Date: 24th October 2021
Time: 13:00 - 17:00 CEST, find the time in your own time zone
Note: Papers will be public and available at the PUBLISSO Fachrepositorium DaMaLOS 2021 collection closed to the workshop date
|13:00 - 13:10||Welcome and introduction||Organizers|
|13:10 - 14:10||Keynote speaker: Bianca Kramer (+ Q&A)||Open metadata - where do we stand?|
|14:10 - 14:20||Short break and discussion topics (proposing a discussion topic)|
|First session: Applications and practical cases - Chair TBA|
|14:20 - 14:40||The Survey Ontology: Packaging Survey Research as Research Objects (DOI:10.4126/FRL01-006429412) |
Surveys are a common and well explored method to collect information from people. Still, the sharing and reuse of survey data present several challenges for survey researchers that need to be supported in packaging and harmonising different resources describing a survey study. In this paper, we present the survey ontology that we designed to empower our CONEY toolkit for conversational surveys. Leveraging on Semantic Web technologies we aimed at building a solution to semantically annotate questions and answers at design time, and to easily elaborate and inter-link the collected data at analysis time. The survey ontology embraces the research object principles, and defines an open vocabulary to represent, annotate, and share a representation of the questionnaire structure and the gathered responses of a survey. We complement the discussion describing a complete survey research study carried out with CONEY and openly published as a research object.
|14:40 - 15:00||Environmental Observations in Knowledge Graphs (DOI:10.4126/FRL01-006429414) |
The notion of Linked Open Science rests on the assumption that Linked Data principles contribute to science and scientific data management in several distinct ways (e.g., by adding rich semantics to improve retrieval and reuse of data). This begs the question of the right level of granularity for such semantic enrichment. On the one extreme of the spectrum, one may provide semantic annotations on the level of entire datasets to improve retrieval while leaving the actual data untouched. On the other end, one may semantically describe every single datum, such as a particular observation leading to data that supports reasoning, automated conflation, and so on, while, at the same time, dramatically increasing the size of data, including redundancy. This paper reports on our experience in modeling heterogeneous environmental data using a semantically-enabled observation framework, namely the SOSA ontology and its extensions to handle observation collections. We discuss different means of using these observation collections and compare their pros and cons in terms of data size and ease of querying.
|15:00 - 15:20||Analysis of Scientific Literature of LDOW Workshops: A Scientometric and NLP approach (DOI:10.4126/FRL01-006429416) |
This paper contributes to compiling and publishing a structured dataset from the scientific literature of the Linked Data on the Web (LDOW) workshop series. This workshop was the primary venue for publishing the frontier topics related to Semantic Web, Linked Open Data, and Web of Data for around ten years. Further, we analyze this dataset using a scientometric approach and n-gram analysis. We apply an n-gram analysis of all the presented titles and abstracts of the dataset to learn the evolving topics discourse. Our analysis reveals interesting patterns over the evolution of the concerning topics in the community of Linked Open Data. We publish this dataset online under GNU General Public License v3.0.
|15:20 - 15:40||Long break and discussion topics (adding questions to the discussion topic)||All|
|Second session: FAIR and DMP - Chair TBA|
|15:40 - 16:00||Automating Evaluation of Machine-Actionable Data Management Plans with Semantic Web Technologies (DOI:10.4126/FRL01-006429413) |
Machine-actionable data management plans (maDMPs) have, by their very nature, potential to bring advantages over data management plans that are written in text form. By employing maDMPs, not only researchers should be able to benefit from their merits, but also research funders receiving and assessing the DMPs. Science Europe, which is an association of major European research funders, have published an evaluation rubric that provides a common basis to support evaluation of DMPs. By stating a set of criteria, it helps to ensure submitted DMPs cover required aspects and support FAIR data management. In this paper, we present a semi-automatic approach to leverage the benefits of maDMPs by providing SPARQL queries that represent requirements of Science Europe. The goal is to support reviewers in the assessment of DMPs expressed as maDMPs. The results shows that semantic web technologies can help in providing customised views to reviewers, but human inspection and interpretation is still needed.
|16:00 - 16:20||Working Towards Understanding the Role of FAIR for Machine Learning (DOI:10.4126/FRL01-006429415) |
The FAIR Guiding Principles aim to improve findability, accessibility, interoperability and reusability for both humans and machines, initially aimed at scientific data, but also intended to apply to all sorts of research digital objects, with recent developments about their modification and application to software and computational workflows. In this position paper we argue that the FAIR principles also can apply to machine learning tools and models, though a direct application is not always possible as machine learning combines aspects of data and software. Here we discuss some of the elements of machine learning that lead to the need for some adaptation of the original FAIR principles, along with stakeholders that would benefit from this adaptation. We introduce the initial steps towards this adaptation, i.e., creating a community around it, some possible benefits beyond FAIR, and some of the open questions that such a community could tackle.
|16:20 - 16:30||Short break and discussion topics (adding questions to the discussion topic)||All|
|Third session: Discussion panel - Chair TBA|
|16:30 - 17:00||Panel/discussion topics and report||All|
|17:00 - 17:10||Wrap-up||Organizers|
Bianca Kramer is a scholarly communication librarian at Utrecht University Library, with a strong focus on open science and open infrastructure. Through her work on the project ‘101 innovations in scholarly communication’ she investigates trends in innovations and tool usage across the research cycle, with special attention to open scholarly infrastructure. She researches and leads workshops on various aspects of scholarly communication (e.g. preprints, peer review, altmetrics) for researchers, students and other stakeholders in scholarly communication, and has an active interest in open access developments and monitoring, as well as in developments around rewards and recognition. She is on the board of FORCE11 and was a member of the EC Expert Group on the Future of Scholarly Communication and Scholarly Publishing.
Please cite it as: Kramer, B. (2021). Open metadata - where do we stand? DaMaLOS 2021. ISWC-DaMaLOS Workshop, Online. https://dx.doi.org/10.4126/FRL01-006429411 (Note: Link will become public after the workshop)
Metadata form an important part of the research communication ecosystem - allowing discovery, linking and integration of data on research process and outputs, research evaluation and metaresearch. It can be argued that publications, data and other research objects can only be FAIR when their metadata are open, and while there are many organizations working on providing open metadata, a number of challenges remain.
These include licensing issues, the existence of siloed collections of metadata and the continued commercial enclosure of certain types of metadata. There is also growing awareness of the need for transparency, provenance and community governance in open metadata collection and provision. Finally, there are questions around the pros and cons of centralization vs. distributed systems, and the role of community curation vs. authoritative sources of metadata.
This presentation will discuss these aspects, highlight a number of current initiatives towards open metadata, and discuss where these can strengthen each other and which gaps and biases in the open metadata landscape remain to be addressed.