Towards FAIR principles for research software

The FAIR Guiding Principles, published in 2016, aim to improve the findability, accessibility, interoperability and reusability of digital research objects for both humans and machines. Until now the FAIR principles have been mostly applied to research data. The ideas behind these principles are, however, also directly relevant to research software. Hence there is a distinct need to explore how the FAIR principles can be applied to software. In this work, we aim to summarize the current status of the debate around FAIR and software, as basis for the development of community-agreed principles for FAIR research software in the future. We discuss what makes software different from data with regard to the application of the FAIR principles, and which desired characteristics of research software go beyond FAIR. Then we present an analysis of where the existing principles can directly be applied to software, where they need to be adapted or reinterpreted, and where the definition of additional principles is required. Here interoperability has proven to be the most challenging principle, calling for particular attention in future discussions. Finally, we outline next steps on the way towards definite FAIR principles for research software

Incentivizing the Dynamic Workforce: Learning Contracts in the Gig-Economy

In principal-agent models, a principal offers a contract to an agent to perform a certain task. The agent exerts a level of effort that maximizes her utility. The principal is oblivious to the agent's chosen level of effort, and conditions her wage only on possible outcomes. In this work, we consider a model in which the principal is unaware of the agent's utility and action space. She sequentially offers contracts to identical agents, and observes the resulting outcomes. We present an algorithm for learning the optimal contract under mild assumptions. We bound the number of samples needed for the principal obtain a contract that is within $\epsilon$ of her optimal net profit for every $\epsilon>0$

A FAIRification roadmap for ELIXIR Software Management Plans

Academic research requires careful handling of data plus any means to collect, transform and publish it, activities commonly supported by research software (from scripts to end-user applications). Data Management Plans (DMPs) are nowadays commonly requested by funders as part of good research practices. A DMP describes the data management lifecycle for the data corresponding to a research project, covering activities from collection to publication and preservation. To support and improve transparency, open science, reproducibility (and other *ilities), data needs to be accompanied by the software transforming it. Similar to DMPs, Software Management Plans (SMPs) can help formalize a set of structures and goals ensuring that the software is accessible and reusable in the short, medium and long term. DMPs and SMPs can be presented as text-based documents, guided by a set of questions corresponding to key points related to the lifecycle of either data or software.A step forward for DMPs are the machine-actionable DMPs (maDMPs) proposed by the Research Data Alliance DMP Common Standards Working Group. A maDMP corresponds to a structured representation of the most common elements present in a DMP (Miksa et al. 2020b), overcoming some obstacles linked to text-based representation. Such a structured representation makes it easier for DMPs to become readable and reusable for both humans and machines alike. The DMP Common Standard ontology (DCSO) (Cardoso et al. 2022) further supports maDMPs as it makes it easier to extend the original maDMP application profile to cover additional elements related to, for instance, SMPs or specific requirements from funders. maDMPs can be combined with the notion of a Research Object Crates (RO-Crate) to automate and ease management of research data (Miksa et al. 2020a). An RO-Crate (Soiland-Reyes et al. 2022) is an open, community-driven, and lightweight approach based on schema.org (Guha et al. 2016) annotations in JSON-LD to package research data (or any other research digital object) together with its metadata in a machine-readable manner.The ELIXIR SMP has been developed by the ELIXIR Software Development Best Practices Group in the ELIXIR Tools Platform to support researchers in life sciences (Alves et al. 2021). The ELIXIR SMP aims at making it easier to follow research software good practices aligned to the findable, accessible, interoperable and reusable principles for research software (FAIR4RS) (Chue Hong et al. 2022) while dealing with the lifecycle of research software. Its primary goal is encouraging a wider adoption by life science researchers, and being as inclusive as possible to the various levels of technical expertise. Here we present a roadmap for ELIXIR SMPs to become a FAIR digital object (FDO) (Schultes and Wittenburg 2019) based on the extension of maDMPs and DCSO and the use of RO-Crates. FDOs have been proposed as a way to package digital objects together with their metadata, types, identifiers and operations, so they become more machine-actionable and auto-contained.The current version of the ELIXIR SMP includes seven sections: accessibility and licensing, documentation, testing, interoperability, versioning, reproducibility, and recognition. Each section includes questions guiding and supporting researchers so they cover key aspects of the software lifecycle relevant to their own case. To lower the barrier and make it easier for researchers, most questions are Yes/No with some few offering a set of options. In some cases, a URL is also requested, for instance regarding the location of the documentation for end-users. Our roadmap for ELIXIR SMPs to move from a text-based questionnaire to an FDO comprises four main steps:creating maSMP application profile,extending DCSO,mapping to schema.org, andusing RO-Crates.Our maSMP application profile will include the semantic representation of the structured metadata that comes from the ELIXIR SMP. We will add granularity to the current root of the DCSO (dcso:DMP), by proposing the term SMP. In addition, we will propose the term ResearchSoftware as a dcso:Dataset. Terminology related to documentation, such as “Objective'' will also be considered. The objective is the Why the research software, which is crucial for their comprehensibility. We will propose the term DatasetObjective as the reason for the creation of a dataset. Source-codeRepository and Source-codeTesting are also good candidates to be part of the DCSO extension.We will extend DCSO with new classes and properties as necessary to include the software related elements mentioned in the maSMP application profile. As the ELIXIR SMP targets the life science community, we will analyze the need to add links from DCSO to ontologies describing common operations, activities, and types in this domain. One important aspect is the creation of a mapping from DCSO to schema.org. Schema.org has become a popular choice to add lightway semantics to web pages but can also be used on its own to provide metadata describing all sorts of objects. In life sciences, Bioschemas (Gray et al. 2017) offers guidelines on how to use some of the schema.org types aligned to this domain. Bioschemas includes a set of profiles, including minimum, recommended and optional properties, that have been agreed to and adopted by the community, for instance the ComputationalTool profile provides a way to describe software tools and applications. Bioschemas promotes its adoption by key resources in Life Sciences and development of tools such as the Bioschemas Markup Scraper and Extractor (BMUSE) used for the harvesting of the data (Gray et al. 2022).Our final step for ELIXIR SMPs to become an FDO is using RO-Crates to package research software together with its metadata and link it to/from its corresponding SMP. To do so, we will create an RO-Crate profile capturing the metadata needed to describe software tools including elements from the SMP. It will become a versioned living crate as research software evolves with time, particularly when new releases are published. Thanks to the RO-Crate bundling nature, where digital objects are packed together with its metadata, a software crate enriched with the elements from the SMP are a good example of an FDO as all the critical information about a software tool is bound together in a unit that can be shared with peers via FAIR registries and repositories

A metadata analysis for machine-actionable Software Mng Plans - Poster

Data Management Plans (DMPs) describe the data management lifecycle for the data corresponding to a research project, including activities from collection to preservation Machine-actionable DMPs improve text-based DMPs by adding a semantic layer representing the most common elements relevant to DMPs, from datasets to funders. Similar to DMPs, Software Management Plans (SMPs) follow the software management lifecycle. The ELIXIR SMP was developed to support life science researchers and make it easier to follow research software good practices aligned to the findable, accessible, interoperable and reusable principles for research software. Currently, the ELIXIR SMP is a questionnaire-based document that would benefit from a machine-actionable approach. Here, we present a preliminary metadata analysis including possible types and properties from Schema.org that could be used to model machine-actionable SMPs

A metadata schema for machine-actionable Software Management Plans

Data-driven research requires handling data together with the software that is used to collect, transform, and create such data. Data Management Plans have emerged as a systematic way to record the data management lifecycle for data corresponding to a research project. Similar to DMPs, Software Management Plans (SMPs) follow the research software management lifecycle, becoming a complement of DMPs. Initially, both DMPs and SMPs were conceived as text-based documents, sometimes guided by a set of questions targeting key points related to the corresponding lifecycle. Machine-actionable DMPs improve text-based DMPs by adding a semantic layer representing the most common elements relevant to DMPs, from datasets to funders. Here, we use the ELIXIR SMP as a use-case and present a preliminary metadata schema including possible types and properties useful to represent machine-actionable SMPs

Trends in Outcomes for Neonates Born Very Preterm and Very Low Birth Weight in 11 High-Income Countries

OBJECTIVE: To evaluate outcome trends of neonates born very preterm in 11 high-income countries participating in the International Network for Evaluating Outcomes of neonates. STUDY DESIGN: In a retrospective cohort study, we included 154 233 neonates admitted to 529 neonatal units between January 1, 2007, and December 31, 2015, at 24(0/7) to 31(6/7) weeks of gestational age and birth weight <1500 g. Composite outcomes were in-hospital mortality or any of severe neurologic injury, treated retinopathy of prematurity, and bronchopulmonary dysplasia (BPD); and same composite outcome excluding BPD. Secondary outcomes were mortality and individual morbidities. For each country, annual outcome trends and adjusted relative risks comparing epoch 2 (2012-2015) to epoch 1 (2007-2011) were analyzed. RESULTS: For composite outcome including BPD, the trend decreased in Canada and Israel but increased in Australia and New Zealand, Japan, Spain, Sweden, and the United Kingdom. For composite outcome excluding BPD, the trend decreased in all countries except Spain, Sweden, Tuscany, and the United Kingdom. The risk of composite outcome was lower in epoch 2 than epoch 1 in Canada (adjusted relative risks 0.78; 95% CI 0.74-0.82) only. The risk of composite outcome excluding BPD was significantly lower in epoch 2 compared with epoch 1 in Australia and New Zealand, Canada, Finland, Japan, and Switzerland. Mortality rates reduced in most countries in epoch 2. BPD rates increased significantly in all countries except Canada, Israel, Finland, and Tuscany. CONCLUSIONS: In most countries, mortality decreased whereas BPD increased for neonates born very preterm

Search for CPCP violation in D0^0→\to KS0^0_\mathrm{S}KS0^0_\mathrm{S} decays in proton-proton collisions at s\sqrt{s} = 13 TeV

International audienceA search is reported for charge-parity D$^0$$\to$ K$^0_\mathrm{S}$K$^0_\mathrm{S}$$CP$ violation in D$^0$$\to$ K$^0_\mathrm{S}$K$^0_\mathrm{S}$ decays, using data collected in proton-proton collisions at $\sqrt{s}$ = 13 TeV recorded by the CMS experiment in 2018. The analysis uses a dedicated data set that corresponds to an integrated luminosity of 41.6 fb$^{-1}$, which consists of about 10 billion events containing a pair of ẖadrons, nearly all of which decay to charm hadrons. The flavor of the neutral D meson is determined by the pion charge in the reconstructed decays D$^{*+}$$\to$ D$^0\pi^+$ and D$^{*-}$$\to$ D$^0\pi^-$. The D$^0$$\to$ K$^0_\mathrm{S}$K$^0_\mathrm{S}$$CP$ asymmetry in D$^0$$\to$ K$^0_\mathrm{S}$K$^0_\mathrm{S}$ is measured to be $A_{CP}$( K$^0_\mathrm{S}$K$^0_\mathrm{S}$) = (6.2 $\pm$ 3.0 $\pm$ 0.2 $\pm$ 0.8)%, where the three uncertainties represent the statistical uncertainty, the systematic uncertainty, and the uncertainty in the measurement of the D$^0$ $\to$ K$^0_\mathrm{S}$K$^0_\mathrm{S}$ $CP$ asymmetry in the D$^0$ $\to$ K$^0_\mathrm{S}\pi^+\pi^-$ decay. This is the first D$^0$ $\to$ K$^0_\mathrm{S}$K$^0_\mathrm{S}$ $CP$ asymmetry measurement by CMS in the charm sector as well as the first to utilize a fully hadronic final state

Measurement of inclusive and differential cross sections for W+^{+}W−^{-} production in proton-proton collisions at s= \sqrt{s} = 13.6 TeV

Measurements at $\sqrt{s}=$ 13.6 TeV of the opposite-sign W boson pair production cross section in proton-proton collisions are presented. The data used in this study were collected with the CMS detector at the CERN LHC in 2022, and correspond to an integrated luminosity of 34.8 fb$^{-1}$. Events are selected by requiring one electron and one muon of opposite charge. A maximum likelihood fit is performed on signal- and background-enriched data categories defined by the flavour and charge of the leptons, the number of jets, and number of jets originating from b quarks. An inclusive W$^{+}$W$^{-}$ production cross section of 125.7 $\pm$ 5.6 pb is measured, in agreement with standard model predictions. Cross sections are also reported in a fiducial region close to that of the detector acceptance, both inclusively and differentially, as a function of the jet multiplicity in the event. For first time in proton-proton collisions, WW events with at least two reconstructed jets are studied and compared with recent theoretical predictions.Measurements at $\sqrt{s}$ = 13.6 TeV of the opposite-sign W boson pair production cross section in proton-proton collisions are presented. The data used in this study were collected with the CMS detector at the CERN LHC in 2022, and correspond to an integrated luminosity of 34.8 fb$^{-1}$. Events are selected by requiring one electron and one muon of opposite charge. A maximum likelihood fit is performed on signal- and background-enriched data categories defined by the flavour and charge of the leptons, the number of jets, and number of jets originating from b quarks. An inclusive W$^+$W$^-$ production cross section of 125.7 $\pm$ 5.6 pb is measured, in agreement with standard model predictions. Cross sections are also reported in a fiducial region close to that of the detector acceptance, both inclusively and differentially, as a function of the jet multiplicity in the event. For first time in proton-proton collisions, WW events with at least two reconstructed jets are studied and compared with recent theoretical predictions

Search for a resonance decaying to a W boson and a photon in proton-proton collisions at s= \sqrt{s} = 13 TeV using leptonic W boson decays

A search for a new charged particle X with mass between 0.3 and 2.0 TeV decaying to a W boson and a photon is presented, using proton-proton collision data at a center-of-mass energy of 13 TeV, collected by the CMS experiment and corresponding to an integrated luminosity of 138 fb$^{-1}$. Particle X has electric charge $\pm$1 and is assumed to have spin 0. The search is performed using the electron and muon decays of the W boson. No significant excess above the predicted background is observed. The upper limit at 95% confidence level on the product of the production cross section of the X and its branching fraction to a W boson and a photon is found to be 94 (137) fb for a 0.3 TeV resonance and 0.75 (0.81) fb for a 2.0 TeV resonance, for an X width-to-mass ratio of 0.01% (5%). This search presents the most stringent constraints to date on the existence of such resonances across the probed mass range. A statistical combination with an earlier study based on the hadronic decay mode of the W boson is also performed, and the upper limit at 95% confidence level for a 2.0 TeV resonance is reduced to 0.50 (0.63) fb for an X width-to-mass ratio of 0.01% (5%).A search for a new charged particle X with mass between 0.3 and 2.0 TeV decaying to a W boson and a photon is presented, using proton-proton collision data at a center-of-mass energy of 13 TeV, collected by the CMS experiment and corresponding to an integrated luminosity of 138 fb$^{-1}$. Particle X has electric charge $\pm$1 and is assumed to have spin 0. The search is performed using the electron and muon decays of the W boson. No significant excess above the predicted background is observed. The upper limit at 95% confidence level on the product of the production cross section of the X and its branching fraction to a W boson and a photon is found to be 94 (137) fb for a 0.3 TeV resonance and 0.75 (0.81) fb for a 2.0 TeV resonance, for an X width-to-mass ratio of 0.01% (5%). This search presents the most stringent constraints to date on the existence of such resonances across the probed mass range. A statistical combination with an earlier study based on the hadronic decay mode of the W boson is also performed, and the upper limit at 95% confidence level for a 2.0 TeV resonance is reduced to 0.50 (0.63) fb for an X width-to-mass ratio of 0.01% (5%)