Ontologies and the Semantic Web: Problems and Perspectives for LIS Professionals

Many years have passed since Berners-Lee envi- sioned the Web as it should be (1999), but still many information professionals do not know their precise role in its development, especially con- cerning ontologies –considered one of its main elements. Why? May it still be a lack of under- standing between the different academic commu- nities involved (namely, Computer Science, Lin- guistics and Library and Information Science), as reported by Soergel (1999)? The idea behind the Semantic Web is that of several technologies working together to get optimum information re- trieval performance, which is based on proper resource description in a machine-understandable way, by means of metadata and vocabularies (Greenberg, Sutton and Campbell, 2003). This is obviously something that Library and Information Science professionals can do very well, but, are we doing enough? When computer scientists put on stage the ontology paradigm they were asking for semantically richer vocabularies that could support logical inferences in artificial intelligence as a way to improve information retrieval systems. Which direction should vocabulary development take to contribute better to that common goal? The main objective of this paper is twofold: 1) to identify main trends, issues and problems con- cerning ontology research and 2) to identify pos- sible contributions from the Library and Information Science area to the development of ontologies for the semantic web. To do so, our paper has been structured in the following manner. First, the methodology followed in the paper is reported, which is based on a thorough literature review, where main contributions are analysed. Then, the paper presents a discussion of the main trends, issues and problems concerning ontology re- search identified in the literature review. Recom- mendations of possible contributions from the Library and Information Science area to the devel- opment of ontologies for the semantic web are finally presented.

Produção e degradação da serrapilheira de espécies lenhosas da caatinga e sua contribuição na recuperação de áreas degradadas.

Resumo: O entendimento do fluxo de produção e do aporte de nutrientes via decomposição da serrapilheira e as interações do processo com parâmetros edáficos e ciclagem de nutrientes de espécies nativas da Caatinga têm sido pouco estudados. O conhecimento sobre ciclagem de nutrientes em florestas manejadas também permite inferências sobre as espécies com maior capacidade de reciclagem de nutrientes e seu potencial para recuperação de áreas degradadas. Objetivou-se com isso avaliar a produção e a degradação da serrapilheira de oito espécies lenhosas da Caatinga e mensurar os efeitos de sua aplicação sobre a fertilidade do solo e sobre a produção de sorgo em solo degradado. Para isso realizou-se três ensaios: para o ensaio I quantificou-se a produção de serrapilheira em um delineamento inteiramente casualizado com 6 repetições, por meio da instalação de coletores sob a projeção da copa das espécies (tratamentos): mofumbo, sabiá, jurema-preta, jucá, catingueira, pereiro, pau-branco e marmeleiro, sendo o material coletado mensalmente; foram quantificadas a produção das frações folhas, caule, material reprodutivo, miscelânea e total, bem como o aporte de nutrientes no período chuvoso e seco. Para o ensaio II avaliou-se a taxa de degradação da fração folhas de cada espécie citada por meio da utilização de litter bags, em delineamento inteiramente casualizado com 4 repetições, as coletas foram aos 0, 30, 60, 90, 120 e 150 dias, em seguida quantificou-se os macro e micronutrientes, celulose, lignina e carbono em cada tempo de amostragem. Para o ensaio III, realizou-se experimento em casa de vegetação para mensurar os efeitos da aplicação dos resíduos da serrapilheira das mesmas espécies mencionadas nos ensaios anteriores (I e II) sobre a fertilidade do solo e a produção de sorgo em solo degradado, neste experimento adotou-se o delineamento em blocos casualizados com 5 tratamentos e 5 repetições, sendo avaliadas doses equivalentes a: 0, 15, 30, 60 e 120 kg ha-1 de N dos resíduos de cada espécie e um tratamento adicional com adubação mineral, totalizando 30 unidades experimentais para cada espécie. As variáveis mensuradas foram biométricas, biomassa, teor relativo de clorofila e nitrogênio total, além de análises de fertilidade do solo. Com a análise dos dados verificou-se que a época de maior produção de serrapilheira ocorreu no final do período chuvoso para o início do período seco. A espécie jucá apresentou maior produção de serrapilheira, comparado às outras espécies. O nutriente cálcio apresentou maior acúmulo na serrapilheira para as espécies mofumbo, sabiá, catingueira, pereiro e marmeleiro e o nitrogênio foi superior para as espécies jurema-preta, jucá e pau-branco. Para todas as espécies avaliadas no ensaio de degradação houve redução significativa na sua biomassa em relação ao tempo zero, apresentando a seguinte ordem de velocidade de decomposição: jurema-preta > catingueira > pau-branco > jucá > marmeleiro > mofumbo > pereiro > sabiá. No ensaio de fertilização com os resíduos verificou-se que o marmeleiro promoveu efeitos negativos no solo, como acidificação. Porém, a aplicação dos resíduos da espécie pau-branco foi a que promoveu aumento nos valores de K, SB e CEC do solo e na produção do sorgo os resíduos de jurema-preta e pau-branco foram as que promoveram aumento na massa seca das plantas. Enquanto a adubação mineral proporcionou aumento na produção de massa seca do sorgo, demonstrando que a associação entre adubo mineral e o uso da serrapilheira de espécies da Caatinga pode ser uma opção viável para acelerar a recuperação de solos degradados. Abstract: The understanding of the production flow and nutrient supply via decomposition of litter and process interactions with edaphic parameters and nutrient cycling of native species of the Caatinga has been little studied. The knowledge of nutrient cycling in managed forests also allow inferences about species with capacity greater nutrient recycling capacity and its potential for recovery of degraded areas. This study aimed to evaluate the production and litter degradation 8 woody species of Caatinga and measure the effects of its application on soil fertility and production of sorghum in degraded soil. To this was carried out three tests: for the test I quantified the production of litter in a completely randomized design with 6 replications, by installing collectors under the canopy projection in the species (treatments): mofumbo, sabiá, jurema-preta, jucá, catingueira, pereiro, pau-branco and marmeleiro for each species, and the material collected monthly, were quantified the production of fractions leaves, stem, reproductive material, miscellany and total nutrient intake in the rainy and dry season. For II test evaluated the degradation rate of the fraction leaves through the use of litter bags, in a completely randomized design with 4 replications, the collected was 0, 30, 60, 90, 120 and 150 days and quantitated nutrients, cellulose, lignin and carbon at each evaluation time. For the III test, there was the experiment in a greenhouse to measure the effects of the application of litter waste of the same species of previous tests (I and II) on soil fertility and production of sorghum in degraded soil, was adopted the randomized block design with 5 treatments and 5 replications and evaluated doses equivalent to: 0, 15, 30, 60 and 120 kg ha-1 N of waste each species and an additional treatment with mineral fertilizer, totaling 30 experimental units for each species. Biometric analysis and biomass, relative chlorophyll content and total nitrogen were proceeded. In addition to soil fertility analysis. With the data analysis it was found that the time of greatest litterfall occurred at the end of the rainy season to the beginning of the dry season. The jucá species showed higher production compared to other species. The nutrient calcium had higher accumulation for the species mofumbo, sabiá, catingueira, pereiro and marmeleiro and nitrogen was higher for species jurema-preta, jucá and pau-branco. All species evaluated in degradation test had a significant reduction in biomass over time zero. They presented the following order of decomposition rate: jurema-preta > catingueira > pau-branco > jucá > marmeleiro > mofumbo > pereiro > sabiá. For fertility test it was found that marmeleiro promoted negative effects on soil, such as acidification. However, pau-branco was the specie that promoted further improvements in the K values, SB and CEC to the soil and for the production of sorghum, the waste jurema-preta and pau-branco promoted increase in dry matter plants. While the mineral fertilization provided an increase in dry matter production of sorghum, demonstrating that the combination of mineral fertilizer and the use of litter of Caatinga species may be a viable option to speed up the recovery of degraded soils.

Ethical Perspectives on Big Data in Agri-food: Ownership and Governance for Safety

Big data are reshaping the way we interact with technology, thus fostering new applications to increase the safety-assessment of foods. An extraordinary amount of information is analysed using machine learning approaches aimed at detecting the existence or predicting the likelihood of future risks. Food business operators have to share the results of these analyses when applying to place on the market regulated products, whereas agri-food safety agencies (including the European Food Safety Authority) are exploring new avenues to increase the accuracy of their evaluations by processing Big data. Such an informational endowment brings with it opportunities and risks correlated to the extraction of meaningful inferences from data. However, conflicting interests and tensions among the involved entities - the industry, food safety agencies, and consumers - hinder the finding of shared methods to steer the processing of Big data in a sound, transparent and trustworthy way. A recent reform in the EU sectoral legislation, the lack of trust and the presence of a considerable number of stakeholders highlight the need of ethical contributions aimed at steering the development and the deployment of Big data applications. Moreover, Artificial Intelligence guidelines and charters published by European Union institutions and Member States have to be discussed in light of applied contexts, including the one at stake. This thesis aims to contribute to these goals by discussing what principles should be put forward when processing Big data in the context of agri-food safety-risk assessment. The research focuses on two interviewed topics - data ownership and data governance - by evaluating how the regulatory framework addresses the challenges raised by Big data analysis in these domains. The outcome of the project is a tentative Roadmap aimed to identify the principles to be observed when processing Big data in this domain and their possible implementations.

Reinforcement learning over encrypted data

Reinforcement learning is a particular paradigm of machine learning that, recently, has proved times and times again to be a very effective and powerful approach. On the other hand, cryptography usually takes the opposite direction. While machine learning aims at analyzing data, cryptography aims at maintaining its privacy by hiding such data. However, the two techniques can be jointly used to create privacy preserving models, able to make inferences on the data without leaking sensitive information. Despite the numerous amount of studies performed on machine learning and cryptography, reinforcement learning in particular has never been applied to such cases before. Being able to successfully make use of reinforcement learning in an encrypted scenario would allow us to create an agent that efficiently controls a system without providing it with full knowledge of the environment it is operating in, leading the way to many possible use cases. Therefore, we have decided to apply the reinforcement learning paradigm to encrypted data. In this project we have applied one of the most well-known reinforcement learning algorithms, called Deep Q-Learning, to simple simulated environments and studied how the encryption affects the training performance of the agent, in order to see if it is still able to learn how to behave even when the input data is no longer readable by humans. The results of this work highlight that the agent is still able to learn with no issues whatsoever in small state spaces with non-secure encryptions, like AES in ECB mode. For fixed environments, it is also able to reach a suboptimal solution even in the presence of secure modes, like AES in CBC mode, showing a significant improvement with respect to a random agent; however, its ability to generalize in stochastic environments or big state spaces suffers greatly.

Ethics in the flesh: formalizing moral values in embodied cognition

Values are beliefs or principles that are deemed significant or desirable within a specific society or culture, serving as the fundamental underpinnings for ethical and socio-behavioral norms. The objective of this research is to explore the domain encompassing moral, cultural, and individual values. To achieve this, we employ an ontological approach to formally represent the semantic relations within the value domain. The theoretical framework employed adopts Fillmore’s frame semantics, treating values as semantic frames. A value situation is thus characterized by the co-occurrence of specific semantic roles fulfilled within a given event or circumstance. Given the intricate semantics of values as abstract entities with high social capital, our investigation extends to two interconnected domains. The first domain is embodied cognition, specifically image schemas, which are cognitive patterns derived from sensorimotor experiences that shape our conceptualization of entities in the world. The second domain pertains to emotions, which are inherently intertwined with the realm of values. Consequently, our approach endeavors to formalize the semantics of values within an embodied cognition framework, recognizing values as emotional-laden semantic frames. The primary ontologies proposed in this work are: (i) ValueNet, an ontology network dedicated to the domain of values; (ii) ISAAC, the Image Schema Abstraction And Cognition ontology; and (iii) EmoNet, an ontology for theories of emotions. The knowledge formalization adheres to established modeling practices, including the reuse of semantic web resources such as WordNet, VerbNet, FrameNet, DBpedia, and alignment to foundational ontologies like DOLCE, as well as the utilization of Ontology Design Patterns. These ontological resources are operationalized through the development of a fully explainable frame-based detector capable of identifying values, emotions, and image schemas generating knowledge graphs from from natural language, leveraging the semantic dependencies of a sentence, and allowing non trivial higher layer knowledge inferences.