Open Government Datasets Research Articles

Putting People First in Data Quality: Feminist Data Ethics for Open Government Datasets

ABSTRACTOpen government information systems offer great potential for advancing civic life and democracy, but they also reflect and reinforce the biases and systematic inequalities faced by members of socially marginalized groups. We present results from a critical data modeling project that uses a data quality framework to examine open datasets published by police departments in order to understand how data modeling choices shape the social impact of these datasets. Using an arrest record dataset published by the Los Angeles Police Department as a case study, we present we present results detailing the representation of racial data and the presence of children in the dataset. We argue that current data quality frameworks for open government data are insufficient for critical data studies due to an orientation around institutional and computational interests. Incorporating feminist data ethics into data quality analysis provides an approach to data quality that centers people and communities. We propose a definition for data quality of open government datasets based on an ethics of care that centers the needs of vulnerable populations and accountability of institutions toward their communities.

Estimating primary substation boundaries and the value of mapping Great Britain's electrical network infrastructure

Localised data aggregation in many countries including Great Britain (GB) is typically performed at a geographical level with polygon boundaries that have a robust and trusted governance system in place. This means there is confidence in a process to create a set of polygons that have unique identifiers coupled to geographical areas, and the ability to have these updated through a defined code of practice. Examples found across many countries are in the delivery of post, such as post codes and zip codes, and of the definition of census areas and municipal boundaries. The confidence in these boundaries allows different data to be aggregated by third parties, which itself provides greater amounts of data over comparable geographical areas to enhance wider analysis and decision making. As helpful as these polygons are for certain types of analyses, they are not specifically defined for energy systems analysis. Here we combine publicly available datasets published from the six regional electricity Distribution Network Operators of GB to produce a new geospatial dataset with 4436 unique polygons defining the areas served by electrical primary substations. An example demonstrating the value of these polygons is given to link these polygons with postcode level open government datasets on domestic energy consumption (2015–2020) from the Department of Energy Security and Net Zero (DESNZ). The resulting new data reflects energy statistics aggregated to the geographical areas served by each primary electrical substation across Great Britain. The significant value of the generated data is demonstrated by the quantification of the domestic annual heating demand presently met by natural gas across different primary substation areas which varies from an average of 5100 kWh to 28,900 kWh per property. This highlights how the rate of electrical capacity expansion will have to differ by geography under an electrified heating scenario. Therefore, we believe there is a compelling argument for all countries to set up processes to create and update polygons that have a meaningful relationship to energy systems. This would allow more accurate energy systems analysis to be performed, ultimately leading to an accelerated or potentially lower cost transition to a net zero world.

EUBUCCO v0.1: European building stock characteristics in a common and open database for 200+ million individual buildings

Building stock management is becoming a global societal and political issue, inter alia because of growing sustainability concerns. Comprehensive and openly accessible building stock data can enable impactful research exploring the most effective policy options. In Europe, efforts from citizen and governments generated numerous relevant datasets but these are fragmented and heterogeneous, thus hindering their usability. Here, we present eubucco v0.1, a database of individual building footprints for ~202 million buildings across the 27 European Union countries and Switzerland. Three main attributes – building height, construction year and type – are included for respectively 73%, 24% and 46% of the buildings. We identify, collect and harmonize 50 open government datasets and OpenStreetMap, and perform extensive validation analyses to assess the quality, consistency and completeness of the data in every country. eubucco v0.1 provides the basis for high-resolution urban sustainability studies across scales – continental, comparative or local studies – using a centralized source and is relevant for a variety of use cases, e.g., for energy system analysis or natural hazard risk assessments.

QODA – Methodology and Legislative Background for Assessment of Open Government Datasets Quality

In last few years, many open government data portals have been emerging in the world. These portals publish open government datasets which can be accessed and used by everyone for their own needs. In this paper, we propose methodology named QODA (Quality of Open government DAtasets) for assessment of quality of published datasets via two aspects. First one is assessment of quality of pure open government datasets, and second is assessment of quality features on the platforms which contributes to the publication of quality datasets. It provides a step-by-step dataset analysis guidance and summarization of results. Research presented in this paper shows that open government dataset quality depends on data provider as well as proper definition of metadata behind datasets. Our findings result in recommendations to open government data (OGD) publishers, to constantly supervise the use of published datasets, with aim to have timely and punctual information on OGD portals, with special attention on quality features.

Ontology-Based Semantic Search Framework for Disparate Datasets

The public sector provides open data to create new opportunities, stimulate innovation, and implement new solutions that benefit academia and society. However, open data is usually available in large quantities and often lacks quality, accuracy, and completeness. It may be difficult to find the right data to analyze a target. There are many rich open data repositories, but they are difficult to understand and use because these data can only be used with a complex set of keyword search options, and even then, irrelevant or insufficient data may eventually be retrieved. To alleviate this situation, ontology-based semantic search has been proven to be an effective way to improve the quality of related content queries in such repositories. In this paper, we propose a new method of semantic linking and storing open government datasets of New Zealand's agriculture, land and rainfall sectors based on the use of ontology. The generated ontology can construct integrated data, in which a unified query can be applied to extract richer and more useful information. To validate our model, we showed how to link ontology manually and automatically. Manual linking requires domain experts, and automatic linking reduces the overhead of relying on domain experts to manually link concepts. The results of this method are promising in terms of improving data quality and search efficiency. In future, the proposed model can be integrated with other domain ontologies.

Risks shift along seafood supply chains

Seafood is a highly traded commodity and 71% of the United States (U.S.) supply is imported. This study addresses questions about imported seafood safety and compares risks of outbreaks and recalls across countries of origin, species, and stages of the supply chain. We found that where seafood comes from does not play a major role in risk. Risk is a function of the activities happening at each stage of the supply chain, inherent riskiness of some products or processes, and “pass through” risks introduced at upstream and midstream stages of the supply chain. Dominant farmed species (shrimp, tilapia, catfish) became less risky as they move along the supply chain toward consumers. We recommend investments in agencies overseeing food safety and health, enhanced traceability within supply chains, and more open government datasets that support systems-level analyses.

Academic social networks and collaboration patterns

PurposeThis study attempts to use a new source of data collection from open government data sets to identify potential academic social networks (ASNs) and defines their collaboration patterns. The purpose of this paper is to propose a direction that may advance our current understanding on how or why ASNs are formed or motivated and influence their research collaboration.Design/methodology/approachThis study first reviews the open data sets in Taiwan, which is ranked as the first state in Global Open Data Index published by Open Knowledge Foundation to select the data sets that expose the government’s R&D activities. Then, based on the theory review of research collaboration, potential ASNs in those data sets are identified and are further generalized as various collaboration patterns. A research collaboration framework is used to present these patterns.FindingsProject-based social networks, learning-based social networks and institution-based social networks are identified and linked to various collaboration patterns. Their collaboration mechanisms, e.g., team composition, motivation, relationship, measurement, and benefit-cost, are also discussed and compared.Originality/valueIn traditional, ASNs have usually been known as co-authorship networks or co-inventorship networks due to the limitation of data collection. This study first identifies some ASNs that may be formed before co-authorship networks or co-inventorship networks are formally built-up, and may influence the outcomes of research collaborations. These information allow researchers to deeply dive into the structure of ASNs and resolve collaboration mechanisms.

Open Government Data for Digital Services: Effects on Innovation, Competition and Societal Benefits

Prompted by recent open data policies in the European Union and the United States, administrations increasingly publish their public sector information. Opening government data for broad commercial re-use is thereby motivated by three primary policy goals: innovation, competition and societal benefits. However, so far, a comprehensive evaluation of how open government data affects re-users' incentives and ensuing market outcomes in the digital economy is missing. Therefore, we conduct a conceptual analysis of the economic effects of open government data and characterize conditions under which primary policy goals can be achieved. Our findings highlight a basic trade-off between innovation and competition goals and demonstrate that the effectiveness of open government data crucially depends on the information contained in a data set. By distinguishing different information domains, we derive insights for policy makers on which open government data sets can promote a desired policy goal and how to balance economic trade-offs.

Towards linked open government data in Canada

Governments are publishing enormous amounts of open data on the web every day in an effort to increase transparency and reusability. Linking data from multiple sources on the web enables the performance of advanced data analytics, which can lead to the development of valuable services and data products. However, Canada's open government data portals are isolated from one another and remain unlinked to other resources on the web. In this paper, we first expose the statistical data sets in Canadian provincial open data portals as Linked Data, and then integrate them using RDF Cube vocabulary, thereby making different open data portals available through a single search endpoint. We leverage Semantic Web Technologies to publish open data sets taken from two provincial portals (Nova Scotia and Alberta) as RDF (the Linked Data format), and to connect them to one another. The success of our approach illustrates its high potential for linking open government data sets across Canada, which will in turn enable greater data accessibility and improved search results.

Feedback driven improvement of data preparation pipelines

Data preparation, whether for populating enterprise data warehouses or as a precursor to more exploratory analyses, is recognised as being laborious, and as a result is a barrier to cost-effective data analysis. Several steps that recur within data preparation pipelines are amenable to automation, but it seems important that automated decisions can be refined in the light of user feedback on data products. There has been significant work on how individual data preparation steps can be refined in the light of feedback. This paper goes further, by proposing an approach in which feedback on the correctness of values in a data product can be used to revise the results of diverse data preparation components. The approach uses statistical techniques, both in determining which actions should be applied to refine the data preparation process and to identify the values on which it would be most useful to obtain further feedback. The approach has been implemented to refine the results of matching, mapping and data repair components in the VADA data preparation system, and is evaluated using deep web and open government data sets from the real estate domain. The experiments have shown how the approach enables feedback to be assimilated effectively for use with individual data preparation components, and furthermore that synergies result from applying the feedback to several data preparation components.

Exploring the extent of openness of open government data – A critique of open government datasets in the UK

The claim of the open government data (OGD) movement is that it would add considerable value to the political, economic and social development of nations. Thus, during the past few years, governments around the world have been under increasing pressure to release data to encourage citizen participation in government. In the UK, the government publishes its data on the data.gov.uk website for the public to find, view, download and interrogate.11See: https://data.gov.uk/. In this paper, we evaluate the extent of openness of OGD in the UK – a recognised global leader in the OGD movement – by examining a sample of 400 datasets listed on this website. The examination uses an ‘ordinary citizen’ test, which is developed based on the original eight Sebastopol principles of open data. Our examination discovers that existing prevalent measures of openness of data are inadequate. Our findings demonstrate that the majority of the published government resources on the website are informational rather than granular data. In fact, only a small minority of these advertised as open data are actually open, which severely limits their open government utilities.

A Comparison of Geovisualizations and Data Tables for Transparency Enablement in the Open Government Data Landscape

Recent years have witnessed progress of public institutions in making their datasets available online, free of charge, for re-use. There have been however limited studies which assess the actual effectiveness of different communication media in making key facts visible to citizens. This article analysed and systematically compared two representations which are relevant in the context of open government data: geovisualizations and data tables. An empirical user study (N=16) revealed that both types of representations have their strengths: geovisualizations make spatial knowledge and the attractiveness of open government data more visible, while data tables are more adequate for the communication of numerical data. The ideas presented are relevant to open data publishers interested in strategies to effectively put the hidden knowledge in current open government datasets into the hands of citizens.

Quantifying the Interoperability of Open Government Datasets

A proposed technique quantifies the semantic interoperability of open government datasets with three metrics calculated using a set of statements that indicate for each pair of identifiers in the system whether or not they represent the same concept.