Structure preserving specification languages for knowledge-based systems

Much of the work on validation and verification of knowledge based systems (KBSs) has been done in terms of implementation languages (mostly rule-based languages). Recent papers have argued that it is advantageous to do validation and verification in terms of a more abstract and formal specification of the system. However, constructing such formal specifications is a difficult task. This paper proposes the use of formal specification languages for KBS-development that are closely based on the structure of informal knowledge-models. The use of such formal languages has as advantages that (i) we can give strong support for the construction of a formal specification, namely on the basis of the informal description of the system; and (ii) we can use the structural correspondence to verify that the formal specification does indeed capture the informally stated requirements

A Survey of Languages for Specifying Dynamics: A Knowledge Engineering Perspective

A number of formal specification languages for knowledge-based systems has been developed. Characteristics for knowledge-based systems are a complex knowledge base and an inference engine which uses this knowledge to solve a given problem. Specification languages for knowledge-based systems have to cover both aspects. They have to provide the means to specify a complex and large amount of knowledge and they have to provide the means to specify the dynamic reasoning behavior of a knowledge-based system. We focus on the second aspect. For this purpose, we survey existing approaches for specifying dynamic behavior in related areas of research. In fact, we have taken approaches for the specification of information systems (Language for Conceptual Modeling and TROLL), approaches for the specification of database updates and logic programming (Transaction Logic and Dynamic Database Logic) and the generic specification framework of abstract state machine

FishMark: A Linked Data Application Benchmark

Abstract. FishBase is an important species data collection produced by the FishBase Information and Research Group Inc (FIN), a not-forprofit NGO with the aim of collecting comprehensive information (from the taxonomic to the ecological) about all the world’s finned fish species. FishBase is exposed as a MySQL backed website (supporting a range of canned, although complex queries) and serves over 33 million hits per month. FishDelish is a transformation of FishBase into LinkedData weighing in at 1.38 billion triples. We have ported a substantial number of FishBase SQL queries to FishDelish SPARQL query which form the basis of a new linked data application benchmark (using our derivative of the Berlin SPARQL Benchmark harness). We use this benchmarking framework to compare the performance of the native MySQL application, the Virtuoso RDF triple store, and the Quest OBDA system on a fishbase.org like application.

An Infrastructure for acquiring high quality semantic metadata

Because metadata that underlies semantic web applications is gathered from distributed and heterogeneous data sources, it is important to ensure its quality (i.e., reduce duplicates, spelling errors, ambiguities). However, current infrastructures that acquire and integrate semantic data have only marginally addressed the issue of metadata quality. In this paper we present our metadata acquisition infrastructure, ASDI, which pays special attention to ensuring that high quality metadata is derived. Central to the architecture of ASDI is a erification engine that relies on several semantic web tools to check the quality of the derived data. We tested our prototype in the context of building a semantic web portal for our lab, KMi. An experimental evaluation omparing the automatically extracted data against manual annotations indicates that the verification engine enhances the quality of the extracted semantic metadata

Diet quality and depressive symptoms in adolescence: no cross-sectional or prospective associations following adjustment for covariates.

OBJECTIVE: Adolescence is a critical period for development of depression and understanding of behavioural risk factors is needed to support appropriate preventive strategies. We examined associations between adolescent diet quality and depressive symptoms, cross-sectionally and prospectively, in a large community cohort, adjusting for behavioural and psychosocial covariates. DESIGN: Prospective community-based cohort study (ROOTS). SETTING: Secondary schools in Cambridgeshire and Suffolk, UK. SUBJECTS: Study participants (n 603) who completed 4 d diet diaries at age 14 years and reported depressive symptoms (Moods and Feelings Questionnaire (MFQ)) at 14 and 17 years of age. RESULTS: Diet data were processed to derive a Mediterranean diet score (MDS) and daily servings of fruit and vegetables, and fish. At age 14 years, a negative association between fruit and vegetable intake and MFQ score was seen in the unadjusted cross-sectional regression model (β=-0·40; 95 % CI -0·71,-0·10), but adjustment for behavioural covariates, including smoking and alcohol consumption, attenuated this association. Fish intake and MDS were not cross-sectionally associated with MFQ score. No prospective associations were found between MDS, fruit and vegetable intake or fish intake and later MFQ score. CONCLUSIONS: Diet quality was not associated with depressive symptoms in mid-adolescence. Previously reported associations in this age range may be due to confounding. Further longitudinal studies are needed that investigate associations between adolescent diet and depression across different time frames and populations, ensuring appropriate adjustment for covariates

A corpus of images and text in online news

In recent years, several datasets have been released that include images and text, giving impulse to new methods that combine natural language processing and computer vision. However, there is a need for datasets of images in their natural textual context. The ION corpus contains 300K news articles published between August 2014 - 2015 in five online newspapers from two countries. The 1-year coverage over multiple publishers ensures a broad scope in terms of topics, image quality and editorial viewpoints. The corpus consists of JSON-LD files with the following data about each article: the original URL of the article on the news publisher’s website, the date of publication, the headline of the article, the URL of the image displayed with the article (if any), and the caption of that image. Neither the article text nor the images themselves are included in the corpus. Instead, the images are distributed as high-dimensional feature vectors extracted from a Convolutional Neural Network, anticipating their use in computer vision tasks. The article text is represented as a list of automatically generated entity and topic annotations in the form of Wikipedia/DBpedia pages. This facilitates the selection of subsets of the corpus for separate analysis or evaluation

A Systematic Review of Amenable Resilience Factors That Moderate and/or Mediate the Relationship Between Childhood Adversity and Mental Health in Young People.

Background: Up to half of Western children and adolescents experience at least one type of childhood adversity. Individuals with a history of childhood adversity have an increased risk of psychopathology. Resilience enhancing factors reduce the risk of psychopathology following childhood adversity. A comprehensive overview of empirically supported resilience factors is critically important for interventions aimed to increase resilience in young people. Moreover, such an overview may aid the development of novel resilience theories. Therefore, we conducted the first systematic review of social, emotional, cognitive and/or behavioral resilience factors after childhood adversity. Methods: We systematically searched Web of Science, PsycINFO, and Scopus (e.g., including MEDLINE) for English, Dutch, and German literature. We included cohort studies that examined whether a resilience factor was a moderator and/or a mediator for the relationship between childhood adversity and psychopathology in young people (mean age 13-24). Therefore, studies were included if the resilience factor was assessed prior to psychopathology, and childhood adversity was assessed no later than the resilience factor. Study data extraction was based on the STROBE report and study quality was assessed with an adapted version of Downs and Black's scale. The preregistered protocol can be found at: http://www.crd.york.ac.uk/PROSPERO/display_record.asp?ID=CRD42016051978. Results: The search identified 1969 studies, of which 22 were included (eight nationalities, study sample n range: 59-6780). We found empirical support for 13 of 25 individual-level (e.g., high self-esteem, low rumination), six of 12 family-level (e.g., high family cohesion, high parental involvement), and one of five community-level resilience factors (i.e., high social support), to benefit mental health in young people exposed to childhood adversity. Single vs. multiple resilience factor models supported the notion that resilience factors should not be studied in isolation, and that interrelations between resilience factors should be taken into account when predicting psychopathology after childhood adversity. Conclusions: Interventions that improve individual, family, and/or social support resilience factors may reduce the risk of psychopathology following childhood adversity. Future research should scrutinize whether resilience factors function as a complex interrelated system that benefits mental health resilience after childhood adversity.AvH is supported by the Royal Society (620 DH15017 & RGF\EA\180029), and MQ (MQBFC/2). JF is supported by the Medical Research Council Doctoral Training/Sackler Fund and the Pinsent Darwin Fund. HC was supported by CLAHRC - East of England at the time of data analysis. PW’s personal unrestricted research account paid for some incidental costs of obtaining papers. Funders of the authors played no role in the conduction or reporting of the systematic review