From science to practice: Bringing innovations to agronomy and forestry

The challenge of the work presented here is to make innovative research output in the agronomy and forestry domain accessible to end-users, so that it can be practically applied. We have developed an approach that consists of three key-elements: an ontology with domain knowledge, a set of documents that have been annotated and meta-annotated, and a system (ask-Valerie) that is based on a dialogue to represent the interaction between end user and system.<br/> We show that the dialogue-metaphor is a good way of modelling the interaction between user and system. The system helps the user in formulating his question and in answering it in a useful way. Meta-annotations of key-paragraphs in the document-base turn out to be relevant in assessing in one glance what the content of a document is. <br/> End-users are very enthusiastic about the possibilities that ask-Valerie offers them in translating scientific results to their own situation

Using multiple related ontologies in a fuzzy information retrieval model.

With the Semantic Web progress many independently developed distinct domain ontologies have to be shared and reused by a variety of applications. The use of ontologies in information retrieval applications allows the retrieval of semantically related documents to an initial users´ query. This work presents a fuzzy information retrieval model for improving the document retrieval process considering a knowledge base composed of multiple domain ontologies that are fuzzy related. Each ontology can be represented independently as well as their relationships. This knowledge organization is used in a novel method to expand the user initial query and to index the documents in the collection. Experimental results show that the proposed model presents better overall performance when compared with another fuzzy-based approach for information retrieval.SBIA 2008

Applying Wikipedia to Interactive Information Retrieval

There are many opportunities to improve the interactivity of information retrieval systems beyond the ubiquitous search box. One idea is to use knowledge bases—e.g. controlled vocabularies, classification schemes, thesauri and ontologies—to organize, describe and navigate the information space. These resources are popular in libraries and specialist collections, but have proven too expensive and narrow to be applied to everyday webscale search. Wikipedia has the potential to bring structured knowledge into more widespread use. This online, collaboratively generated encyclopaedia is one of the largest and most consulted reference works in existence. It is broader, deeper and more agile than the knowledge bases put forward to assist retrieval in the past. Rendering this resource machine-readable is a challenging task that has captured the interest of many researchers. Many see it as a key step required to break the knowledge acquisition bottleneck that crippled previous efforts. This thesis claims that the roadblock can be sidestepped: Wikipedia can be applied effectively to open-domain information retrieval with minimal natural language processing or information extraction. The key is to focus on gathering and applying human-readable rather than machine-readable knowledge. To demonstrate this claim, the thesis tackles three separate problems: extracting knowledge from Wikipedia; connecting it to textual documents; and applying it to the retrieval process. First, we demonstrate that a large thesaurus-like structure can be obtained directly from Wikipedia, and that accurate measures of semantic relatedness can be efficiently mined from it. Second, we show that Wikipedia provides the necessary features and training data for existing data mining techniques to accurately detect and disambiguate topics when they are mentioned in plain text. Third, we provide two systems and user studies that demonstrate the utility of the Wikipedia-derived knowledge base for interactive information retrieval

Cognitive Ontology based Framework for Networking Women in Sciences

In order to increase the percentage of women in academics or researchers, there is need for a functioning research networking through which women can exchange ideas; ask questions and more importantly, mentorship, in Nigeria. In order to make for this, several recommendations have been suggested but are not scientific. Therefore, to bridge this gap scientifically, this paper is presenting an overview of a question and answering system framework that hybridize semantic search methodology and cognitive reasoning. The hybridization will enhance the question and answering accuracy especially due to the introduction of domain ontology for the semantic process. This paper also presents the output of the first phase of the implementation which is the development of the domain ontology for the question and answering syste

Design of Multiple Ontology Based Agro Knowledge Mining Model

Farming is regarded as a major industry in India, accounting for 17% of the country's GDP growth. Agriculture employs 60% of the population hence it is considered an important sector in India. The important factors for agriculture are pest management, disease prevention, irrigation management, soil mineral composition, crop management, location, and the season in which the crop is grown. Hence all this information along with the techniques are well known only by the experienced farmers. Hence it is important to create an agro knowledge management system. As a result, this work makes an attempt to develop a multiple ontology-based agro knowledge management system. The designed system consists of agriculture information related to attributes of soil mineral, moisture, season, location, crop type, and temperature. It consists of multiple ontologies such as soil ontology, crop ontology, location ontology, and crop season ontology to provide agronomy knowledge. Soil ontology is premeditated to classify the soil type in a hierarchical order while crop ontology classifies the crop type, location ontology classifies locations suitable for different crop types and finally, crop season ontology classifies the season that is suitable for different crops. A rule base is built to develop the knowledge base and to validate the truthfulness of the knowledge base. Visualization of a knowledge base is carried out for better understanding and decision-making

Lifecycle-Support in Architectures for Ontology-Based Information Systems

Ontology-based applications play an increasingly important role in the public and corporate Semantic Web. While today there exist a range of tools and technologies to support specific ontology engineering and management activities, architectural design guidelines for building ontology-based applications are missing. In this paper, we present an architecture for ontology-based applications—covering the complete ontology-lifecycle—that is intended to support software engineers in designing and developing ontology based-applications. We illustrate the use of the architecture in a concrete case study using the NeOn toolkit as one implementation of the architecture

User-centered semantic dataset retrieval

Finding relevant research data is an increasingly important but time-consuming task in daily research practice. Several studies report on difficulties in dataset search, e.g., scholars retrieve only partial pertinent data, and important information can not be displayed in the user interface. Overcoming these problems has motivated a number of research efforts in computer science, such as text mining and semantic search. In particular, the emergence of the Semantic Web opens a variety of novel research perspectives. Motivated by these challenges, the overall aim of this work is to analyze the current obstacles in dataset search and to propose and develop a novel semantic dataset search. The studied domain is biodiversity research, a domain that explores the diversity of life, habitats and ecosystems. This thesis has three main contributions: (1) We evaluate the current situation in dataset search in a user study, and we compare a semantic search with a classical keyword search to explore the suitability of semantic web technologies for dataset search. (2) We generate a question corpus and develop an information model to figure out on what scientific topics scholars in biodiversity research are interested in. Moreover, we also analyze the gap between current metadata and scholarly search interests, and we explore whether metadata and user interests match. (3) We propose and develop an improved dataset search based on three components: (A) a text mining pipeline, enriching metadata and queries with semantic categories and URIs, (B) a retrieval component with a semantic index over categories and URIs and (C) a user interface that enables a search within categories and a search including further hierarchical relations. Following user centered design principles, we ensure user involvement in various user studies during the development process

Sidra5: a search system with geographic signatures

Tese de mestrado em Engenharia Informática, apresentada à Universidade de Lisboa através da Faculdade de Ciências, 2007Este trabalho consistiu no desenvolvimento de um sistema de pesquisa de informação com raciocínio geográfico, servindo de base para uma nova abordagem para modelação da informação geográfica contida nos documentos, as assinaturas geográficas. Pretendeu-se determinar se a semântica geográfica presente nos documentos, capturada através das assinaturas geográficas, contribui para uma melhoria dos resultados obtidos para pesquisas de cariz geográfico. São propostas e experimentadas diversas estratégias para o cálculo da semelhança entre as assinaturas geográficas de interrogações e documentos. A partir dos resultados observados conclui-se que, em algumas circunstâncias, as assinaturas geográficas contribuem para melhorar a qualidade das pesquisas geográficas.The dissertation report presents the development of a geographic information search system which implements geographic signatures, a novel approach for the modeling of the geographic information present in documents. The goal of the project was to determine if the information with geographic semantics present in documents, captured as geographic signatures, contributes to the improvement of search results. Several strategies for computing the similarity between the geographic signatures in queries and documents are proposed and experimented. The obtained results show that, in some circunstances, geographic signatures can indeed improve the search quality of geographic queries

Enrichment of the Phenotypic and Genotypic Data Warehouse analysis using Question Answering systems to facilitate the decision making process in cereal breeding programs

Currently there are an overwhelming number of scientific publications in Life Sciences, especially in Genetics and Biotechnology. This huge amount of information is structured in corporate Data Warehouses (DW) or in Biological Databases (e.g. UniProt, RCSB Protein Data Bank, CEREALAB or GenBank), whose main drawback is its cost of updating that makes it obsolete easily. However, these Databases are the main tool for enterprises when they want to update their internal information, for example when a plant breeder enterprise needs to enrich its genetic information (internal structured Database) with recently discovered genes related to specific phenotypic traits (external unstructured data) in order to choose the desired parentals for breeding programs. In this paper, we propose to complement the internal information with external data from the Web using Question Answering (QA) techniques. We go a step further by providing a complete framework for integrating unstructured and structured information by combining traditional Databases and DW architectures with QA systems. The great advantage of our framework is that decision makers can compare instantaneously internal data with external data from competitors, thereby allowing taking quick strategic decisions based on richer data.This paper has been partially supported by the MESOLAP (TIN2010-14860) and GEODAS-BI (TIN2012-37493-C03-03) projects from the Spanish Ministry of Education and Competitivity. Alejandro Maté is funded by the Generalitat Valenciana under an ACIF grant (ACIF/2010/298)