Fabrizio Orlandi

A systematic review of open government data initiatives

Abstract We conduct a systematic survey with the aim of assessing open government data initiatives, that is; any attempt, by a government or otherwise, to open data that is produced by a governmental entity. We describe the open government data life-cycle and we focus our discussion on publishing and consuming processes required within open government data initiatives. We cover current approaches undertaken for such initiatives, and classify them. A number of evaluations found within related literature are discussed, and from them we extract challenges and issues that hinder open government initiatives from reaching their full potential. In a bid to overcome these challenges, we also extract guidelines for publishing data and provide an integrated overview. This will enable stakeholders to start with a firm foot in a new open government data initiative. We also identify the impacts on the stakeholders involved in such initiatives.

Aggregated, interoperable and multi-domain user profiles for the social web

User profiling techniques have mostly focused on retrieving and representing a users knowledge, context and interests in order to provide recommendations, personalise search, and build user-adaptive systems. However, building a user profile on a single social network limits the quality and completeness of the profile, especially when interoperability of the profile is key and its reuse on different sites is necessary for providing other types of personalisation. Indeed recent studies have shown that users on the Social Web often use different social networking sites for diverse, and sometimes non-overlapping, purposes and interests. In this paper, we describe our methodology for the automatic creation and aggregation of interoperable and multi-domain user profiles of interests using semantic technologies. Moreover, we propose a user study on different user profiling techniques for social networking websites in general, and for Twitter and Facebook in particular. In this regard, based on the results of our user evaluation, we investigate (i) the accuracy of different methodologies for profiling, (ii) the effect of time decay functions on ranking user interests, and (iii) the benefits of merging different user models using semantic technologies.

LinkDaViz --- Automatic Binding of Linked Data to Visualizations

As the Web of Data is growing steadily, the demand for user-friendly means for exploring, analyzing and visualizing Linked Data is also increasing. The key challenge for visualizing Linked Data consists in providing a clear overview of the data and supporting non-technical users in finding suitable visualizations while hiding technical details of Linked Data and visualization configuration. In order to accomplish this, we propose a largely automatic workflow which guides users through the process of creating visualizations by automatically categorizing and binding data to visualization parameters. The approach is based on a heuristic analysis of the structure of the input data and a comprehensive visualization model facilitating the automatic binding between data and visualization parameters. The resulting assignments are ranked and presented to the user. With LinkDaViz we provide a web-based implementation of the approach and demonstrate the feasibility by an extended user and performance evaluation.

Semantic search on heterogeneous Wiki systems

This paper describes a system to enable semantic search across heterogeneous wikis in an unified way using Semantic Web technologies. In particular, we discuss (i) how we designed a common model for representing social and structural wiki features and (ii) how we extracted semantic data from wikis using Mediawiki and Dokuwiki. On this basis, we show how we built and efficient application with a simple user-interface enabling semantic searching and browsing capabilities on the top of different interlinked wikis.

How Much? is not Enough: an Analysis of Open Budget Initiatives

A worldwide movement towards the publication of Open Government Data is taking place, and budget data is one of the key elements pushing this trend. Its importance is mostly related to transparency, but publishing budget data, combined with other actions, can also improve democratic participation, allow comparative analysis of governments and boost data-driven business. However, the lack of standards and common evaluation criteria still hinders the development of appropriate tools and the materialization of the appointed benefits. In this paper, we present a model to analyse government initiatives to publish budget data. We identify the main features of these initiatives with a double objective: (i) to drive a structured analysis, relating some dimensions to their possible impacts, and (ii) to derive characterization attributes to compare initiatives based on each dimension. We define use perspectives and analyse some initiatives using this model. We conclude that, in order to favour use perspectives, special attention must be given to user feedback, semantics standards and linking possibilities.

Matching Natural Language Relations to Knowledge Graph Properties for Question Answering

Research has seen considerable achievements concerning translation of natural language patterns into formal queries for Question Answering (QA) based on Knowledge Graphs (KG). One of the main challenges in this research area is about how to identify which property within a Knowledge Graph matches the predicate found in a Natural Language (NL) relation. Current approaches for formal query generation attempt to resolve this problem mainly by first retrieving the named entity from the KG together with a list of its predicates, then filtering out one from all the predicates of the entity. We attempt an approach to directly match an NL predicate to KG properties that can be employed within QA pipelines. In this paper, we specify a systematic approach as well as providing a tool that can be employed to solve this task. Our approach models KB relations with their underlying parts of speech, we then enhance this with extra attributes obtained from Wordnet and Dependency parsing characteristics. From a question, we model a similar representation of query relations. We then define distance measurements between the query relation and the properties representations from the KG to identify which property is referred to by the relation within the query. We report substantive recall values and considerable precision from our evaluation.

Challenges and opportunities in renovating public sector information by enabling linked data and analytics

Linked Data has become the current W3C recommended approach for publishing data on the World Wide Web as it is sharable, extensible, and easily re-usable. An ecosystem of linked data hubs in the Public Sector has the potential to offer significant benefits to its consumers (other public offices and ministries, as well as researchers, citizens and SMEs), such as increased accessibility and re-use value of their data through the use of web-scale identifiers and easy interlinking with datasets of other public data providers. The power and flexibility of the schema-defying Linked Data, however, is counterbalanced by inborn factors that diminish the potential for cost-effective and efficient adoption by the Public Sector. The paper analyzes these challenges in view of the current state-of-the-art in linked data technologies and proposes a technical framework that aims to hide the underlying complexity of linked data while maintaining and promoting the interlinking capabilities enabled by the Linked Data Paradigm. The paper presents the innovations behind our proposed solutions as well as their advantages, especially for the non-expert users.

Data Value Networks: Enabling a New Data Ecosystem

With the increasing permeation of data into all dimensions of our information society, data is progressively becoming the basis for many products and services. It is hence becoming more and more vital to identify the means and methods how to exploit the value of this data. In this paper we provide our definition of the Data Value Network, where we specifically cater for non-tangible data products. We also propose a Demand and Supply Distribution Model with the aim of providing insight on how an entity can participate in the global data market by producing a data product, as well as a concrete implementation through the Demand and Supply as a Service. Through our contributions we project our vision of generating a new Economic Data Ecosystem that has the Web of Data as its core.

Towards Cleaning-Up Open Data Portals: A Metadata Reconciliation Approach

This paper presents an approach for metadata reconciliation, curation and linking for Open Governamental Data Portals (ODPs). ODPs have been lately the standard solution for governments willing to put their public data available for the society. Portal managers use several types of metadata to organize the datasets, one of the most important ones being the tags. However, the tagging process is subject to many problems, such as synonyms, ambiguity or incoherence, among others. As our empiric analysis of ODPs shows, these issues are currently prevalent in most ODPs and effectively hinders the reuse of Open Data. In order to address these problems, we develop and implement an approach for tag reconciliation in Open Data Portals, encompassing local actions related to individual portals, and global actions for adding a semantic metadata layer above individual portals. The local part aims to enhance the quality of tags in a single portal, and the global part is meant to interlink ODPs by establishing relations between tags.

Value Creation on Open Government Data

Governments are one of the largest producers and collectors of data in many different domains. As one major aim of open government data initiatives is the release of social and commercial value, we here explore existing processes of value creation on government data. We identify the dimensions that impact, or are impacted by value creation, and distinguish between the different value creating roles and participating stakeholders. We propose the use of Linked Data as an approach to enhance the value creation process, and provide a Value Creation Assessment Framework to analyse the resulting impact.