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TThere is a growing body of literature recognizing the benefits of Open Data. However, many potential data providers are unwilling to publish their data and at the same time, data users are often faced with difficulties when attempting to use Open Data in practice. Despite various barriers in using and publishing Open Data still being present, studies which systematically collect and assess these barriers are rare. Based on this observation we present a review on prior literature on barriers and the results of an empirical study aimed at assessing both the users' and publishers' views on obstacles regarding Open Data adoption. We collected data with an online survey in Austria and internationally. Using a sample of 183 participants, we draw conclusions about the relative importance of the barriers reported in the literature. In comparison to a previous conference paper presented at the conference for E-Democracy and Open Government, this article includes new additional data from participants outside Austria, reports new analyses, and substantially extends the discussion of results and of possible strategies for the mitigation of Open Data barriers.

There is a growing body of literature recognizing the benefits of Open Data. However, many potential data providers are unwilling to publish their data and at the same time, data users are often faced with difficulties when attempting to use Open Data in practice. Despite various barriers in using and publishing Open Data still being present, studies which systematically collect and assess these barriers are rare. Based on this observation we present a review on prior literature on barriers and the results of an empirical study aimed at assessing both the users' and publishers' views on obstacles regarding Open Data adoption. We collected data with an online survey in Austria and internationally. Using a sample of 183 participants, we draw conclusions about the relative importance of the barriers reported in the literature. In comparison to a previous conference paper presented at the conference for E-Democracy and Open Government, this article includes new additional data from participants outside Austria, reports new analyses, and substantially extends the discussion of results and of possible strategies for the mitigation of Open Data barriers.

TThere is a growing body of literature recognizing the benefits of Open Data. However, many potential data providers are unwilling to publish their data and at the same time, data users are often faced with difficulties when attempting to use Open Data in practice. Despite various barriers in using and publishing Open Data still being present, studies which systematically collect and assess these barriers are rare. Based on this observation we present a review on prior literature on barriers and the results of an empirical study aimed at assessing both the users' and publishers' views on obstacles regarding Open Data adoption. We collected data with an online survey in Austria and internationally. Using a sample of 183 participants, we draw conclusions about the relative importance of the barriers reported in the literature. In comparison to a previous conference paper presented at the conference for E-Democracy and Open Government, this article includes new additional data from participants outside Austria, reports new analyses, and substantially extends the discussion of results and of possible strategies for the mitigation of Open Data barriers.

One of the grand challenges discussed during the Dagstuhl Seminar "Knowledge Graphs: New Directions for Knowledge Representation on the Semantic Web" and described in its report is that of a: "Public FAIR Knowledge Graph of Everything: We increasingly see the creation of knowledge graphs that capture information about the entirety of a class of entities. [.] This grand challenge extends this further by asking if we can create a knowledge graph of "everything" ranging from common sense concepts to location based entities. This knowledge graph should be "open to the public" in a FAIR manner democratizing this mass amount of knowledge." Although linked open data (LOD) is one knowledge graph, it is the closest realisation (and probably the only one) to a public FAIR Knowledge Graph (KG) of everything. Surely, LOD provides a unique testbed for experimenting and evaluating research hypotheses on open and FAIR KG. One of the most neglected FAIR issues about KGs is their ongoing evolution and long term preservation. We want to investigate this problem, that is to understand what preserving and supporting the evolution of KGs means and how these problems can be addressed. Clearly, the problem can be approached from different perspectives and may require the development of different approaches, including new theories, ontologies, metrics, strategies, procedures, etc. This document reports a collaborative effort performed by 9 teams of students, each guided by a senior researcher as their mentor, attending the International Semantic Web Research School (ISWS 2019). Each team provides a different perspective to the problem of knowledge graph evolution substantiated by a set of research questions as the main subject of their investigation. In addition, they provide their working definition for KG preservation and ...