Francesco Poggi

Dealing with structural patterns of XML documents

Evaluating collections of XML documents without paying attention to the schema they were written in may give interesting insights into the expected characteristics of a markup language, as well as any regularity that may span vocabularies and languages, and that are more fundamental and frequent than plain content models. In this paper we explore the idea of structural patterns in XML vocabularies, by examining the characteristics of elements as they are used, rather than as they are defined. We introduce from the ground up a formal theory of 8 plus 3 structural patterns for XML elements, and verify their identifiability in a number of different XML vocabularies. The results allowed the creation of visualization and content extraction tools that are completely independent of the schema and without any previous knowledge of the semantics and organization of the XML vocabulary of the documents.

Recognising document components in XML-based academic articles

Recognising textual structures (paragraphs, sections, etc.) provides abstract and more general mechanisms for describing documents independent of the particular semantics of specific markup schemas, tools and presentation stylesheets. In this paper we propose an algorithm that allows us to identify the structural role of each element in a set of homogeneous scientific articles stored as XML files.

Big Data Quality: A Roadmap for Open Data.

Open Data (OD) is one of the most discussed issue of Big Data which raised the joint interest of public institutions, citizens and private companies since 2009. However, the massive amount of freely available data has not yet brought the expected effects: as of today, there is no application that has fully exploited the potential provided by large and distributed information sources in a non-trivial way, nor any service has substantially changed for the better the lives of people. The era of a new generation applications based on OD is far to come. In this context, we observe that OD quality is one of the major threats to achieving the goals of the OD movement. The starting point of this case study is the quality of the OD released by the five Constitutional offices of Italy. Our exploratory case study aims to assess the quality of such releases and the real implementations of OD. The outcome suggests the need of a drastic improvement in OD quality. Finally we highlight some key quality principles for OD, and propose a roadmap for further research.

Annotations with EARMARK in practice: a fairy tale

There is still a gap between models for external annotations of markup documents and their applications. In this paper we present the EARMARK API, a Java framework that allows users to combine embedded markup with stand-off markup. We discuss a few relevant issues on adding annotations to TEI documents that refer to external entities and we show how to use EARMARK to link textual ranges of such documents to resources in the Linked Open Data.

It ROCS!: The RASH Online Conversion Service

In this poster paper we introduce the RASH Online Conversion Service, i.e., a Web application that allows the conversion of ODT documents into RASH, a HTML-based markup language for writing scholarly articles, and from RASH into LaTeX according to Springer LNCS and ACM ICPS.

Embedding semantic annotations within texts: the FRETTA approach

In order to make semantic assertions about the text content of a document we need a mechanism to identify and organize the text structures of the document itself. Such mechanism would closely resemble a document-oriented markup language and would be free of the classical constraints of an embedded markup language, having no limitations given by sequentiality, containment, or contiguity of text fragments. In the past years we developed EARMARK, our OWL proposal for expressing arbitrary semantic annotations about the structure and the text content of a document. In this paper we describe FRETTA, our mechanism for rendering arbitrary EARMARK annotations (including non-sequential, non-hierarchical and non-contiguous ones) in XML, bringing into a unifying framework a half dozen of syntactic tricks used in literature to handle overlapping structures in a strictly hierarchical language.

The RASH JavaScript Editor (RAJE): A Wordprocessor for Writing Web-first Scholarly Articles

The most used format for submitting and publishing papers in the academic domain is the Portable Document Format (PDF), since its possibility of being rendered in the same way independently from the device used for visualising it. However, the PDF format has some important issues as well, among which the lack of interactivity and the low degree of accessibility. In order to address these issues, recently some journals, conferences, and workshops have started to accept also HTML as Web-first submission/publication format. However, most of the people are not able to produce a well-formed HTML5 article from scratch, and they would, thus, need an appropriate interface, e.g. a word processor, for creating such HTML-compliant scholarly article. To provide a solution to the aforementioned issue, in this paper we introduce the RASH JavaScript Editor (a.k.a. RAJE), which is a multi platform word processor for writing scholarly articles in HTML natively. RAJE allows authors to write research papers by means of a user-friendly interface hiding the complexities of HTML5. We also discuss the outcomes of a user study where we asked some researchers to write a scientific paper using RAJE.

Semantic Run-Time Models for Self-Adaptive Systems: A Case Study

Todays software systems increasingly work in changing environments, where rapid modifications in user needs, resource variabilities and system faults require remarkable administrative efforts. In order to mitigate the costs for governing these activities, software systems are expected to dynamically self-adapt. The problem of supporting auto-adaptation, which is complex activity in itself, is further exacerbated when applied to legacy systems which have not been developed for this purpose. In this paper we introduce a novel approach to self-adaptation based on the MAPE-K paradigm, where semantic models are used to provide an unified view of the heterogeneous elements composing these systems, and reasoning mechanisms are leveraged to drive adaptation strategies. We present the implementation of an adaptation engine based these concepts that uses ontologies and Semantic Web technologies, and discuss its application in a real world case study. From this experience, we offer recommendations for future research in this area.

An application of semantic technologies to self adaptations

In this paper we present an approach to add self-adaptive features to software systems not initially designed to be self-adaptive. Rapid changes in users needs, available resources, and types of system faults are everyday concerns in operating complex systems. The ability to face these issues in a (semi-)automatic fashion is a welcome feature. MAPE-K (Monitor, Analyze, Plan, Execute - Knowledge), or one of its variations, is the basic architectural pattern around which most adaptation engines are built. The knowledge (K) element in that pattern is usually a collection of dynamic and static models representing relevant aspects of the system and its environment. Knowledge-based features can be encoded using various techniques and serve a number of disparate roles: providing dynamic views of the system (Reflection Models), representing reconfiguration policies (Evaluation Models), mapping reconfigurations into system-level adaptations (Execution Models), and so forth. In our approach all these models are unified by using ontologies and Semantic Web technologies; the resulting knowledge base is then used to drive adaptation activities. We discuss how the various MAPE-K components can be designed in order to take advantage of this knowledge base by applying our approach to a real-word case study: a deployed system that was not designed to perform automatic adaptation. We then discuss merits and limits of our proposal both in the context of this specific case study and in a broader scope.

Exploring Bibliographies for Research-related Tasks

Bibliographies are fundamental tools for research communities. Besides the obvious uses as connection to previous research, citations are also widely used for evaluation purposes: the productivity of researchers, departments and universities is increasingly measured by counting their citations. Unfortunately, citations counters are just rough indicators: a deeper knowledge of individual citations -- where, when, by whom and why -- improves research evaluation tasks and supports researchers in their daily activity. Yet, such information is mostly hidden within repositories of scholarly papers and is still difficult to find, navigate and make use of. In this paper, we present a novel tool for exploring scientific articles through their citations. The environment is built on top of a rich citation network, encoded as a LOD, and includes a user-friendly interface to access, filter and highlight information about bibliographic data.