thorough　evaluation　on　real　databases,　we　test　the　speed　and　effectiveness　of　our　techniques.