I run prefix.cc, a website for RDF developers where anyone can register and look up the expansion URIs for namespace prefixes such as foaf, dc, qb or void. The site tracks which prefixes gets looked up most often. This allows some insight into the popularity of RDF vocabularies and datasets.
This post is a snapshot of the top 100 most requested prefixes as of today.
Caveats:
- The counts reflect what knowledgeable RDF hackers are interested in. This may or may not reflect the interests of more casual users, or what’s deployed on the web. The og prefix for Facebook’s Open Graph protocol for example is outside of the list, at #273.
- “Users” of the site include automated apps and web crawlers. This distorts numbers. For example, the prefix.cc homepage links to prefix.cc/foaf, driving crawlers and first-time visitors that way, inflating foaf numbers.
- Here I deliberately do not include the full URI expansions for those prefixes. Prefix.cc allows multiple competing expansions for a prefix. Users can then vote to determine what’s shown first. It can be subject to gaming, ballot stuffing, and so on. There are strong disagreements over the “best” expansion for some prefixes, starting right at #2 with dc, which is one of most controversial prefixes on the site. (If you need expansions, then you can get a fresh set from the API.)
- Prefix.cc doesn’t allow registration of single-letter namespaces, along with some other syntactic restrictions. Some vocabularies suggest single-letter prefixes, most notably Google’s rdf.data-vocabulary.org, which is commonly abbreviated “v”. (Someone has registered dv for it, but that rarely gets looked up.)
That being said: The data is below, and a CSV version is available too.
Rank | Prefix | Lookups |
---|---|---|
1 | foaf | 45506 |
2 | dc | 17621 |
3 | rdf | 17585 |
4 | rdfs | 14865 |
5 | owl | 11898 |
6 | geonames | 9349 |
7 | geo | 4757 |
8 | skos | 4501 |
9 | dbp | 3396 |
10 | swrc | 2439 |
11 | sioc | 2336 |
12 | xsd | 2310 |
13 | dbo | 2089 |
14 | dc11 | 2006 |
15 | doap | 1856 |
16 | dbpprop | 1697 |
17 | content | 1621 |
18 | wot | 1598 |
19 | rss | 1474 |
20 | gen | 1403 |
21 | dbpedia | 1377 |
22 | d2rq | 1370 |
23 | nie | 1352 |
24 | xhtml | 1336 |
25 | test2 | 1305 |
26 | gr | 1301 |
27 | dcterms | 1255 |
28 | org | 1157 |
29 | vcard | 1154 |
30 | akt | 1150 |
31 | dct | 1118 |
32 | ex | 1104 |
33 | fb | 995 |
34 | owlim | 993 |
35 | cfp | 978 |
36 | xf | 960 |
37 | sism | 956 |
38 | earl | 948 |
39 | bio | 941 |
40 | reco | 936 |
41 | xfn | 926 |
42 | media | 925 |
43 | air | 921 |
44 | dcmit | 920 |
45 | void | 917 |
46 | fn | 915 |
47 | afn | 910 |
48 | cc | 906 |
49 | cld | 900 |
50 | vann | 898 |
51 | days | 895 |
52 | ical | 893 |
53 | http | 893 |
54 | mu | 888 |
55 | sd | 874 |
56 | osag | 874 |
57 | botany | 859 |
58 | cal | 858 |
59 | musim | 850 |
60 | factbook | 848 |
61 | cs | 845 |
62 | log | 838 |
63 | rev | 837 |
64 | swande | 836 |
65 | bibo | 834 |
66 | dcq | 834 |
67 | cv | 832 |
68 | ome | 830 |
69 | biblio | 830 |
70 | dir | 828 |
71 | giving | 827 |
72 | memo | 827 |
73 | ok | 826 |
74 | rel | 821 |
75 | event | 818 |
76 | ir | 818 |
77 | aiiso | 816 |
78 | ad | 813 |
79 | dbr | 813 |
80 | co | 812 |
81 | af | 809 |
82 | cmp | 806 |
83 | bill | 805 |
84 | rif | 804 |
85 | xs | 804 |
86 | math | 803 |
87 | rdfg | 803 |
88 | daia | 801 |
89 | swc | 800 |
90 | tag | 800 |
91 | swanq | 799 |
92 | xhv | 796 |
93 | book | 795 |
94 | jdbc | 793 |
95 | myspace | 792 |
96 | tzont | 792 |
97 | sr | 790 |
98 | ctag | 789 |
99 | dcn | 787 |
100 | lomvoc | 786 |
Some including namespace a very doubtable regarding their popularity. You may should mark “counts reflect what knowledgeable RDF hackers are interested in” in bold style. However, I think even then it is still very doubtable. Anyway, thanks a lot for your efforts. You already named the sources for this biased view (automated apps and web crawlers – are not “RDF hackers” ;) ).
@zazi: Data with known biases is better than no data.