Percy Salas

Publishing Statistical Data on the Web

Statistical data is one of the most important sources of information, relevant for large numbers of stakeholders in the governmental, scientific and business domains alike. In this article, we overview how statistical data can be managed on the Web. With OLAP2 Data Cube and CSV2 Data Cube we present two complementary approaches on how to extract and publish statistical data. We also discuss the linking, repair and the visualization of statistical data. As a comprehensive use case, we report on the extraction and publishing on the Web of statistical data describing 10 years of life in Brazil.

Open government data in Brazil

This article discusses the current status of open government data in Brazil and summarizes the lessons learned from publishing Brazilian government data as linked data.

PUBLISHING STATISTICAL DATA ON THE WEB

Statistical data is one of the most important sources of information, relevant for large numbers of stakeholders in the governmental, scientific and business domains alike. In this article, we over...

Interoperability by design using the StdTrip tool: an a priori approach

A database conceptual schema is a high-level description of how database concepts are organized, typically as a set of classes of objects and their attributes. Triplification is the process by which a database schema, and its instances, are transformed into a RDF dataset. A major step in this process is deciding how to represent database schema concepts in terms of RDF classes and properties. This is done by mapping database concepts to a vocabulary, to be used as the base in which to generate the RDF triples from. The construction of this vocabulary is extremely important, because the more one reuses well known standards, the easier it will be to interlink the result to other existing datasets. Most triplifying engines today provide support to the mechanical process of transforming relational to RDF data. However, to best of our knowledge, none provide user support during the conceptual modeling stage. In this paper, we present StdTrip, a tool that guides users in this process. If possible, the tool promotes the reuse of standard, W3C recommended RDF vocabularies, or otherwise suggests the reuse of vocabularies already adopted by other RDF datasets.

The role of constraints in linked data

The paper argues that a Linked Data source should publish an application ontology that includes a set of constraints that capture the semantics of the classes and properties used to model the data. Furthermore, if the Linked Data source publishes a mapping between its vocabulary and the vocabulary of a domain ontology, then it has to specify the application ontology constraints so that they are consistent with those of the domain ontology. The main contributions of the paper are methods for constructing the constraints of the application ontology of a Linked Data source, defined as fragments of domain ontologies. The methods assume that the ontologies are written in an expressive family of attributive languages and depend on a procedure to test logical implication, which explores the structure of sets of constraints.

StdTrip: Promoting the Reuse of Standard Vocabularies in Open Government Data

Linked Data is the standard generally adopted for publishing Open Government Data. This operation requires that a myriad of public information datasets be converted to a set of RDF triples. A major step in this process is deciding how to represent the database schema concepts in terms of RDF classes and properties. This is done by mapping database concepts to a vocabulary, which will be used as the base for generating the RDF representation. The construction of this vocabulary is extremely important, because it determines how the generated triples interlink the resulting dataset with other existing ones. However, most engines today provide support only to the mechanical process of transforming relational to RDF data. In this chapter, we discuss this process and present the StdTrip framework, a tool that supports the conceptual modeling stages of the production of RDF datasets, promoting the reuse of W3C recommended standard RDF vocabularies or suggesting the reuse of non-standard vocabularies already adopted by other RDF datasets.

RDB2RDF plugin: relational databases to RDF plugin for eclipse

RDB2RDF is the process by which a relational database schema (RDB) is transformed into a set of RDF triples. A major step in this process is deciding how to represent database schema concepts in terms of RDF classes and properties. This correlation is described in the RDB2RDF mapping file, which is used as the base for the generation of RDF triples. Most RDB2RDF engines today provide support to the mechanical process of transforming RDB to RDF, each with its own mapping language. Due to this fact, the W3C RDB2RDF Working Group has been working to standardize a language to map relational data to RDF called R2RML. Part of their efforts is directed to fostering the development of methods, tools and techniques to support standard RDB2RDF mapping strategies. In this paper, we introduce an Eclipse plug-in that supports the standard RDB to RDF Mapping Language (R2RML) to produce Direct Mappings in RDF.

RDB2RDF: A relational to RDF plug-in for Eclipse

The process of transforming data stored in relational databases (RDBs) into sets of Resource Description Framework (RDF) triples is known as triplification or RDB2RDF. It consists of two consecutive operations, schema extraction and data conversion. Schema extraction is a process similar to creating an external schema, and contains a collection of database views. The data conversion is divided into two steps. The first step consists of deciding how to represent database schema concepts in terms of RDF classes and properties, defining an RDB2RDF mapping. The second step consists of the actual conversion of relational data to RDF data instances, based on the mapping previously defined. Although the schema extraction is very well understood, the data conversion operation is still murky. Indeed, the World Wide Web Consortium RDB2RDF Working Group has been working to define a standard language, called R2RML, to describe RDB2RDF mapping files. The definition of the R2RML, however, is still undergoing changes. In this paper, we introduce an Eclipse plug‐in that supports the entire conversion process. Its architecture takes into consideration the specificities of the triplification process by providing a modular structure that encapsulates the stable and well‐understood components separately from the volatile, change‐prone mapping strategies. The latter are accessible via a well‐defined interface to promote information hiding and separation of concerns and to facilitate evolution. Copyright

A mediator for statistical linked data

This paper introduces a mediation architecture to help describing and consuming statistical data, exposed as RDF triples, but stored in relational databases. The architecture features a catalogue of linked data cube descriptions, created according to the Linked Data principles. The catalogue has a standardized description for each data cube actually stored in each statistical (relational) database known to the mediation environment. The mediator offers an interface to browse the linked data cube descriptions and exports the data cubes as RDF triples, generated on demand from the underlying databases.

Understanding IT Organizations Using Viewpoints

Understanding IT organizations is essential for ensuring a successful transformation phase in IT outsourcing deals. However, this process of understanding is regard as a hard task, since usually there are important differences between its current (AS-IS) state and the desired (TO-BE) state. It becomes a greater problem when there are different models of both AS-IS and TO-BE states in an organization. We present a methodology based on viewpoint concepts from requirement engineering. This methodology allows us to represent and visualize distinct viewpoints models of an IT organization from several perspectives and to compare these models in order to help design changes to bring the organization from an AS-IS state to a TO-BE state.