Pagerank algorithm analyses links between web pages and produces better result when querying. But applying similar algorithms (Pagerank) for ontologies in the hope of identifying the most popular ontologies may not help. Because, the majority of ontologies available on the Web are not connected well (but web pages are linked highly, hence the better result for “string match” based search engines) and more than half of the ontologies are not linked to other ontologies at all. Poor connectivity would certainly produce poor PageRank results. Secondly, the links in the current web provides value at the level of page or sub sections. But semantic web provides value at the level objects/entities and their relations. Hence, semantic search rank should include factors like relations, attributes, similarity/word distance, etc. In other words the weight should be assigned at the level of entities/relations (low level graph). Pagerank works well at macro level. But not suitable at micro level.