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The purpose of this paper is to derive design principles for improving the open data publishing process of public organizations. Although governments create large amounts of data, the publication of open data is often cumbersome and there are no standard procedures and processes for opening data, blocking the easy publication of government data.

Action design research (ADR) was used to derive design principles. The literature was used as a foundation, and discussion sessions with civil servants were used to evaluate the usefulness of the principles.

Barriers preventing easy and low-cost publication of open data were identified and connected to design principles, which can be used to guide the design of an open data publishing process. Five new principles are: start thinking about the opening of data at the beginning of the process; develop guidelines, especially about privacy and policy sensitivity of data; provide decision support by integrating insight in the activities of other actors involved in the publishing process; make data publication an integral, well-defined and standardized part of daily procedures and routines; and monitor how the published data are reused.

The principles are derived using ADR in a single case. A next step can be to investigate multiple comparative case studies and detail the principles further. We recommend using these principles to develop a reference architecture.

The design principles can be used by public organizations to improve their open data publishing processes. The design principles are derived from practice and discussed with practitioners. The discussions showed that the principles could improve the publication process.

Decreasing the barriers for publishing open government data could result in the publication of more open data. These open data can then be used to stimulate various public values, such as transparency, accountability, innovation, economic growth and informed decision- and policymaking.

Publishing data by public organizations is a complex and ill-understood activity. The lack of suitable business processes and the unclear division of responsibilities block publication of open data. This paper contributes to the literature by presenting design principles which can be used to improve the open data publishing process of public sector organizations.

Data providers have been increasingly publishing content as linked data (LD) on the Web. This process includes guidelines (i.e. good practices) to publish, share, and connect data on the Web. Several people in different areas, for instance, sciences, medicine, governments and so on, use these practices to publish data. The LD community has been proposing many practices to aid the publication of data on the Web. However, discovering these practices is a costly and time-consuming task, considering the practices that are produced by the literature. Moreover, the community still lacks a comprehensive understanding of how these practices are used for publishing LD. Thus, the purpose of this paper is to investigate and better understand how best practices support the publication of LD as well as identifying to what extent they have been applied to this field.

The authors conducted a systematic literature review to identify the primary studies that propose best practices to address the publication of LD, following a predefined review protocol. The authors then identified the motivations for recommending best practices for publishing LD and looked for evidence of the benefits of using such practices. The authors also examined the data formats and areas addressed by the studies as well as the institutions that have been publishing LD.

In summary, the main findings of this work are: there is empirical evidence of the benefits of using best practices for publishing LD, especially for defining standard practices, integrability and uniformity of LD; most of the studies used RDF as data format; there are many areas interested in dissemination data in a connected way; and there is a great variety of institutions that have published data on the Web.

The results presented in this systematic review can be very useful to the semantic web and LD community, since it gathers pieces of evidence from the primary studies included in the review, forming a body of knowledge regarding the use best practices for publishing LD pointing out interesting opportunities for future research.

The purpose of this paper is to detail a low-cost, low-maintenance publishing strategy aimed at unlocking the value of Linked Data collections held by libraries, archives and museums (LAMs).

The shortcomings of commonly used Linked Data publishing approaches are identified, and the current lack of substantial collections of Linked Data exposed by LAMs is considered. To improve on the discussed status quo, a novel approach for publishing Linked Data is proposed and demonstrated by means of an archive of DBpedia versions, which is queried in combination with other Linked Data sources.

The authors show that the approach makes publishing Linked Data archives easy and affordable, and supports distributed querying without causing untenable load on the Linked Data sources.

The proposed approach significantly lowers the barrier for publishing, maintaining, and making Linked Data collections queryable. As such, it offers the potential to substantially grow the distributed network of queryable Linked Data sources. Because the approach supports querying without causing unacceptable load on the sources, the queryable interfaces are expected to be more reliable, allowing them to become integral building blocks of robust applications that leverage distributed Linked Data sources.

The novel publishing strategy significantly lowers the technical and financial barriers that LAMs face when attempting to publish Linked Data collections. The proposed approach yields Linked Data sources that can reliably be queried, paving the way for applications that leverage distributed Linked Data sources through federated querying.

This article explores the recent turn within academic publishing towards ‘seamless access’, an approach to content provision that ensures users do not have to continually authenticate in order to access journal content.

Through a critical exploration of Get Full Text Research, a service developed collaboratively by five of the world's largest academic publishers to provide such seamless access to academic research, the article shows how publishers are seeking to control the ways in which readers access publications in order to trace, control and ultimately monetise user interactions on their platforms.

Theorised as a process of individuation through infrastructure, the article reveals how publishers are attempting an ontological shift to position the individual, quantifiable researcher, rather than the published content, at the centre of the scholarly communication universe.

The implications of the shift towards individuation are revealed as part of a broader trend in scholarly communication infrastructure towards data extraction, mirroring a trend within digital capitalism more generally.

This article aims to discuss how the emergence of advanced semantic web technology has transformed the conventional web into machine processable and understandable form.

In this paper the authors survey the current research works, tools and applications on publishing legacy data as linked data with the aspiration of conferring healthier understanding of the working domain of the linked data world.

Today, a vast amount of data are stored in various file formats other than RDF, which are called legacy data. In order to publish them as linked data they need to be extracted and converted into RDF or linked data without altering the original data schema or loss of information.

Most of the key issues have to be addressed. A more sophisticated approach to this technology is the linked data, which constructs the transformation of web of documents into the web of connected data possible.

The focus of this chapter is the intersection of social media, publication, data sharing, and research ethics. By now there is an extensive literature on the use of social media in research. There is also excellent work on challenges of postpublication sharing of social media, primarily focused on legal restrictions, technical infrastructure, and documentation. This chapter attempts to build upon and extend this work by using cases to deepen the analysis of ethical issues arising from publishing and sharing social media data. Publishing will refer to the presentation of data extracts, aggregations, or summaries, while sharing refers to the practice of making the underlying data available postpublication for others to use. It will look at the ethical questions that arise both for researchers (or others) sharing data, and those who are using data that has been made available by others, emphasizing the inherently relational nature of data sharing. The ethical challenges researchers face when considering sharing user-generated content collected from social media platforms are the focus of the cases. The chapter begins by summarizing the general principles of research ethics, then identifies the specific ethical challenges from sharing social media data and positions these challenges in the context of these general principles. These challenges are then analyzed in more detail with cases from research projects that drew upon several different genres of social media. The chapter concludes with some recommendations for practical guidance and considers the future of ethical practice in sharing social media data.

This chapter outlines libraries’ (and librarians’) changing identities in the new world of research mandates from funders, institutions, and publishers. As libraries respond to the demands of these mandates on their users at the individual, departmental, and institutional levels, they need to revise their approaches to relationship building and user engagement, as well as maintain flexibility in the face of changing roles and skill requirements. This chapter will (1) outline the changing scholarly ecosystem; (2) summarize major terms and concepts to understand the process of producing research outputs; (3) discuss the perspectives of the major players in the research enterprise; (4) present some of the challenges that research mandates and the changing research environment have brought to libraries; and finally (5) review ways in which libraries have successfully addressed them. The focus here is on the academic research setting, although many of the strategies outlined can be equally applicable in both non-academic research and non-research funding contexts.

Linked data is a technical standard to structure complex information and relate independent sets of data. Recently, governments have started to use this technology for bridging separated data “(silos)” by launching linked open government data (LOGD) portals. The purpose of this paper is to explore the role of LOGD as a smart technology and strategy to create public value. This is achieved by enhancing the usability and visibility of open data provided by public organizations.

In this study, three different LOGD governance modes are deduced: public agencies could release linked data via a dedicated triple store, via a shared triple store or via an open knowledge base. Each of these modes has different effects on usability and visibility of open data. Selected case studies illustrate the actual use of these three governance modes.

According to this study, LOGD governance modes present a trade-off between retaining control over governmental data and potentially gaining public value by the increased use of open data by citizens.

This study provides recommendations for public sector organizations for the development of their data publishing strategy to balance control, usability and visibility considering also the growing popularity of open knowledge bases such as Wikidata.

The purpose of this paper is to provide a comprehensive cross-national comparative framework to compare open data policies from different countries and to derive lessons for developing open data policies. Open data policies guide the opening and stimulate the usage of public data. However, some countries have no or less developed open data policies, in this way missing the opportunity to reap the benefits of open data.

Literature review and case studies were conducted to extend an existing comparison framework, and the framework was used to compare open data policies of the UK, the USA, The Netherlands, Kenya and Indonesia.

The comparison of open data policies highlighted several lessons that can be learned, including actions regarding a robust legal framework, generic operational policies, data providers and data users, data quality, designated agencies or taskforces and initiatives and incentives for stimulating demand for data. National policies should also be focused on removing barriers on the operational level and policies for stimulating the release and use of data.

There is hardly any research systematically comparing open data policies. The comparative framework provided in this paper is a first analytical basis for cross-national comparison of open data policies and offers possibilities for systematic cross-national lesson-drawing.

The authors found two waves of policy-making. The first wave of policy is focused on stimulating the release of data, whereas the second wave of policy is aimed at stimulating use. The comparison can be used to learn from other policies and help to improve open data policies. A third wave of open data policy is expected to materialize focusing on realizing added value from utilizing open data.

Improving a country’s open data policy can help the country to reap the benefits of open data, such as government transparency, efficiency and economic growth.

Open data are a recent phenomenon and countries are looking for ways to obtain the benefits. This research can be used for developing and evaluating open data policies.