2014
DOI: 10.15446/ing.investig.v34n1.39449
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Visualization of information: a proposal to improve the search and access to digital resources in repositories

Abstract: Presently, the most notable challenges associated with repositories in resolving problems of searches of digital resources, lie in providing an understanding of resource classification according to a knowledge representation scheme and the relationship between them. However, one of the areas with very little research in the field is the study of visual search interfaces that provide access to relevant materials in digital repositories; more specifically, in the access of digital resources according to areas an… Show more

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Cited by 22 publications
(13 citation statements)
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“…In the same way, it is proposed as a guide the use of open educational resources to conduct linking processes through technologies like Linked Data [7]. This way, the inter-operability of digital resources through semantic models that classify them may be used based on related knowledge fields, using information visualization and classification methods like the ones defined by [12]. For this, the use and classification of educative repositories by related topics is proposed, so that a web of repositories with academic content and specialized according to the needs of users using tools previously mentioned like Linked Data [40], categorization or agent systems, will be available to implant new methods of search based on specialized search engines.…”
Section: Discussionmentioning
confidence: 99%
See 1 more Smart Citation
“…In the same way, it is proposed as a guide the use of open educational resources to conduct linking processes through technologies like Linked Data [7]. This way, the inter-operability of digital resources through semantic models that classify them may be used based on related knowledge fields, using information visualization and classification methods like the ones defined by [12]. For this, the use and classification of educative repositories by related topics is proposed, so that a web of repositories with academic content and specialized according to the needs of users using tools previously mentioned like Linked Data [40], categorization or agent systems, will be available to implant new methods of search based on specialized search engines.…”
Section: Discussionmentioning
confidence: 99%
“…Nowadays, the users face the need of finding more relevant academic resources for their necessities and their personal characteristics and cultural aspects based on suitable visual search interfaces [11][12][13]; nonetheless, locating resources in an infrastructure like Internet, that does not stop growing, is a complex activity. For this reason, there are strategies proposed to optimize location processes.…”
Section: B Contents Searchmentioning
confidence: 99%
“…Although there are similar studies in order to improve access to learning objects in repositories [37], [41], [42], and the use of the Web of Trust concept [34], [43] there are no studies related with the use of intelligent agents and the use of the Web of Trust in LCMS, such as Moodle and Efront. Notwithstanding the obtained results in the agent response time, it is important to clarify that aspects such as bandwidth connection, number of requests made to the server, and operational burden from other running applications on the server were not considered, elements that significantly affect the agent response time.…”
Section: Discussionmentioning
confidence: 99%
“…Considering the differences and features of the knowledge representation schemes analysed by [29], as well as the approaches raised by [28] on knowledge representation schemes, Table I shows some of the most representative features provided by each of these knowledge representation schemes and which are focused on the development of digital repositories. According to previous studies made by [30,8], in the design of digital repositories, the most common instruments used to represent knowledge are: taxonomies, ontologies, thesauri, graphs, mind maps, among others. Fig.…”
Section: A Analysis Of Knowledge Representation Schemementioning
confidence: 99%