Automated Knowledge Base Quality Assessment and Validation based on Evolution Analysis

In recent years, numerous efforts have been put towards sharing Knowledge Bases (KB) in the Linked Open Data (LOD) cloud. These KBs are being used for various tasks, including performing data analytics or building question answering systems. Such KBs evolve continuously: their data (instances) and schemas can be updated, extended, revised and refactored. However, unlike in more controlled types of knowledge bases, the evolution of KBs exposed in the LOD cloud is usually unrestrained, what may cause data to suffer from a variety of quality issues, both at a semantic level and at a pragmatic level. This situation affects negatively data stakeholders – consumers, curators, etc. –. Data quality is commonly related to the perception of the fitness for use, for a certain application or use case. Therefore, ensuring the quality of the data of a knowledge base that evolves is vital. Since data is derived from autonomous, evolving, and increasingly large data providers, it is impractical to do manual data curation, and at the same time, it is very challenging to do a continuous automatic assessment of data quality. Ensuring the quality of a KB is a non-trivial task since they are based on a combination of structured information supported by models, ontologies, and vocabularies, as well as queryable endpoints, links, and mappings. Thus, in this thesis, we explored two main areas in assessing KB quality: (i) quality assessment using KB evolution analysis, and (ii) validation using machine learning models. The evolution of a KB can be analyzed using fine-grained “change” detection at low-level or using “dynamics” of a dataset at high-level. In this thesis, we present a novel knowledge base quality assessment approach using evolution analysis. The proposed approach uses data profiling on consecutive knowledge base releases to compute quality measures that allow detecting quality issues. However, the first step in building the quality assessment approach was to identify the quality characteristics. Using high-level change detection as measurement functions, in this thesis we present four quality characteristics: Persistency, Historical Persistency, Consistency and Completeness. Persistency and historical persistency measures concern the degree of changes and lifespan of any entity type. Consistency and completeness measures identify properties with incomplete information and contradictory facts. The approach has been assessed both quantitatively and qualitatively on a series of releases from two knowledge bases, eleven releases of DBpedia and eight releases of 3cixty Nice. However, high-level changes, being coarse-grained, cannot capture all possible quality issues. In this context, we present a validation strategy whose rationale is twofold. First, using manual validation from qualitative analysis to identify causes of quality issues. Then, use RDF data profiling information to generate integrity constraints. The validation approach relies on the idea of inducing RDF shape by exploiting SHALL constraint components. In particular, this approach will learn, what are the integrity constraints that can be applied to a large KB by instructing a process of statistical analysis, which is followed by a learning model. We illustrate the performance of our validation approach by using five learning models over three sub-tasks, namely minimum cardinality, maximum cardinality, and range constraint. The techniques of quality assessment and validation developed during this work are automatic and can be applied to different knowledge bases independently of the domain. Furthermore, the measures are based on simple statistical operations that make the solution both flexible and scalable

Linked Data Quality Assessment: A Survey

Data is of high quality if it is fit for its intended use in operations, decision-making, and planning. There is a colossal amount of linked data available on the web. However, it is difficult to understand how well the linked data fits into the modeling tasks due to the defects present in the data. Faults emerged in the linked data, spreading far and wide, affecting all the services designed for it. Addressing linked data quality deficiencies requires identifying quality problems, quality assessment, and the refinement of data to improve its quality. This study aims to identify existing end-to-end frameworks for quality assessment and improvement of data quality. One important finding is that most of the work deals with only one aspect rather than a combined approach. Another finding is that most of the framework aims at solving problems related to DBpedia. Therefore, a standard scalable system is required that integrates the identification of quality issues, the evaluation, and the improvement of the linked data quality. This survey contributes to understanding the state of the art of data quality evaluation and data quality improvement. A solution based on ontology is also proposed to build an end-to-end system that analyzes quality violations\u27 root causes

GATE : a simulation toolkit for PET and SPECT

Monte Carlo simulation is an essential tool in emission tomography that can assist in the design of new medical imaging devices, the optimization of acquisition protocols, and the development or assessment of image reconstruction algorithms and correction techniques. GATE, the Geant4 Application for Tomographic Emission, encapsulates the Geant4 libraries to achieve a modular, versatile, scripted simulation toolkit adapted to the field of nuclear medicine. In particular, GATE allows the description of time-dependent phenomena such as source or detector movement, and source decay kinetics. This feature makes it possible to simulate time curves under realistic acquisition conditions and to test dynamic reconstruction algorithms. A public release of GATE licensed under the GNU Lesser General Public License can be downloaded at the address http://www-lphe.epfl.ch/GATE/

Partitioning and Microdosimetry of Plutonium-239 and 55-Iron in Environmental Bacteria Grown in Liquid Cultures

The work presented herein provides quantitative data related to bacteria exposed in situ to two radionuclides relevant to nuclear sensing: plutonium-239 (239Pu) and iron-55 (55Fe). Originally motivated by the fundamental science underlying biosensing, liquid cultures of Pseudomonas putida and Escherichia coli were exposed to radionuclides over the course of 15-day experimental periods with the intent of gaining insight into the response of these bacteria. An essential component of characterizing or utilizing this response in a meaningful way is an understanding of the dose leading to that response. This dissertation narrows the knowledge gap associated with dose-response of microorganisms at environmentally relevant radionuclide concentrations through consideration of factors that influence the local dose, i.e., microdosimetry, experienced by the bacteria. These studies found that 239Pu accumulation in P. putida cells increased initially but plateaued after about 5 days, whether or not complexed with citrate. Moreover, 239Pu concentration in E. coli cells was greater than that in P. putida cells which may be the result of a stronger complexing agent made by E. coli for the purpose of Fe uptake. In cultures grown with 55Fe, over 75% of 55Fe was located in cell samples because of internal and external accumulation. When P. putida cultures were grown with 239Pu and 55Fe in combination, as well as 239Pu in combination with stable Fe, results indicate that 239Pu inhibited the uptake of 55Fe, and that the presence of Fe in cultures may promote pathways for Fe accumulation that are used by 239Pu. Finally, consideration of RNA extractions specifically suggested that 239Pu and 55Fe detected in RNA extraction samples is the result of binding to RNA prior to the time of extraction, as opposed to flow through or binding after cell lysis, and it highlights the practical importance of nucleic acid sample characterization to radiation protection, more generally. The work presented in this dissertation supports a more robust understanding of the behavior of 239Pu and 55Fe in bacteria systems and provides the groundwork necessary for the development of appropriate microdosimetric models for bacteria as well as more informed interpretation of transcriptomic analysis

Dual gated PET/CT imaging of heart

Coronary artery disease (CAD) resulting from atherosclerotic arterial changes, plaques, is a progressive process, which can be asymptomatic for many years. Asymptomatic CAD can cause a heart attack that leads to sudden death if the vulnerable coronary plaque ruptures and causes artery occlusion. The plaque inflammation plays an important role in the rupture susceptibility. Reliable anticipation of rupture is still clinically impossible for a single patient. Detection of the vulnerable coronary plaques before clinical signs remains a significant scientific challenge where positron emission tomography (PET) can play an important role. The aim of this dissertation was to find out whether a small, coronary plaque size, heart structures could be detected by a clinically available positron emission tomography and computed tomography (PET/CT) hybrid camera in realistically moving cardiac phantoms, a minipig model, and patients with CAD. Due to cardiac motions accurate detection of small heart structures are known to be problematic in PET imaging. Due to absence of commercial application at the beginning of the study, new dual gating method for cardiac PET imaging was developed and programmed that takes into account both contraction and respiratory induced cardiac motions. Cardiac phantom PET studies showed that small, active and moving plaques can be distinguished from myocardium activity and the gating methods improved the detection sensitivity and resolution of the plaques. In minipig and CAD patient cardiac PET studies small structures of myocardium and coronary arteries was detected more sensitive and accurately when using dual gating method than manufacturer gating methods. In cardiac patient PET study respiratory induced cardiac motions were shown to be linearly dependent with spirometry-measured respiratory volumes. Standard 3-lead electrocardiogram (ECG) measurement can be filtered by anesthesia monitor to detect lung impedance signal. In cardiac patient PET study this lung impedance signal were applied for respiratory gating. In this study was observed that the 3-lead ECG derived impedance signal gating method detects respiratory induced cardiac motion in PET as well as other externally used respiratory gating methods. In summary, the dual gated cardiac PET method is more sensitive and accurate to detect small cardiac structures, as coronary vessel wall pathology, than the commercial methods used in the study.Sydämen kaksoisliiketahdistettu PET/CT kuvantaminen Ateroskleroottisten valtimomuutosten, plakkien, seurauksena asteittain kehittyvä sepelvaltimotauti voi olla vuosia oireeton. Oireeton sepelvaltimotauti voi aiheuttaa äkkikuolemaan johtavan sydäninfarktin, mikäli sepelvaltimon seinämäplakin repeytymisestä aiheutuu verisuonen tukkiva hyytymä. Tutkimuksissa on osoitettu, että plakin tulehduksella on merkittävä rooli repeytymisalttiudelle. Repeytymisen luotettava ennakointi on yksittäisen potilaan kohdalla edelleen kliinisesti mahdotonta. Tulehtuneiden ja repeytymisalttiiden sepelvaltimoplakkien toteaminen ennen kliinisiä oireita on edelleen merkittävä tieteellinen haaste, missä positroniemissiotomografia (PET) kuvantamisella voi olla merkittävä rooli. Väitöskirjan tavoitteena oli selvittää, voidaanko kliinisessä käytössä olevalla positroniemissiotomografia ja tietokonetomografia (PET/TT) yhdistelmäkameralla havaita pieniä, sepelvaltimoplakkien kokoisia, sydämen rakenteita koneellisesti toimivissa todenmukaisissa sydänmalleissa, eläinmallissa ja sepelvaltimotautia sairastavilla potilailla. Sydämen pienten rakenteiden tarkka havaitseminen PET/TTkameroilla on haasteellista sydämen liikkumisen vuoksi. Tutkimuksessa kehitettiin ja ohjelmoitiin uusi sydämen PET-kuvantamisen liiketahdistusmenetelmä, joka ottaa huomioon sekä sydämen supistusliikkeen että hengitysliikkeen vaikutuksen sydämen PET kuvantamissa. Koneellisilla sydänmalleilla osoitettiin, että PET on riittävän herkkä havaitsemaan pieniä ja liikkuvia radioaktiivisia ”sepelvaltimoplakkeja”, ja että liiketahdistusmenetelmät parantavat plakkien havaitsemisherkkyyttä ja tarkkuutta. Eläinmallissa ja sepelvaltimotautipotilailla kaksoisliiketahdistusmenetelmän herkkyys ja tarkkuus havaita pieniä sydänlihaksen ja sepelvaltimoiden rakenteita todettiin kaupallisia tahdistusmenetelmiä paremmaksi. Potilastutkimuksissa todettiin hengityksen aiheuttama sydämen liike PET-kuvissa lineaarisesti riippuvaiseksi spirometrialla mitattujen hengitystilavuuksien kanssa. Tavallisesta 3-johtoisesta sydänsähkökäyrästä voidaan anestesiamonitorin avulla suodattaa keuhkojen impedanssisignaalia. Hengitysliikkeen aiheuttama potilaiden sydämen liike PETkuvissa havaittiin yhtä hyvin käyttämällä tätä keuhkojen impedanssisignaalia kuin muita yleisesti käytettäviä ulkoisia hengitystahdistussignaaleja. Todetaan, että kaksoisliiketahdistettu sydämen PET-kuvantamismenetelmä on tutkimuksessa käytettyjä kaupallisia menetelmiä herkempi ja tarkempi havaitsemaan sydämen pieniä rakenteita sekä sepelvaltimon seinämän tulehdusplakkeja

Environmental and experimental evaluation of producing chemicals from CO2 using bioelectrochemical systems

Ph. D. ThesisMicrobial electrosynthesis (MES) which uses microbes and electricity to generate high grade chemicals could contribute to the reduction of greenhouse emissions as it uses CO2 in the process. The implementation of this technology on an industrial scale could be on the horizon. Currently, little is known about the environmental loads associated with the successful scale up of the technology with regards to global warming potential and other environmental burdens. Such knowledge is needed in order for relatively new bioprocesses like MES to be sustainably scaled up and industrially applied. This research conducted an empirical and environmental investigation of MES for the synthesis of chemicals from CO2. Experimentally, MES for bio production of chemicals from CO2 was investigated using mixed culture as biocatalyst. CO2 introduced into H-shaped bioelectrochemical systems produced methane, formic, acetic and propionic acids more readily however under some conditions isobutyric acid and ethanol were synthesized. Different polarizations (-0.8V, -1.0V, -1.2V and -1.4V vs Ag/AgCl) and temperatures (27oC and 40oC) were used revealing that bioproduction was affected by changes to these parameters. Biofilm growth and gradual acclimation to CO2 achieved a maximum production rate of 3677μM/day at -1.4V vs Ag/AgCl and 40oC. However an average decline of 18 percent in the coulombic efficiency was observed when the potential was reduced by 0.2V.This showed that there may be energy and environmental risks associated with products synthesized at lower potentials needing confirmation by an environmental analysis. The environmental impacts of products synthesized through MES were examined by modelling a simulated industrial plant (1000 tonnes/year). Environmental analyses were used to reveal the main products to target for MES. Different MES plants generating a range of biochemicals were modelled considering two sources of energy (natural gas and UK national grid), one at a time. This gave specific and detailed scenarios that allowed comparison of the environmental impacts. Results shows that the synthesis of acetic acid, propionic acid, ethanol and methanol released more carbon dioxide than it used for both natural gas and the UK national grid. However, formic acid (-3,421 tonnes CO2 eqv) was found to be the only product having a negative global warming potential using natural gas and comparatively low environmental impacts in other environmental categories. It was concluded that formic acid synthesis through MES is a more suitable product than the other biochemicals analysed in terms of energy efficiency, global warming potential and other potentially harmful environmental impact categories.Petroleum Technology Development Fund, Nigeri