02185nas a2200193   4500008004100000245008900041210006900130260000900199300001400208490000700222520151600229653001501745653003601760653002701796653001701823100001401840700002001854856011701874       2012                        eng d00aWebbing semantified scholarly communication datasets for improved resource discovery0 aWebbing semantified scholarly communication datasets for improve  c2012  a245 - 2530 v103 aThe success of Linked Data project has played a vital role in the realization of the Semantic Web on a global stage. It has motivated people to publish datasets which are important for information linking, resource discovery and can further make contributions in shaping the Web as a single connected data space. This effort has successfully amassed a variety of Linked Data and has introduced many novel ways for the publishing of data. As a result, putting Linked Data online has become rather easy, but actually linking the data with already existing data in the cloud and further on presentation of post-interlinking data are still researchable challenges. The search and identification of relevant datasets as well as devising a strategy for linking to these datasets with post-organization of interlinked data for human perceivable presentation is still a difficult task. In this paper, a novel approach is presented which 1) highlights and implements the steps involved in the interlinking process and 2) proposed a proof of concept application for automatic generation of an organized profile for post interlinked data presentation. These approaches are applied and presented as a case study focusing on interlinking scholarly communication datasets and highlighting the potential benefits of Linked Data. This study has interlinked two semantified scholarly datasets and was successfully able to discover new resources which were further organized into profile for showcasing potentials of Linked Data.10aCase study10aInterlinking scholarly datasets10aLinked Open Data (LOD)10aSemantic web1 aLatif, A.1 aTochtermann, K.  uhttp://www.scopus.com/inward/record.url?eid=2-s2.0-84866447762&partnerID=40&md5=15e762eee3e9e8e6b5060785d45a923c01946nas a2200265   4500008004100000245005700041210005700098260000900155300001400164490000600178520115700184653001301341653002901354653002601383653002701409653001701436653000801453653002001461100001401481700001601495700001601511700001601527700002001543856011701563       2010                        eng d00aHarvesting pertinent resources from Linked Open Data0 aHarvesting pertinent resources from Linked Open Data  c2010  a205 - 2120 v83 aLinked Open Data (LOD) is becoming an essential part of the Semantic Web. Although LOD has amassed large quantities of structured data from diverse, openly available data sources, there is still a lack of user-friendly interfaces and mechanisms for exploring this huge resource. In this paper, we describe a methodology for harvesting relevant information from the gigantic LOD cloud. The methodology is based on combination of information: identification, extraction, integration and presentation. Relevant information is identified by using a set of heuristics. The identified information resource is extracted by employing an intelligent URI discovery technique. The extracted information is further integrated with the help of a Concept Aggregation Framework. Then the information is presented to end users in logical informational aspects. Thereby, the proposed system is capable of hiding complex underlying semantic mechanics from end users and reducing the users' cognitive load in locating relevant information. In this paper, we describe the methodology and its implementation in the CAF-SIAL system, and compare it with the state of the art.10aCAF-SIAL10aInformation presentation10aInformation retrieval10aLinked Open Data (LOD)10aSemantic web10aURI10aUser interfaces1 aLatif, A.1 aAfzal, M.T.1 aSaeed, A.U.1 aHoefler, P.1 aTochtermann, K.  uhttp://www.scopus.com/inward/record.url?eid=2-s2.0-79960685735&partnerID=40&md5=cc886d4db44fdc4f20722b7621aca818