Innovation with open data: Essential elements of open data ecosystems

Abstract

Open data ecosystems are expected to bring many advantages, such as stimulating citizen participation and innovation. However, scant attention has been given to what constitutes an open data ecosystem. The objective of this paper is to provide an overview of essential elements of open data ecosystems for enabling easy publication and use of open data. To achieve this objective, the literature has been reviewed and a scenario about the publication and use of open data has been analyzed. It was found that various applications, tools and portals are available which together can form an ecosystem. The best functionalities of this ecosystem can be selected and utilized by open data providers and users. To create an open data ecosystem at least four key elements should be captured, namely, 1) releasing and publishing open data on the internet, 2) searching, finding, evaluating and viewing data and their related licenses, 3) cleansing, analyzing, enriching, combining, linking and visualizing data and 4) interpreting and discussing data and providing feedback to the data provider and other stakeholders. Furthermore, to integrate the ecosystem elements and to let them act as an integrated whole, there should be three additional elements 5) user pathways showing directions for how open data can be used, 6) a quality management system and 7) different types of metadata to be able to connect the elements.

The Impact of Open Data in the Uk: Complex, Unpredictable, and Political

“…The data released so far represent the first steps in an evolving ‘ecology’ of Open Data (Cornford et al ; Zuiderwijk et al ). On the evidence to date, as a democratic instrument, the local spending data add a further element of turbulence and unpredictability to the political process (Hale et al ).…”

Application of an Ecosystem Methodology Based on Legal Language Processing for the Transformation of Court Decisions and Legal Opinions into Open Data

“…Currently, more researchers have been highlighting the need to replace traditional Open Data practices with approaches that focus on the larger Open Data environment, known as the Open Data ecosystem, in order to create value from Open Data. For an extensive literature review on this subject, one may refer to [22]. Following this "ecosystem" approach, the researchers in [23] combined steps from existing models in an extended Open Data lifecycle, which consists of the following stages: create/gather, pre-process, curate, store/obtain, publish, retrieve/acquire, process, use, collaborate with users, and provide feedback.…”

“…Following this "ecosystem" approach, the researchers in [23] combined steps from existing models in an extended Open Data lifecycle, which consists of the following stages: create/gather, pre-process, curate, store/obtain, publish, retrieve/acquire, process, use, collaborate with users, and provide feedback. As Open Data ecosystems involve a data provider and a data user level [22], the researchers imagined that the above stages form two interdependent cycles [21]: the inner one referring to the data provider level (create, preprocess, curate, store/obtain, publish) and the outer one to the data user level (retrieve/acquire, process, use, collaborate with users, and provide feedback). Similarly, Lnenicka and Komarkova [24] focusing on Big and Open Linked Data (BOLD) ecosystems, identified several types of involved stakeholders (ecosystem orchestrator, service provider, application provider, data producer, data publisher, data user, and data prosumer) and proposed a BOLD analytics lifecycle consisting of six phases: acquisition and extraction, management and preparation, storage and archiving, processing and analysis, visualization and use, publication, sharing, Information 2020, 11, 10 4 of 30 and reuse.…”

Open data for competitive advantage

“…The scenario was used to identify resources that are typically needed for open data use by companies. Information about activities conducted for open data use was collected from the open data literature [e.g., 34,35,36], and this provided input for the creation of the scenario. The topic of the scenario concerned a company that needed to find a location to build and sell bungalows.…”