Advancing discovery science with fair data stewardship:Findable, accessible, interoperable, reusable

This report summarizes a presentation by Dr. Michel Dumontier. It reviews innovative scientific research methods created by data science, and the need to develop infrastructure, methodologies, and user communities to advance data science. Stakeholders have proposed a set of principles to make digital resources findable, accessible, interoperable, and reusable—FAIR. FAIR principles provide guidelines, do not require specific technologies, and allow communities of stakeholders to define specific FAIR standards and develop metrics to quantify them. Libraries can be part of the new data ecosystemby providing education, data stewardship, and infrastructure

A Unified Nanopublication Model for Effective and User-Friendly Access to the Elements of Scientific Publishing

Scientific publishing is the means by which we communicate and share scientific knowledge, but this process currently often lacks transparency and machine-interpretable representations. Scientific articles are published in long coarse-grained text with complicated structures, and they are optimized for human readers and not for automated means of organization and access. Peer reviewing is the main method of quality assessment, but these peer reviews are nowadays rarely published and their own complicated structure and linking to the respective articles is not accessible. In order to address these problems and to better align scientific publishing with the principles of the Web and Linked Data, we propose here an approach to use nanopublications as a unifying model to represent in a semantic way the elements of publications, their assessments, as well as the involved processes, actors, and provenance in general. To evaluate our approach, we present a dataset of 627 nanopublications representing an interlinked network of the elements of articles (such as individual paragraphs) and their reviews (such as individual review comments). Focusing on the specific scenario of editors performing a meta-review, we introduce seven competency questions and show how they can be executed as SPARQL queries. We then present a prototype of a user interface for that scenario that shows different views on the set of review comments provided for a given manuscript, and we show in a user study that editors find the interface useful to answer their competency questions. In summary, we demonstrate that a unified and semantic publication model based on nanopublications can make scientific communication more effective and user-friendly

Semantičko objavljivanje te usporedba entiteta prve skupine između SPAR ontologija FaBiO-a i FRBR DL-a te bibliografskih ontologija FaBiO i BIBFRAME

Cilj. Semantičko objavljivanje koristi koncepte i alate semantičkog weba i nastalo je njegovim razvojem. Budući da se klasičan način publiciranja znanstvenih radova suočio s njihovim brzim porastom, bilo je potrebno osigurati metode njihove automatske organizacije. Cilj ovoga rada jest definirati značenje semantičkog objavljivanja znanstvenih radova te usporediti FaBiO i FRBR DL te FaBiO i BIBFRAME. Metodologija. Metodološki je pristup u ovom radu komparativno-analitički. Analizirana je bibliografska ontologija FaBiO metodom komparacije s FRBR DL-om te BIBFRAME-om. Rezultati. Korištenje tehnologija semantičkog weba omogućuje poboljšanje značenja objavljenog članka u časopisu, olakšavanje njegovog automatskog otkrivanja, po- vezivanje sa semantički povezanim člancima te pristupanje podacima unutar članka. Semantičke web tehnologije, kao npr. RDF, RDFS, OWL i SPARQL formalni su alati koji to omogućuju. FaBiO se temelji na FRBR entitetima. U radu je prikazano kako se može pojednostaviti FRBR prikaz uz pomoć bibliografske ontologije FaBiO. Prikazana je i usporedba FaBi-a te BIBFRAME-a. Vrijednost. Članci i znanstveni podaci trebaju biti strojno čitljivi te jednostavni za pronalaženje i pregledavanje. Rezultati pretraživanja bitni su za znanstvena istraživanja radi postavljanja hipoteze te interpretacije. Semantičko objavljivanje pospješuje veći broj prijava radova, veći broj čitatelja i veće čimbenike utjecaja. Mogućnost pronalaženja članaka srodne tematike te otkrivanja nepoznatih veza između radova koji nisu eksplicitno povezani citatima doprinosi boljim čimbenicima utjecaja

Computable species descriptions and nanopublications: applying ontology-based technologies to dung beetles (Coleoptera, Scarabaeinae)

Taxonomy has long struggled with analysing vast amounts of phenotypic data due to computational and accessibility challenges. Ontology-based technologies provide a framework for modelling semantic phenotypes that are understandable by computers and compliant with FAIR principles. In this paper, we explore the use of Phenoscript, an emerging language designed for creating semantic phenotypes, to produce computable species descriptions. Our case study centers on the application of this approach to dung beetles (Coleoptera, Scarabaeinae)

Using nanopublications as a distributed ledger of digital truth

With the increase in volume of research publications, it is very difficult for researchers to keep abreast of all work in their area. Additionally, the claims in classical publications are not machine-readable making it challenging to retrieve, integrate, and link prior work. Several semantic publishing approaches have been proposed to address these challenges, including Research Object, Executable Paper, Micropublications, and Nanopublications. Nanopublications are a granular way of publishing research-based claims, their associated provenance, and publication information (metadata of the nanopublication) in a machine-readable form. To date, over 10 million nanopublications have been published, covering a wide range of topics, predominantly in the life sciences. Nanopublications are immutable, decentralised/distributed, uniformly structured, granular level, and authentic. These features of nanopublications allow them to be used as a Distributed Ledger of Digital Truth. Such a ledger enables detecting conflicting claims and generating the timeline of discussion on a particular topic. However, the inability to identify all nanopublications related to a given topic prevent existing nanopublications forming a ledger. In this dissertation, we make the following contributions: (i) Identify quality issues regarding misuse of authorship properties and linkrot which impact on the quality of the digital ledger. We argue that the Nanopub community needs to be developed a set of guidelines for publishing nanopublications. (ii) Provide a framework for generating a timeline of discourse over a collection of nanopublications by retrieving and combining nanopublications on a particular topic to provide interoperability between them. (iii) Detect contradictory claims between nanopublications automatically highlighting the conflicts and provide explanations based on the provenance information in the nanopublications. Through these contributions, we show that nanopublications can form a distributed ledger of digital truth, providing key benefits such as citability, timelines of discourse, and conflict detection, to users of the ledger

Linked Research on the Decentralised Web

This thesis is about research communication in the context of the Web. I analyse literature which reveals how researchers are making use of Web technologies for knowledge dissemination, as well as how individuals are disempowered by the centralisation of certain systems, such as academic publishing platforms and social media. I share my findings on the feasibility of a decentralised and interoperable information space where researchers can control their identifiers whilst fulfilling the core functions of scientific communication: registration, awareness, certification, and archiving. The contemporary research communication paradigm operates under a diverse set of sociotechnical constraints, which influence how units of research information and personal data are created and exchanged. Economic forces and non-interoperable system designs mean that researcher identifiers and research contributions are largely shaped and controlled by third-party entities; participation requires the use of proprietary systems. From a technical standpoint, this thesis takes a deep look at semantic structure of research artifacts, and how they can be stored, linked and shared in a way that is controlled by individual researchers, or delegated to trusted parties. Further, I find that the ecosystem was lacking a technical Web standard able to fulfill the awareness function of research communication. Thus, I contribute a new communication protocol, Linked Data Notifications (published as a W3C Recommendation) which enables decentralised notifications on the Web, and provide implementations pertinent to the academic publishing use case. So far we have seen decentralised notifications applied in research dissemination or collaboration scenarios, as well as for archival activities and scientific experiments. Another core contribution of this work is a Web standards-based implementation of a clientside tool, dokieli, for decentralised article publishing, annotations and social interactions. dokieli can be used to fulfill the scholarly functions of registration, awareness, certification, and archiving, all in a decentralised manner, returning control of research contributions and discourse to individual researchers. The overarching conclusion of the thesis is that Web technologies can be used to create a fully functioning ecosystem for research communication. Using the framework of Web architecture, and loosely coupling the four functions, an accessible and inclusive ecosystem can be realised whereby users are able to use and switch between interoperable applications without interfering with existing data. Technical solutions alone do not suffice of course, so this thesis also takes into account the need for a change in the traditional mode of thinking amongst scholars, and presents the Linked Research initiative as an ongoing effort toward researcher autonomy in a social system, and universal access to human- and machine-readable information. Outcomes of this outreach work so far include an increase in the number of individuals self-hosting their research artifacts, workshops publishing accessible proceedings on the Web, in-the-wild experiments with open and public peer-review, and semantic graphs of contributions to conference proceedings and journals (the Linked Open Research Cloud). Some of the future challenges include: addressing the social implications of decentralised Web publishing, as well as the design of ethically grounded interoperable mechanisms; cultivating privacy aware information spaces; personal or community-controlled on-demand archiving services; and further design of decentralised applications that are aware of the core functions of scientific communication

Expressing high-level scientific claims with formal semantics

The use of semantic technologies is gaining significant traction in science communication with a wide array of applications in disciplines including the life sciences, computer science, and the social sciences. Languages like RDF, OWL, and other formalisms based on formal logic are applied to make scientific knowledge accessible not only to human readers but also to automated systems. These approaches have mostly focused on the structure of scientific publications themselves, on the used scientific methods and equipment, or on the structure of the used datasets. The core claims or hypotheses of scientific work have only been covered in a shallow manner, such as by linking mentioned entities to established identifiers. In this research, we therefore want to find out whether we can use existing semantic formalisms to fully express the content of high-level scientific claims using formal semantics in a systematic way. Analyzing the main claims from a sample of scientific articles from all disciplines, we find that their semantics are more complex than what a straight-forward application of formalisms like RDF or OWL account for, but we managed to elicit a clear semantic pattern which we call the "super-pattern''. We show here how the instantiation of the five slots of this super-pattern leads to a strictly defined statement in higher-order logic. We successfully applied this super-pattern to an enlarged sample of scientific claims. We show that knowledge representation experts, when instructed to independently instantiate the super-pattern with given scientific claims, show a high degree of consistency and convergence given the complexity of the task and the subject. These results therefore open the door on the longer run for allowing researchers to express their high-level scientific findings in a manner they can be automatically interpreted. This in turn will allow for automated consistency checking, question answering, aggregation, and much more

Data Driven Understanding of Energy-Meteorological Variability and its Impact on Energy System Operations

Earth’s climate is changing. For a habitable planet in the future the emission of greenhouse gasses needs to be stopped. As future societies still require energy for their basic needs, a transition away from fossil fuel to renewable energy sources is needed. Nothing is as variable as the weather, and weather is the driving force of renewable energy resources. The interaction of societal and weather driven variability, here coined the energy-meteorological variability, is still largely unchartered. This variability is the central theme of this thesis. The different backgrounds and expertise of those working at the intersection of the energy and climate domain mean that the current methods to assess this variability in energy system operations are inadequate. A data driven approach is needed to incorporate the energy-meteorological variability within assessments of (future) energy systems. In this thesis we investigate data driven methods and metrics to quantify and identify a deviation of the expected patterns. We need to overcome the disconnect between energy and climate scientists in order to integrate an understanding of variability in energy system operations. The applicability of approaches in operational energy system assessments is key. Intensive and sustainable collaborations between the different disciplines is needed to facilitate the energy transition, between the different domains of science as well as between science and industry

Crowdsourcing User-Centered Teams

Crowdsourcing has become an increasingly important tool for team formation and collaboration. This thesis investigates how User-Centered Design, an iterative process that prioritizes users and their needs, can be applied to improve the efficiency and effectiveness of crowdsourcing systems for teamwork and team formation. To achieve this, we conducted a series of studies to explore the role of various factors in shaping crowd workers' behaviour and preferences in collaborative contexts. The main findings of our research are as follows. In online team formation settings, crowd workers prefer disclosing overt traits (e.g., age, gender, topical interests) and avoid sharing sensitive information (e.g., ethnicity, depression). However, they are willing to share information regarding their personality and values, typically considered deep-level sensitive traits. Well-defined digital nudging interventions, such as a diversity progress bar, can promote diverse team formation. In contrast, subtler forms of nudging may inadvertently trigger biases working against the intended objectives. Ad-hoc crowd teams working under pressure can benefit from systems that account for differences in personality traits, as these can influence collaboration outcomes and perceptions. Designing crowdsourcing systems for emergency response requires modelling communication tools that aid, assist, and monitor the shared load, considering the strictly cooperative roles and task- and user-dependent communication styles between collaborators. When forming teams, crowd workers tend to balance attributes between and within groups, with a preference for Openness to Experience among the Big-5 personality traits. Based on these findings, we recommend applying a User-Centered approach to design collaborative crowdsourcing systems, considering user needs, behaviour, intents, and perceptions of digital environments. Future research should continue to explore and evaluate innovative strategies for promoting effective collaboration and team formation in crowdsourcing contexts