S Calvez

G Lafleur

C Arlotti

A Larrue

P.-F Calmon

A Arnoult

G Almuneau

O Gauthier-Lafaye

III-V-semiconductor vertically-coupled whispering-gallery mode resonators made by selective lateral oxidation

Keywords: resonator, disk, whispering gallery mode, integration, oxidation, AlOx, GaAs

Integrated whispering-gallery mode resonators are attractive devices which have found applications as selective filters, low-threshold lasers, high-speed modulators, high-sensitivity sensors and even as nonlinear converters. Their performance is governed by the level of detrimental (scattering, bulk, bending) loss incurred and the usable loss represented by the coupling rate between the resonator and its access waveguide. Practically, the latter parameter can be more accurately controlled when the resonator lies above the access waveguide, in other words, when the device uses a vertical integration scheme. So far, when using such an integration technique, the process involved a rather technically challenging step being either a planarization or a substrate transfer step.

In this presentation, we propose and demonstrate an alternative method to fabricate vertically-coupled whispering-gallery mode resonators on III-V semiconductor epitaxial structures which has the benefit of being planarization-free and performed as single-side top-down process. The approach relies on a selective lateral thermal oxidation of aluminum-rich AlGaAs layers to define the buried access waveguide and enhance the vertical confinement of the whispering-gallery mode into the resonator. As a first experimental proof-of-principle of this approach, 75 µm-diameter micro-disk devices exhibiting quality factor reaching ~4500 have been successfully made.

INTRODUCTION

Integrated whispering-gallery mode resonators are compact devices which can exhibit greatly enhanced intra-cavity fields at selected wavelengths, the exploitation of which makes them attractive for applications such as narrowbandwidth filters, low-threshold lasers, high-speed modulators, high-sensitivity sensors or low-power nonlinear converters [START_REF] Matsko | Optical resonators with whispering gallery modes I: basics[END_REF][START_REF] Feng | Silicon photonics: from a microresonator perspective[END_REF][START_REF] Ward | WGM microresonators: sensing, lasing and fundamental optics with microspheres[END_REF] . As indicated above, their usefulness is essentially governed by the ability to obtain high quality factors. To do so, it is necessary to simultaneously minimize the amount of detrimental (scattering, bulk, bending) loss in the resonator and obtain the "so-called" critical coupling condition where the latter loss level is equal to the coupling rate between the resonator and its access waveguide(s). Since the resonator in/out coupling is commonly done in the form of an evanescent coupling scheme, it is easier to meet the latter condition with the technological approach which offers the most tolerant and controllable process. It turns out to be when the resonator lies above the access waveguide or, in other words, when the device is made by vertical integration [START_REF] Wen Tee | Fabrication-tolerant active-passive integration scheme for vertically coupled microring resonator[END_REF][START_REF] Ghulinyan | Oscillatory Vertical Coupling between a Whispering-Gallery Resonator and a Bus Waveguide[END_REF] . To implement such geometry in practice, the fabrication of a buried (access) waveguide with a planar top surface is needed. This task happens to be technologically complex, typically requiring a demanding technological step such as a planarization step [START_REF] Suzuki | Integrated-optic ring resonators with two stacked layers of silica waveguide on Si[END_REF][START_REF] Ghulinyan | Monolithic Whispering-Gallery Mode Resonators With Vertically Coupled Integrated Bus Waveguides[END_REF] or a substrate transfer [START_REF] Absil | Vertically coupled microring resonators using polymer wafer bonding[END_REF] .

In this paper, following our recent demonstration [START_REF] Calvez | Vertically Coupled Microdisk Resonators Using AlGaAs/AlOx Technology[END_REF] , we present a technologically simpler method to fabricate verticallycoupled micro-disk resonators in III-V semiconductors based on the use of a selective lateral oxidation step to define the buried access waveguide.

DESIGN

A schematic representation of a vertically-coupled microdisk under study is shown in Figure 1. The layered vertical structure is composed of an air/GaAs/Al 0.3 Ga 0.7 As/Al 0.98 Ga 0.02 As/Al 0.3 Ga 0.7 As resonator waveguide on top of an AlOx confined buried access waveguide. The access waveguide stack is an asymmetric Al 0.3 Ga 0.7 As/GaAs/Al 0.6 Ga 0.4 As waveguide with an Al 0.98 Ga 0.02 As layer inserted in the Al 0.3 Ga 0.7 As upper cladding. The high-aluminum-containing layers will be selectively transformed into AlOx to form the waveguide aperture and enhance the vertical confinement of the resonator modes. The thickness of the GaAs cores (680nm for the resonator and 400nm for the access waveguide) were selected to obtain identical slab waveguide effective indexes. The chosen 330nm Al 0.3 Ga 0.7 As separation lead to the resonator supermode of the coupled slab waveguides to present a 1% (respectively 6.2%) intensity overlap with the core of the access waveguide slab when the Al 0.98 Ga 0.02 As layers are considered to be oxidized (respectively unoxidized).

The position (150 nm) and width of the AlOx aperture were chosen to achieve >3-µm-wide singlemode waveguides to facilitate cleaved-facet injection and to be compatible with the (~1-µm-)spatial resolution of oxidation furnace monitoring system [START_REF] Almuneau | Realtime in situ monitoring of wet thermal oxidation for precise confinement in VCSELs[END_REF] . Figure 2 shows the effective index contrast between the oxidized and unoxidized regions and the maximum width of the aperture for singlemode operation as a function of the separation between the oxide layer and the waveguide core. Please verify that (1) all pages are present, (2) all figures are correct, (3) all fonts and special characters are correct, and (4) all text and figures fit within the red margin lines shown on this review document. Complete formatting information is available at http://SPIE.org/manuscripts Return to the Manage Active Submissions page at http://spie.org/submissions/tasks.aspx and approve or disapprove this submission. Your manuscript will not be published without this approval. Please contact author_help@spie.org with any questions or concerns. For a separation of 150 nm, further waveguide calculations carried out using 2x1D effective index and a vectorial mode solver (WGModes) [START_REF] Fallahkhair | Vector Finite Difference Modesolver for Anisotropic Dielectric Waveguides[END_REF] show that the waveguide can be considered to remain singlemode up to a aperture width of ~3.7 µm. Neglecting the access slab waveguide, the evolution of the resonator mode effective index as a function the microdisk diameter was also evaluated using a cylindrical geometry and a vectorial finite-difference mode solver (WGMS3D) [START_REF] Krause | Finite-Difference Mode Solver for Curved Waveguides With Angled and Curved Dielectric Interfaces[END_REF] . Figure 4 shows, as expected, that the resonator effective index reduces as the diameter decreases. This variation also influences the coupling between the resonator and the access waveguide effective index (n access ~3.267) as the coupling beat length shrinks from 28.7 µm at a diameter of 400 µm down to 6.6 µm for a 50-µm-diameter microdisk. 4) all text and figures fit within the red margin lines shown on this review document. Complete formatting information is available at http://SPIE.org/manuscripts Return to the Manage Active Submissions page at http://spie.org/submissions/tasks.aspx and approve or disapprove this submission. Your manuscript will not be published without this approval. Please contact author_help@spie.org with any questions or concerns.

FABRICATION

The above-described layer structure was grown by molecular beam epitaxy on a standard (001) GaAs wafer. The devices were then fabricated using two lithographic and etching steps permitting the successive definition of the access guides and the resonators. As shown in Figure 5, the subsequent wet oxidation of both Al 0.98 Ga 0.02 As layers was performed at a rate of ~0.12 μm/min in a custom furnace under optical monitoring and stopped after an oxidation extent of ~14 µm leading to 3.7-µm-wide-apertured buried access waveguides. The wafer was then thinned down to ~150 µm, cleaved into samples which were subsequently mounted on custom Si-based sub-mounts. An image of a resulting microdisk is shown in Figure 6. Please verify that (1) all pages are present, (2) all figures are correct, (3) all fonts and special characters are correct, and (4) all text and figures fit within the red margin lines shown on this review document. Complete formatting information is available at http://SPIE.org/manuscripts Return to the Manage Active Submissions page at http://spie.org/submissions/tasks.aspx and approve or disapprove this submission. Your manuscript will not be published without this approval. Please contact author_help@spie.org with any questions or concerns.

CHARACTERISATION AND ANALYSIS

The mounted devices were characterized using the setup shown in Figure 7. The transmission characteristics were recorded using a step-tunable laser with central wavelength of 1.6 µm, a 10 pm spectral resolution and a 100 kHz linewidth. Figure 7 (right) shows the measured transmission characteristic of a 75-µm-diameter microdisk over one free spectral range. The intensity contrast (c=(I max -I min )/(Imax+Imin)) and loaded Q-factor (Q=λ/Δλ) are respectively measured to be 0.403 and 4450. To extract more meaningful parameters, namely the amplitude coupling coefficient (κ) and the intensity absorption coefficient (α), maps of the contrast and Q factors were calculated using the general equation [START_REF] Yariv | Universal relations for coupling of optical power between microresonators and dielectric waveguides[END_REF] :

T = ( ) ( ) ϕ ϕ cos 2 1 cos 2 2 2 2 2 coupler disk coupler disk coupler disk coupler disk t a t a t a t a - + - + (1)
where t coupler is the amplitude transmission coefficient of the coupling region (t coupler =(1-κ 2 ) 0.5 ) and a disk stands for the amplitude transmission coefficient (a disk =exp(-α π D/2)), and φ corresponds to the phase accumulated over one round-trip along the resonator periphery. Please verify that (1) all pages are present, (2) all figures are correct, (3) all fonts and special characters are correct, and (4) all text and figures fit within the red margin lines shown on this review document. Complete formatting information is available at http://SPIE.org/manuscripts Return to the Manage Active Submissions page at http://spie.org/submissions/tasks.aspx and approve or disapprove this submission. Your manuscript will not be published without this approval. Please contact author_help@spie.org with any questions or concerns. As it can be readily seen from equation ( 1) and inferred from Figure 8, two solutions (t coupler ,a disk )=(0.72,0.93) and (t coupler ,a disk )=(0.93,0.72) corresponding respectively to the over-coupled (low-loss) resonator (κ=0.69, α=6.2 cm -1 ) and under-coupled (high-loss) resonator (κ=0.37, α=27.8 cm -1 ) situations can provide a match to the above-mentioned characteristic values (Q=4450, c=0.403). The measurements carried out to-date do not allow the discrimination between these two situations although experimental techniques exist to alleviate this undetermination [START_REF] Lee | A General Characterizing Method for Ring Resonators Based on Low Coherence Measurement[END_REF][START_REF] Zhou | Characterisation of microring resonator optical delay and its dependence on coupling gap using modulation phase-shift technique[END_REF] . Nevertheless, similar analysis was performed on devices with greater diameters (up to 300 µm) and the summary of the performance is provided in Figure 9. With a view to understand the device performance limiting factors, the bending losses and substrate-leakage-like losses induced by the presence of the slab access waveguide were evaluated by vectorial finite-difference mode analysis. As shown in Figure 10, the substrate loss dominates with a value of 9.2 cm -1 (compounded with the bending loss) for a 75-µm-diameter microdisk rising to 15.0 cm -1 for 300µm-diameter disks. This also suggests that, in spite of a relatively thin separation layer, the devices are operating in under-coupling regime, possibly because of the unfavorable effective index mismatch between the resonator and the access waveguide. Please verify that (1) all pages are present, (2) all figures are correct, (3) all fonts and special characters are correct, and (4) all text and figures fit within the red margin lines shown on this review document. Complete formatting information is available at http://SPIE.org/manuscripts Return to the Manage Active Submissions page at http://spie.org/submissions/tasks.aspx and approve or disapprove this submission. Your manuscript will not be published without this approval. Please contact author_help@spie.org with any questions or concerns.

CONCLUSIONS

A novel method exploiting selective lateral oxidation has been established to fabricate vertically-coupled whisperinggalery-mode resonators on III-V semiconductors. The first fabrication run lead to 75-µm-diameter microdisks with Q factor reaching 4450 at a wavelength of ~1600 nm. The performance of the current set of devices was identified to be limited by the leakage to the slab access waveguide. Future work will focus on the modification of the structure to reach higher Q-factors.

Figure 1 .

 1 Figure 1. Device schematic (dark blue: GaAs -light blue Al 0.3 Ga 0.7 As -light purple Al 0.6 Ga 0.4 As -yellow: AlOx)

Figure 2 .

 2 Figure 2. Access waveguide cross-section diagram and key characteristics (at a wavelength of 1.55 µm).

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Figure 3 .

 3 Figure 3. Effective indexes and mode lateral widths at a wavelength of 1.55 µm for the first two TE-polarized modes that the oxide-apertured waveguide might support.

Figure 4 .

 4 Figure 4. Resonator mode effective index at a wavelength of 1.55 µm

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Figure 5 .

 5 Figure 5. Evolution of the lateral extent of the oxide (white part on the images) as monitored by infrared reflectometry. The width of the mesa is 32 µm.

Figure 6 .

 6 Figure 6. SEM picture of a 75-µm-diameter microdisk.

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Figure 7 .

 7 Figure 7. Characterization setup and typical close-to-resonance response of a 75µm-diameter microdisk.

Figure 8 .

 8 Figure 8. Calculated Q-factor (in log scale) and contrast maps for a 75-µm-diameter microdisk.

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Figure 9 .

 9 Figure 9. Calculated Q-factor and contrast maps for a 75-µm-diameter microdisk.

Figure 10 .

 10 Figure 10. Calculated Q-factor and contrast maps for a 75µm-diameter microdisk.

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ACKNOWLEDGEMENTS

Clément Arlotti would like to acknowledge the Délégation Générale de l'Armement and the Centre National d'Etudes Spatiales for supporting his PhD studentship. The work was also partly supported by the Centre National d'Etudes Spatiales research Grant R et T: R-S13-LN-0001-025 and the French Renatech Network of cleanroom facilities.


Alban Gaignard
email: alban.gaignard@univ-nantes.fr

Khalid Belhajjame

Hala Skaf-Molli

SHARP: Harmonizing cross-workflow provenance

Keywords: Reproducibility, Scientific Workflows, Provenance, Prov Constraints 8 SAMtools mpileup

PROV has been adopted by a number of workflow systems for encoding the traces of workflow executions. Exploiting these provenance traces is hampered by two main impediments. Firstly, workflow systems extend PROV differently to cater for system-specific constructs. The difference between the adopted PROV extensions yields heterogeneity in the generated provenance traces. This heterogeneity diminishes the value of such traces, e.g. when combining and querying provenance traces of different workflow systems. Secondly, the provenance recorded by workflow systems tends to be large, and as such difficult to browse and understand by a human user. In this paper, we propose SHARP, a Linked Data approach for harmonizing cross-workflow provenance. The harmonization is performed by chasing tuple-generating and equalitygenerating dependencies defined for workflow provenance. This results in a provenance graph that can be summarized using domain-specific vocabularies. We experimentally evaluate the effectiveness of SHARP using a real-world omic experiment involving workflow traces generated by the Taverna and Galaxy systems.

Introduction

Reproducibility has recently gained momentum in (computational) sciences as a means for promoting the understanding, transparency and ultimately the reuse of scientific experiments. This is particularly true in the life sciences where Next Generation Sequencing (NGS) equipments produce tremendous amounts of omics data, and lead to massive computational analysis (aligning, comparing, filtering, etc.). Life scientists urgently need for reproducibility and reuse to avoid duplication of storage and computing efforts.

Pivotal to reproducibility is provenance [START_REF] Davidson | Provenance and scientific workflows: challenges and opportunities[END_REF], which documents the experiment, including information about the activities that were conducted during the experiment, the agents that were involved, the resources and programs that were utilized as well as the data artifacts that were used and generated. Several researchers have investigated the use of provenance as a means for tracing pack the execution of experiment (see e.g., [START_REF] Zhao | Using semantic web technologies for representing e-science provenance[END_REF][START_REF] Miles | The requirements of using provenance in e-science experiments[END_REF][START_REF] Altintas | Provenance collection support in the kepler scientific workflow system[END_REF][START_REF] Alper | Enhancing and abstracting scientific workflow provenance for data publishing[END_REF]). We note however that experiments may involve multiple scientists, each of them is responsible for conducting and analyzing the execution of part of the overall experiment, using his/her favorite data analysis tool (workflow system, programming or scripting language, etc.), which may be different from those used by the rest of the team. This is particularly the case for interdisciplinary projects involving scientists with different backgrounds and expertise. In order to exploit the provenance generated by the different data analysis tools utilized within the scope of an experiment, there is therefore the need for harmonizing and interlinking the provenance traces such tool recorded and generated. The adoption of the W3C PROV recommendations [START_REF] Missier | The w3c prov family of specifications for modelling provenance metadata[END_REF] (in particular the PROV-O ontology [START_REF] Lebo | Prov-o: The prov ontology[END_REF] given increasing number of provenance-producing environments adopting semantic web technologies) by a number of data analysis tools has to a certain extent lessen the severity of the provenance harmonization problem. Yet, the fact that such environments use PROV extensions that extend PROV differently, means that there is a need for aligning the provenance traces generated by those tools. Moreover, the provenance graphs generated by those environments need to be interlinked by identifying the entities that refer to the same real world entity.

Interlinking and harmonizing provenance data is essential to deliver a global account of what happened during scientific experiments. It is, however, by no means sufficient for promoting the understanding and re-usability of the experiment and its associated results. Indeed, the provenance graph generated are often large and contain low level and cumbersome information that is targeted for the consumption of machines. This calls for abstraction mechanisms for providing a human user with a global view on what happens in the experiment, by deriving from the raw provenance information, high level and succinct information that helps users in understanding the experiment and the results of its execution in its entirety. In this paper, we propose SHARP that addresses the above issues. We propose the following contributions:

-An approach for interlinking and harmonizing provenance traces recorded by different workflow systems based on PROV inferences.

-An application of provenance harmonization towards Linked Experiment

Reports by using domain-specific annotations as in [START_REF] Gaignard | From scientific workflow patterns to 5-star linked open data[END_REF]. -An evaluation with real world omic use case illustrating the feasibility of SHARP.

The paper is organized as follows. Section 2 describes motivations and problem statement. Section 3 presents the harmonization of multiple PROV Graphs and its application towards Linked Experiment Reports. Section 4 reports our experimental results. Section 5 summarizes related works. Finally, conclusions and future works are outlined in Section 6.

Due to costly sequencing equipment and massively produced data, DNA sequencing is generally outsourced to third-party facilities. Therefore, part of the scientific experiment is conducted by the sequencing facility which requires dedicated high throughput computing infrastructures, and a second part is conducted by the scientists themselves to analyze and interpret the results of sequencing using traditional computing resources. Figure 2.1 illustrates a concrete example of such experiment, which is composed of two workflows enacted by different workflow systems, namely Galaxy [START_REF] Afgan | The galaxy platform for accessible, reproducible and collaborative biomedical analyses: 2016 update[END_REF] and Taverna [START_REF] Wolstencroft | The taverna workflow suite: designing and executing workflows of web services on the desktop, web or in the cloud[END_REF]. The first workflow (WF1), in blue in Figure 2.1, is implemented in Galaxy and addresses common DNA data pre-processing. Such workflow takes as input two DNA sequences from two biological samples s1 and s2, represented in green. For each sample, the sequence data is stored in forward 4 (.R1) and reverse (.R2) files. The first sample has been split by the sequencer in two parts, (.a) and (.b). The very first processing step consists in aligning (Alignment 5 ) short sequence reads onto a reference human genome (GRCh37). Then the two parts a and b are merged 6 into a single file. Then the aligned reads are sorted 7 prior to genetic variant identification 8 (Variant Calling). This primary analysis workflow finally produces a VCF 9 file which lists all known genetics variations compared to the GCRh37 reference genome.

Taverna workflow @research-lab

Galaxy workflow @sequencing-facility

Variant

The second workflow (WF2) is implemented with Taverna, and highly depends on scientific questions. It is generally conducted by life scientists possibly from different research labs and with less computational needs. Such workflow proceeds as follows. It first queries a database of known effects to associate a predicted effect 10 (Variant effect prediction). Then all these predictions are filtered to select only those applying to the exon parts of genes (Exon filtering). The results obtained by the executions of such workflows allow the scientists to have answers for questions such as Q1 : "From a set of gene mutations, which are common variants, and which are rare variants ?", Q2 : "Which alignment algorithm was used when predicting these effects ?", or Q3: "A new version of a reference genome is available, which genome was used when predicting these effects ?". While Q1 can be answered based on provenance tracking from WF1, Q2 and Q3 need for an overall tracking of provenance at the scale of both WF1 (Galaxy) and WF2 (Taverna) workflows.

While the two workflow environments used in the above experiments (Taverna and Galaxy) track provenance information conforming to the same W3C standardized PROV vocabulary, there are unfortunately impediments that hinder their exploitation. i)-The heterogeneity of the provenance languages used to encode workflow runs, despite the fact that they extend the same vocabulary PROV, does not allow the user to issue queries that use and combine traces recorded by different workflow languages. ii)-Heterogeneity aside, the provenance traces of workflow runs tend to be large, and thus cannot be utilized as they are to document the results of the experiment execution. We show how the above issues can be addressed by, i) applying graph saturation techniques and PROV inferences to overcome vocabulary heterogeneity, and ii) summarizing harmonized provenance graphs for life-science experiment reporting purposes.

Harmonizing multiple PROV Graphs

Faced with the heterogeneity in the provenance vocabularies, we can use classical data integration approaches such as peer-to-peer data integration or mediatorbased data integration [START_REF] Doan | Principles of Data Integration[END_REF] Both options are expensive since they require the specification of schema mappings that often require heavy human inputs. In this paper, we explore a third and cheaper approach that exploits the fact that many of the provenance vocabularies used by workflow systems extend the W3C PROV-O ontology. This means that such vocabularies already come with (implicit) mappings between the concepts and relationships they used and those of the W3C PROV-O. Of course, not all the concepts and relationships used by individual mappings will be catered for in PROV. Still this solution remains attractive because it does not require any human inputs, since the constraints (mappings) are readily available. We show in this section how the provenance traces that are encoded using different PROV extensions can be harmonized by capitalizing on such constraints.

Tuple-Generating Dependencies

Central to our approach to harmonizing provenance traces is the saturation operation. Given a possibly disconnected provenance RDF graph G, the saturation process generates a saturated graph G 8 obtained by repeatedly applying some rules to G until no new triple can be inferred. We distinguish between two kinds of rules. OWL entailment rules includes, among other things, rules for deriving new RDF statements through the transitivity of class and property relationships. Prov constraints [START_REF] Cheney | Constraints of the provenance data model[END_REF], these are of interest to us as they encode inferences and constraints that need to be satisfied by provenance traces, and can as a such be used for deriving new RDF provenance triples.

In this section, we examine such constraints by identifying those that are of interest when harmonizing the provenance traces of workflow executions, and show (when deemed useful) how they can be translated into SPARQL queries for saturation purposes. It is worth noting that the W3C Provenance constraint document presents the inferences and constraints assuming a relational-like model with possibly relations of arity greater than 2. We adapt these rules to the context of RDF where properties (relations) are binary. For space limitations, we do not show all the inferences rules that can be implemented in SPARQL, we focus instead on representative ones. We identify three categories of rules with respect to expressiveness (i) rules that contain only universal variables, (ii) rules that contain existential variables, (iii) rules making use of n-array relations (with n ě 3). The latter is interesting, since RDF reification is needed to represent such relations. For exemplary rule, we present the rules using tuple-generating dependencies TGDs [START_REF] Abiteboul | Foundations of Databases[END_REF], and then show how we encode it in SPARQL. A TGD is a first order logic formula @ xy φpx, ȳq Ñ Dz ψpȳ, zq, where φpx, ȳq and ψpȳ, zq) are conjunctions of atomic formulas.

Transitivity of alternateOf. Alternate-Of is a binary relation that associates two entities e 1 and e 2 to specify that the two entities present aspects of the same thing. The following rule states that such a relation is transitive, and it can be encoded using a SPARQL construct query, in a straightforward manner. alternateOfpe1, e2q, alternateOfpe2, e3q Ñ alternateOfpe1, e3q.

Inference of Usage and Generation from Derivation

The following rule states that if an entity e 2 was derived from an entity e 1 , then there exists an activity a, such that a used e 1 and generated e 2 .

wasDerivedFrompe2, e1q Ñ D a usedpa, e1q, wasGeneratedFrompe2, aq.

Notice that unlike the previous rule, the head of the above rule contains an existential variable, namely the activity a. To encode such a rule in SPARQL, we make use of blank nodes 11 for existential variables as illustrated below.

CONSTRUCT { ?e_2 prov:wasGeneratedBy _:blank_node . _:blank_node prov:used ?e_1 } WHERE { ?e_2 prov:wasDerivedFrom ?e_1 } Inference of Usage and Generation from Derivation Using the Qualification patterns In the previous rule, derivation, usage and generation are represented using binary relationships, which do not pose any problem to be encoded in RDF. Note, however, that PROV-DM allows such relationships to be augmented with optional attributes, for example, usage can be associated with a timestamp specifying the time at which the activity used the entity. The presence of extra optional attributes increases the arity of the relations that can no longer be represented using an RDF property. As a solution, the PROV-O opts for qualification patterns 12 introduced in [START_REF] Dodds | Linked Data Patterns: A pattern catalogue for modelling, publishing, and consuming Linked Data[END_REF]. To illustrate this, Figure 3.1 shows how a qualified usage can be encoded in RDF. The following rule shows how the inference of usage and generation from derivation can be expressed when such relationships are qualified. It can also be encoded using a SPARQL Construct query with blank nodes. qualifiedDerivationpe 2 , dq, provEntitypd, e 1 q Ñ D a, u, g qualifiedUsagepa, uq, provEntitypu, e 1 q, qualifiedGenerationpe 2 , gq, provActivitypg, aq.

Equality-Generating Dependencies

As well as the tuple-generating dependencies, we need to consider equalitygenerating dependencies (EGDs), which are induced by uniqueness constraints.

An EGD is a first order formula: @xφpxq Ñ px 1 " x 2 q, where φpxq is a conjunction of atomic formulas, and x 1 and x 2 are among the variables in x. We give below an example of an EGD, that is implied by the uniqueness of the generation that associates a given activity a with a given entity e.

wasGeneratedBypgen 1 , e, a, attrs 1 q, wasGeneratedBypgen 2 , e, a, attrs 2 q Ñ pgen 1 " gen 2 q

Having defined an example EGD, we need to specify what it means to apply it (or chase it [START_REF] Fagin | Data exchange: semantics and query answering[END_REF]) when we are dealing with RDF data. The application of an EGD has three possible outcomes. To illustrate them, we will work on the above example EGD. Typically, the generations gen 1 and gen 2 will be represented by two RDF resources. We distinguish the following cases:

(i) gen 1 is a non blank RDF resource and gen 2 is a blank node. In this case, we add to gen 1 the properties that are associated with the blank node gen 2 , and remove gen 2 . (ii) gen 1 and gen 2 are two blank nodes. In this case, we create a single blank node gen to which we associate the properties obtained by unionizing the properties of gen 1 and gen 2 , and we remove the two initial blank nodes. (iii) gen 1 and gen 2 are non blank nodes that are different. In this case, the application of the EGD (as well as the whole saturation) fails. In general, we would not have this case, if the initial workflows runs that we use as input are valid (ie., they respect the constraints defined in the W3C Prov Constraint recommendation [START_REF] Cheney | Constraints of the provenance data model[END_REF].

To select the candidate substitutions (line 5 of Algorithm 1), we express the graph patterns illustrated in the previous cases 1 and 2 as a SPARQL query. This query retrieves candidate substitutions as blank nodes coupled to their substitute, i.e., another blank node or a URI.

For each of the found substitution (line 6), we merge the incoming and outgoing relations between the source node and the target node. This operation is done in two steps. First, we navigate through the incoming relations of the source node (line 9), we copy them as incoming relations of the target node (line 10), and finally remove them from the source node (line 11). Second, we repeat Algorithm 1: EGD pseudo-code for merging blank nodes produced by PROV inference rules with existential variables.

Input : G 1 : the provenance graph resulting from the application of TGD on G Output: G 2 : the provenance graph with substituted blank nodes, when possible. this operation for the outgoing relations (lines 12 to 14). We repeat this process until we can't find any candidate substitutions.

1 begin 2 G 2 Ð G 1 3 substitutions Ð new

Full provenance harmonization process

Multi-provenance linking. This process starts by first linking the traces of the different workflow runs. Typically, the outputs produced by a run of a given workflow are used to feed the execution of a run of another workflow as depicted in Figure 2.1.

The main idea consists in providing an owl:sameAs property between the PROV entities associated with the same physical files. The production of owl:sameAs can be automated as follows : i) generate a fingerprint of the files (SHA-512 is one of the recommended hashing functions), ii) produce the PROV annotation associated the fingerprint to the PROV entities, iii) generate, through a SPARQL CONSTRUCT query, the owl:sameAs relationships when fingerprints are matched. When applied to our motivating example (Figure 2.1), the PROV entity annotating the V CF F ile produced by the Galaxy workflow becomes equivalent to the one as input of Taverna workflow. A PROV example associating a file name and its fingerprint is reported below: <http://fr.symetric#c583bef6-de69-4caa-bc3a-00000000> a prov:Entity ; rdfs:label "my-variants.vcf"^^xsd:String ; crypto:sha512 "1d305986330304378f82b938d776ea0be48eda8210f7af6c 152e8562cf6393b2f5edd452c22ef6fe8c729cb01eb3687ac35f1c5e57ddefc4 6276e9c60409276a"^^xsd:String .

The following SPARQL Construct query can be used to produce owl:sameAs relationships :

CONSTRUCT { ?x owl:sameAs ?y } WHERE { ?x a prov:Entity . ?x crypto:sha512 ?x_sha512 . ?y a prov:Entity . ?y crypto:sha512 ?y_sha512 . FILTER( ?x_sha512 = ?y_sha512 ) }

Multi-provenance reasoning. Once the traces of the workflow runs have been linked, we saturate the graph obtained using OWL entailment rules. This operation can be performed using an existing OWL reasoner (e.g., [START_REF] Carroll | implementing the semantic web recommendations[END_REF][START_REF] Jena | Reasoners and rule engines: Jena inference support[END_REF]). We then start by repeatedly applying the TGDs and EGDs derived from the W3C PROV constraint document, as illustrated in section 3.1 and 3.2. The harmonization process terminates when we can no longer apply any existing TGD or EGD. This harmonization process raises the question as to whether such process will terminate. The answer is affirmative. Indeed, it has been shown in the W3C PROV Constraint document that the constraints are weakly acyclic, which guarantees the termination of the chasing process in polynomial time (see Fagin et al. [START_REF] Fagin | Data exchange: semantics and query answering[END_REF] for more details).

Application of provenance harmonization: domain-specific experiment reports

In this section we propose to exploit previously harmonized provenance graphs by transforming them into Linked Experiment Reports. These reports are no longer machine-only-oriented and benefit from a humanly tractable size, and domain-specific concepts. Several ontologies and controlled vocabularies have been proposed to capture and organize knowledge associated to in silico experiments.

Domain-specific vocabularies. Workflow annotations. P-Plan13 is an ontology aimed at representing the plans followed during a computational experiment.

Plans can be atomic or composite and are a made by a sequence of processing Steps. Each Step represents an executable activity, and involves input and output Variables. P-Plan fits well in the context of multi-site workflows since it allows to work at the scale of a site-specific workflow as well as at the scale of the global workflow. Domain-specific concepts and relations. To capture knowledge associated to the data processing steps, we rely on EDAM 14 which is actively developed, in the context of the Bio.Tools registry, and which organizes common terms used in the field of bioinformatics. However these annotations on processing tools do not capture the scientific context in which a workflow takes place. SIO 15 , the Semantic science Integrated Ontology, has been proposed as a comprehensive and consistent knowledge representation framework to model and exchange physical, informational and processual entities. Since SIO has been initially focusing on Life Sciences, and is reused in several Linked Data repositories, it provides a way to link the data routinely produced by PROV-enabled workflow environment to major linked open data repositories, such as Bio2RDF.

NanoPublications 16 are minimal sets of information to publish data as citable artifacts while taking into account the attribution and authorship. NanoPublications provide named graphs mechanisms to link Assertion, Provenance, and Publishing statements. In the remainder of this section, we show how fine-grained and machine-oriented provenance graphs can be summarized into NanoPublications.

Linked Experiment Reports Based on harmonized multi-provenance graphs, we show how to produce NanoPublications as exchangeable and citeable scientific experiment reports. Figure 3.3 drafts how data artifacts and scientific context can be related to each other for the motivating scenario introduced in section 2. The expected Linked Experiment Report would be a NanoPublication as follows. For the sake of simplicity we omitted the definition of namespaces, and we used the labels of SIO predicates instead of their identifiers.

Table 1: [before,after] metrics characterizing the impact of the provenance harmonization process. wDF refers to wasDerivedFrom properties and wIB refers to wasInfluencedBy.

The processing time of the OWL entailments, TGDs, and EGDs provenance harmonization process is near to 5 seconds as shown in Table 1. This is negligible in the context of scientific workflows, which generally rely on possibly long batch job submissions. With respect to the inferred predicates, Table 1 also shows that the number of wasInfluencedBy (wIB) is important. In spite of its loose semantics, these inferred statements could be helpful for tracing data lineage in provenance graphs. Even if not present in the original PROV graph, SHARP was able to produce these common data lineage relations. We can also note that the harmonization process does not allow to infer wasDerivedFrom (wDF) relations. By design, the PROV inference regime does not allow the inference of new wasDerivedFrom relations, which means that a particular attention should be paid to initially capture this provenance relation.

Usage of semi-automatically produced NanoPublications

We run the multi-site experiment of section 2 using Galaxy and Taverna workflow management systems. The Galaxy workflow has been designed in the context of the SyMeTRIC systems medicine project, and was run on the production Galaxy instance 18 of the BiRD bioinformatics infrastructure. The Taverna workflow was run on a desktop computer. Provenance graphs were produced by the Taverna built-in PROV feature, and by a Galaxy dedicated provenance capture tool 19 , Table 2: Most prominent predicates when considering the initial two PROV graphs and their harmonization (PROV++)

We executed the summarization query proposed in section 3.4 on the harmonized provenance graph. The resulting NanoPublication (assertion named graph) represents the input DNA sequences aligned to the GRCh37 human reference genome through an sio:is-variant-of predicate. It also links the annotated variants (Taverna WF output) with the prepossessed DNA sequences (Galaxy WF inputs). Related to the Q3 life-science question highlighted in section 2, this NanoPublication can be queried to retrieve for instance the reference genome used to select and annotate the resulting genetic variants.

Related Works

Data harmonization (integration) [START_REF] Doan | Principles of Data Integration[END_REF] and summarization [START_REF] Aggarwal | Graph data management and mining: A survey of algorithms and applications[END_REF] have been largely studied in different research domains. Our objective is not to invent yet another technique for integrating and/or summarizing data. Instead, we show how provenance constraint rules, domain annotations, and Semantic Web techniques can be combined to harmonize and summarize provenance data into linked experiment reports.

There have been several proposals and tools that tackle scientific reproducibility 20 . For example, Reprozip [START_REF] Chirigati | Reprozip: Using provenance to support computational reproducibility[END_REF] captures operating system events that are then utilized to generate a workflow illustrating the events that happened and their sequences. While valuable, such proposals neither address the harmonization of provenance traces recorded by different analysis tools that utilize dif-ferent PROV extension nor machine-and human-tractable experiment reports, as proposed in SHARP.

Datanode ontology [START_REF] Daga | Describing semantic web applications through relations between data nodes[END_REF] proposes to harmonize data by describing relationships between data artifacts. Datanode allows to present in a simple way dataflows that focus on the fundamental relationships that exist between original, intermediary, and final datasets. Contrary to Datanode, SHARP uses existing PROV vocabularies and constraints to harmonize provenance traces, thereby reducing harmonization efforts.

LabelFlow [START_REF] Alper | Labelflow: Exploiting workflow provenance to surface scientific data provenance[END_REF] proposes a semi-automated approach for labeling data artifacts generated from workflow runs. Compared to LabelFlow, SHARP uses existing PROV ontology and Semantic Web technology to connect and harmonizes the dataflows. Moreover, LabelFlow is confined to single workflows, whereas SHARP targets a collection of workflow runs that are produced by different workflow systems.

In previous work [START_REF] Gaignard | From scientific workflow patterns to 5-star linked open data[END_REF], we proposed PoeM to produce linked in silico experiment reports based on workflow runs. As SHARP, PoeM leverages Semantic Web technologies and reference vocabularies (PROV-O, P-Plan) to generate provenance mining rules and finally assemble linked scientific experiment reports (Micropublications, Experimental Factor Ontology). SHARP goes steps forward by proposing the harmonization of provenance traces recorded by different workflow systems.

Conclusions

In this paper, we presented SHARP, a Linked Data approach for harmonizing cross-workflow provenance. The resulting harmonized provenance graph can be exploited to run cross-workflow queries and to produce provenance summaries, targeting human-oriented interpretation and sharing. Our ongoing work includes deploying SHARP to be used by scientists to process their provenance traces or those associated with provenance repositories, such as ProvStore. For now, we work on multi-site provenance graphs with centralized inferences. Another exciting research direction would be to consider low-cost highly decentralized infrastructure for publishing NanoPublication as proposed in [START_REF]Decentralized provenance-aware publishing with nanopublications[END_REF].

Fig. 2 . 1 :

 21 Fig. 2.1: A multi-site genomics workflow, involving Galaxy and Taverna workflow environments.

Fig. 3 . 1 :

 31 Fig. 3.1: Example of a qualified relationship.

Figure 3 .Fig. 3 . 2 :

 332 Figure 3.2 presents inferred statements in dashed arrows resulting from the application of this rule.

Fig. 3 . 3 :

 33 Fig. 3.3: Expected experiment report, linking the most relevant multi-site workflow artifacts with domain specific statements, and scientific context.

  List ă P air ă N ode, N ode ąą pq G 1 .listStatementsp˚, ˚, sourceq) do 10 G 2 Ð G 2 .addpin.getSubjectpq, in.getP redicatepq, targetq 11 G 2 Ð G 2 .delpinq 12 foreach (out P G 1 .listStatementspsource, ˚, ˚q) do 13 G 2 Ð G 2 .addptarget, out.getP redicatepq, out.getObjectpqq

	4	repeat
	5	S Ð f indSubstitutionspG 1 q
	6	foreach (s P S) do
	7	source Ð sr0s
	8	target Ð sr1s
	9	foreach (in P

14

G 2 Ð G 2 .delpoutq 15 until pS.sizepq " 0q

DNA sequencers can decode genomic sequences in both forward and reverse directions which improves the accuracy of alignment to reference genomes.

[START_REF] Alper | Labelflow: Exploiting workflow provenance to surface scientific data provenance[END_REF] BWA-mem: http://bio-bwa.sourceforge.

net 6 PICARD: https://broadinstitute.github.io/

picard/ 7 SAMtools sort: http://www.htslib.org

https://www.w3.org/TR/rdf11-concepts/#dfn-blank-node

http://purl.org/net/p-plan

http://edamontology.org

http://sio.semanticscience.org

https://provenance.ecs.soton.ac.uk/store/

https://galaxy-bird.univ-nantes.fr/galaxy/

https://github.com/albangaignard/sharp-prov-toolbox

:head { ex:pub1 a np:Nanopublication . ex:pub1 np:hasAssertion :assertion1 ; np:hasAssertion :assertion2 . ex:pub1 np:hasProvenance :provenance . ex:pub1 np:hasPublicationInfo :pubInfo . } :assertion1 { ex:question a sio:Question ; sio:has-value "What are the effects of SNPs located in exons for study-Y samples" ; sio:is-supported-by ex:referenceGenome ; sio:is-supported-by ex:sample_001 ; sio:is-supported-by ex:annotatedVariants . } :assertion2 { ex:referenceGenome a sio:Genome . ex:sample_001 a sio:Sample ; sio:is-variant-of ex:referenceGenome ; sio:has-phenotype ex:annotatedVariants .

ex:annotatedVariants sio:is-supported-by ex:referenceGenome . } :provenance { :assertion2 prov:wasDerivedFrom :harmonizedProvBundle .} :pubInfo { ex:pub1 prov:wasAttributedTo ex:MyLab . }

To produce this NanoPublication, we identify a data lineage path in multiple PROV graphs, beforehand harmonized (as proposed in section 3). Since we identified the prov:wasInfluencedBy as the most commonly inferred lineage relationship, we search for all connected data entities through this relationship. Then, when connected data entities are identified, we extract the relevant ones so that they can be later on incorporated and annotated through new statements in the NanoPublication. The following SPARQL query illustrates how :assertion2 can be assembled from a matched path in harmonized provenance graphs. The key point consists in relying on SPARQL property path expressions (prov:wasInfluencedBy)+ to identify all paths connecting data artifacts composed by one or more occurrences of the prov:wasInfluencedBy predicate. Such SPARQL queries could be programmatically generated based on P-Plan templates as it has been proposed in our previous work [START_REF] Gaignard | From scientific workflow patterns to 5-star linked open data[END_REF].

CONSTRUCT {

GRAPH :assertion { ?ref_genome a sio:Genome . ?sample a sio:Sample ; sio:is-variant-of ?ref_genome ; sio:has-phenotype ?out . ?out rdfs:label ?out_label . ?out sio:is-supported-by ?ref_genome . } } WHERE { ?sample rdfs:label ?sample_label. FILTER (contains(lcase(str(?sample_label)), lcase("fastq"))) . ?ref_genome rdfs:label ?ref_genome_label. FILTER (contains(lcase(str(?ref_genome_label)), lcase("GRCh"))) . ?out ( prov:wasInfluencedBy )+ ?sample ?out tavernaprov:content ?out_label . FILTER (contains(lcase(str(?out_label)), lcase("exons"))) . }

Experimental results and discussion

As a first evaluation, we ran two experiments. The first one evaluates the performance of harmonization in terms of execution time, number and nature of inferred relations. In a second experiment, we evaluated the ability of the system to answer the domain-specific questions of our motivating scenario.

Harmonization of heterogeneous PROV traces

In this experiment, we used provenance document of ProvStore 17 . Specifically, we selected three documents, namely P A (ID 113207), P B (ID 113206), and P C (ID 113263). These documents have different sizes from 10 to 666 triples and use different concepts and relations of PROV. We ran the provenance harmonization process as described in this paper using such documents on a classical desktop computer (4-cores CPU, 16GB of memory). We computed the mean time and standard deviation based on five executions of the harmonization, as well as the size of the provenance graph before and after the harmonization. based on the Galaxy API, the later transforms a user history of actions into PROV RDF triples. Table 2 presents a sorted count of the top-ten predicates in i) the Galaxy and Taverna provenance traces without harmonization, ii) these provenance traces after the first iteration of the harmonization process:


Alban Gaignard
email: alban.gaignard@univ-nantes.fr

Khalid Belhajjame

Hala Skaf-Molli

SHARP: Harmonizing Galaxy and Taverna workflow provenance

Keywords: Reproducibility, Scientific Workflows, Provenance, Prov Constraints

SHARP is a Linked Data approach for harmonizing cross-workflow provenance. In this demo, we demonstrate SHARP through a real-world omic experiment involving workflow traces generated by Taverna and Galaxy systems. SHARP starts by interlinking provenance traces generated by Galaxy and Taverna workflows and then harmonize the interlinked graphs thanks to OWL and PROV inference rules. The resulting provenance graph can be exploited for answering queries across Galaxy and Taverna workflow runs.

Introduction

Imagine a system that allows scientists to answer queries like Which parameters were used by my colleagues in their workflow that would explain my workflow results ! Answering such queries requires the exploitation of provenances traces generated by different workflow systems. PROV has been adopted by a number of workflow systems for encoding the traces of workflow executions. However, workflow systems extend PROV differently which yields heterogeneity in the generated provenance traces. This heterogeneity diminishes the value of such traces, e.g. when combining and querying provenance traces of different workflow systems.

In this demo, we present SHARP; an approach for interlinking and harmonizing provenance traces of different workflow systems using PROV inferences. We demonstrate SHARP through a real-world omic experiment involving workflow traces generated by the Galaxy and Taverna systems.

SHARP: Harmonizing multi-PROV Graphs

SHARP exploits the fact that provenance vocabularies used by workflow systems extend the W3C PROV-O ontology. It uses reasoning for harmonizing provenance traces thanks to OWL entailment regime and PROV constraints [START_REF] Cheney | Constraints of the provenance data model[END_REF]. SHARP identifies three categories of rules of Prov constraints with respect to expressiveness (i) rules that contain only universal variables, (ii) rules that contain existential variables, and (iii) rules making use of n-array relations (with n ě 3). SHARP formalizes constraints as tuple-generating dependencies TGDs and equality-generating-dependencies EGD [START_REF] Abiteboul | Foundations of Databases[END_REF], and then implements them as Jena rules.

The following example illustrates usage and generation from derivation rule. The following rule states that if an entity e 2 was derived from an entity e 1 , then there exists an activity a, such that a used e 1 and generated e 2 .

wasDerivedFrompe2, e1q Ñ D a usedpa, e1q, wasGeneratedFrompe2, aq. The overall provenance harmonization process consists in i) interlinking data artifacts through owl:sameAs property, ii) applying OWL inferences, iii) applying PROV constraints TGDs and EGDs as a set of inference rules. This process terminates because PROV constraints are known to be weakly acyclic [START_REF] Fagin | Data exchange: semantics and query answering[END_REF].

SHARP Demo Scenario

We use a real scientific experiment conducted through two bioinformatics workflows. The first workflow, in blue in Figure 3.1, is implemented in Galaxy [START_REF] Afgan | The galaxy platform for accessible, reproducible and collaborative biomedical analyses: 2016 update[END_REF] and addresses DNA data pre-processing which is loosely coupled to the scientific hypothesis. This workflow takes as input two DNA sequences from two biological samples s1 and s2, represented in green. The second workflow is implemented with Taverna [START_REF] Wolstencroft | The taverna workflow suite: designing and executing workflows of web services on the desktop, web or in the cloud[END_REF], and highly depends on scientific questions. It is generally conducted by life scientists possibly from different research labs and with less computational needs. In the following section, we explain how SHARP interlinks and harmonizes provenances graphs produced by two workflow systems.

Taverna workflow @research-lab

Galaxy workflow @sequencing-facility

Variant

Implementation

Galaxy PROV

For now, it is not possible to export provenance from Galaxy workflow environment4 through a standard schema and format. To address this issue and to allow the combination of multiple workflow execution traces, we developed a loosely coupled tool aimed at exporting Galaxy user histories into PROV RDF data. This tool results in a command-line interface and a web application which allows users to list and export the content of their Galaxy Workflow histories, as illustrated in Figure 4.1.

Users provide the URL of their Galaxy workflow portal, and their private API key. Then, the tool communicates with the Galaxy API through the HTTP protocol and JSON documents. It can produce as a result RDF PROV triples in the Turtle syntax, or a graphical representation of the PROV sub-graph. The command line interface has been implemented in Java and makes use of the Jersey library for connecting to the REST API. The command line interface is available as open-source 5 . The back-end web application was also implemented in Java. Jetty was used as a standalone web server hosting an HTTP REST API, and a mongoDB database was setup to collect basic usage metrics. The frontend was implemented in HTML and JavaScript (BackboneJS, D3.JS). The web application will be available shortly as open-source in the same repository.

Multi PROV harmonization

We implemented the PROV harmonization process in a command line tool available as open-source6 . This tool can be used to infer new PROV statements for a single provenance trace by providing an input trace in the Turtle syntax. More interestingly, it can be used to interlink and harmonize cross-workflow provenance traces by specifying multiple provenance traces as input, accompanied with owl:sameAs statements. Finally, based on inferred prov:wasInfluencedBy predicates, cross-workflow data lineage can be visualized.

This tool has been implemented in Java and is supported by Jena7 for RDF data management and reasoning tasks. PROV Constraints8 inference rules have been implemented in the Jena syntax9 . HTML and JavaScript (D3.JS) code templates have been used to generate harmonized provenance visualization.

The automatic generation of owl:sameAs statements between files based on hashing techniques, as well as a web interface are still under active development. These features should available soon in the same repository.

Results

This demonstration shows that SHARP allows to homogenize PROV graphs and achieve unified SPARQL queries across multiple provenance traces. For instance, the following query assembles a data influence graph between multiple workflow execution traces in which some data artifacts play two roles, i) output for a give workflow, and ii) input for other workflows. This query matches prov:wasInfluencedBy properties resulting from harmonization process. These properties were not initially stated neither in the Taverna nor in the Galaxy provenance traces.

Conclusions

In this paper, we presented SHARP, a Linked Data approach for harmonizing crossworkflow provenance. The resulting harmonized provenance graph can be exploited to run cross-workflow queries. Our ongoing work includes the automation of owl:sameAs property generation as well as providing a unified web interface. As future works, we will address human-centered interpretation of possibly massive PROV graphs through domain-specific summarization techniques.

Fig. 3 .

 3 Fig. 3.1: A multi-site genomics workflow, involving Galaxy and Taverna systems.

Fig. 4 .

 4 Fig. 4.1: A web application to export provenance graphs from Galaxy user histories in PROV.

Figure 5 .

 5 1 shows the resulting data lineage graph associated with the two workflow traces of our motivating use case (Figure 3.1). While the left part of the graphs represents the Galaxy workflow invocation, the right part represents the Taverna one.

Fig. 5 . 1 :

 51 Fig. 5.1: prov:wasInfluencedBy properties between Galaxy and Taverna.

https://usegalaxy.org

galaxy-PROV: https://github.com/albangaignard/galaxy-PROV

sharp-prov-toolbox: https://github.com/albangaignard/sharp-prov-toolbox

Jena: https://jena.apache.org

https://www.w3.org/TR/prov-constraints/

https://github.com/albangaignard/sharp-prov-toolbox/blob/master/ SharpProvToolbox/src/main/resources/provRules_all.jena


Keywords: Expansive Soil, Suction, Compacted Soil, Hydromechanical behaviour, Compressibility, Laboratory Tests

A study of the hydromechanical behaviour of a compacted swelling material in the range of suctions comprised between 0 and 40 MPa was performed. This study has required the development of two kinds of suction controlled oedometer devices based on two different suction control techniques. In the range of suctions higher than 8.5 MPa, the saturated salt solutions method was used and a new oedometer using this suction control technique was developed. For suctions lower than 8.5 MPa an osmotic oedometer was used. Despite the differences between the applied suction components (matric and total), the correlation between the two methods was verified for the tested material. The second part of the paper presents a set of oedometer tests conducted under various suctions. The effect of the applied suction on the hydromechanical parameters was studied. First, two swelling phases were highlighted: a low swelling phase above a suction of 4 MPa and a high swelling one below this value. These phases were considered as being related to the microstructure of compacted swelling clays. Secondly, it was shown that the slopes of the elastic part and of the plastic part of the consolidation curves were not influenced significantly by the applied suctions. In opposition, the preconsolidation pressure is affected by the decrease of the applied suctions even in the low swelling phase. Such a behaviour could be explained by the effects of wetting on the microstructure.

INTRODUCTION

Because of their very low permeability, compacted swelling soils are used for the construction of engineered barriers in waste disposal facilities. During their lifetime, these materials undergo wetting/drying cycles, i.e. suction variations. These soils exhibit large volume variations in response to suction changes. However, the relationship between suction variations and compressibility is not well known as far as compacted swelling materials are concerned. The experimental investigation of the hydromechanical behaviour of unsaturated swelling soils requires the use of suction controlled devices in a comprehensive range of suction, from low to very high suctions. However there are very few suction controlled studies performed over an extensive range of suction in the literature [START_REF] Bernier | Suction controlled experiments on Boom clay[END_REF]Al Mukthar et al. 1999;[START_REF] Villar | Investigation of the behaviour of bentonite by means of suctioncontrolled oedometer tests[END_REF][START_REF] Alonso | Expansive bentonite/sand mixtures in cyclic controlled-suction drying and wetting[END_REF][START_REF] Cui | A model for the volume change behavior of heavily compacted swelling clays[END_REF]. This is mainly related to the fact that the methods commonly used in experimental testing, such as the air overpressure method [START_REF] Richards | Capillary conduction of liquids through porous medium[END_REF] and the osmotic method [START_REF] Kassif | Experimental relationship between swell pressure and suction[END_REF] investigate only a small suction range, from saturation up to a few MPa (Fig. 1). Some developments of these methods have been used, but the maximum suction they are able to reach is about 14 MPa [START_REF] Villar | First results of suction controlled oedometer tests in highly expansive montmorillonite[END_REF][START_REF] Delage | The relationship between suction and the swelling properties in a heavily compacted swelling clay[END_REF]. The only available method to reach several hundred MPa is the control of relative humidity by means of salt solutions. However, this is a complex method to implement because of some uncertainties on the imposed suction due to temperature and pressure variations, and the measurement of the exact value of the relative humidity inside the testing device [START_REF] Delage | The relationship between suction and the swelling properties in a heavily compacted swelling clay[END_REF][START_REF] Cuisinier | Comportement hydromécanique des sols gonflants compactés[END_REF].

This paper presents a study of the hydromechanical behaviour of a compacted swelling soil carried out on a range of suction comprised between 0 and 40 MPa. In the first part, oedometers using the osmotic method and others based on the saturated salt solutions technique are introduced. The feasibility of these devices and the correlation between the two suction control methods is also discussed. In the second part, a set of suction controlled oedometer tests is presented. From these results, the influence of suction on the swelling potential ∆H/H, the preconsolidation pressure p 0 (s), the slopes of the elastic part κ, and of the plastic part λ(s), of the consolidation curves is discussed.

The results are considered with two independent variables: the net vertical stress σ v *, defined as the difference between the total vertical stress and the pore-air pressure, and the suction s, which corresponds to the difference between the pore-air pressure and the pore-water pressure [START_REF] Coleman | Stress-strain relations for partly saturated soils[END_REF][START_REF] Matyas | Volume change characteristics of partially saturated soils[END_REF]).

DESCRIPTION OF THE SUCTION CONTROLLED OEDOMETER DEVICES

Figure 1 shows that at least two complementary suction control techniques are required to perform a study over an extensive suction range. The salt solutions technique for suctions higher than 8.5 MPa and the osmotic method for suctions lower than this value were selected.

Salt solutions method

The basic principle of the saturated salt solutions technique is to introduce a sample inside a hermetic chamber where the relative humidity is maintained constant with a salt solution. The water exchange occurs by vapour transfer. The relative humidity Hr (%) is linked to the suction, through Kelvin's law:

) Hr ln( g M T R s w γ = (1)
with R = universal gas constant (8.31 J.mol -1 .K -1 ); γ w = unit weight of water (9.81 kN.m -3 ); g = gravitational constant (9.81 m.s -2 ); M = molecular weight of water (18 10 -3 kg.mol -1 ); T = absolute temperature (K). It was possible to apply different suctions with this method, depending on the kind of salt solution used and its concentration. In this study, totally saturated salt solutions were selected.

The value of the relative humidity imposed by a given salt is highly dependent on temperature [START_REF] Afnor Nf | Mesure de l'humidité de l'air -Générateurs d'air humide à solutions salines pour l'étalonnage des hygromètres[END_REF]. In our tests, the room temperature was maintained at 20 ± 0.15 °C. The relative humidity imposed by a given saturated salt solution is known with an uncertainty comprised between 1 and 2 % (AFNOR, 1999). [START_REF] Delage | The relationship between suction and the swelling properties in a heavily compacted swelling clay[END_REF] and [START_REF] Cuisinier | Développement d'un appareil oedométrique à succion contrôlée pour l'étude des sols gonflants[END_REF] have demonstrated that these uncertainties limit the use of saturated salt solutions to suctions higher than 8.5 MPa, because below this value the relative uncertainty on the imposed suction is higher than 15 %.

Given thermodynamic considerations, the soil suction is the sum of several components; a matric potential (adsorption and capillary), an osmotic potential (related to solute concentrations), and other components (related to pressure and temperature) which are supposed as being of negligible importance here. A comprehensive review of these considerations is available in [START_REF] Fredlund | Soils mechanics for unsaturated soils[END_REF]. With the saturated salt solutions method, total suction is imposed during a test.

The new odometer device using saturated salt solutions is shown in Figure 2. This device combines, in the same system, the functions of a basic oedometer (AFNOR, 1997) and of a closed chamber with constant relative humidity (ISO 483, 1998). Based on this principle, two different devices, with two maximum vertical pressures (1 200 and 20 000 kPa) were developed. The range of suction that could be attained was comprised between 8.5 and 292.4 MPa. The diameter of the sample was 7.4 cm in the low vertical stress oedometer and 5 cm in the other one. In both cases, the initial height of the sample was about 1 cm. The different elements of the device in contact with the sample were made of porous steel in order to facilitate the vapour transfer between the sample and the saturated salt solution. Following a change of the applied suction and/or the vertical stress, several weeks are required to reach deformation equilibrium [START_REF] Cuisinier | Comportement hydromécanique d'un sol gonflant sous très fortes succions[END_REF]. Therefore, one test might take several months to be completed. The validation of the efficiency of these new oedometers was presented in [START_REF] Cuisinier | Study of the hydromechanical behaviour of a swelling soil under high suctions[END_REF].

Osmotic method

In this method, a semi-permeable membrane, is introduced between a solution of macromolecules and an unsaturated soil sample [START_REF] Zur | Osmotic control of the matric soil-water potential: I. Soil water system[END_REF]. The exchange of water is due to the process of osmosis. The amount of exchanged water, and therefore the suction, is controlled by the macromolecule concentration: the higher the concentration, the higher the suction. The macromolecule commonly in use is the polyethyleneglycol (PEG) with a molecular weight of 20 000 or 6 000 Da1 . The relationship between PEG concentration and suction (Fig. 3) is known for suctions ranging from 0 to 1.5 MPa and is independent of the PEG molecular weight [START_REF] Williams | An evaluation of polyethyleneglycol (PEG) 6 000 and PEG 20 000 in the osmotic control of soil water matric potential[END_REF]. In this range, [START_REF] Cui | Étude du comportement d'un limon compacté non saturé et de sa modélisation dans un cadre élastoplastique[END_REF] has proposed an empirical calibration relationship between PEG concentration and suction:

2 c 11 s = (2)
where s is the suction in MPa and c the concentration of the PEG solution expressed in g of PEG per g of water. This equation is also reproduced in Figure 3. The temperature influences the relationship between PEG concentration and suction [START_REF] Guiras-Skandaji | Déformabilité des sols argileux non saturés : etude expérimentale et modélisation[END_REF]. In order to limit this effect, the temperature was maintained at 20 ± 1.5 °C.

With the osmotic suction control method, only the matric suction component of a sample is mastered during a test.

It was necessary to calibrate the PEG solution from a suction of 1.5 MPa up to 8.5 MPa. For such a calibration, a sample of PEG solution, prepared at a known concentration, is enclosed in a hermetic chamber where the relative humidity is kept constant by a saturated salt solution. [START_REF] Delage | The relationship between suction and the swelling properties in a heavily compacted swelling clay[END_REF] have performed such tests and their results, obtained with PEG 6 000, are plotted in Figure 3. An additional calibration test was made with a similar procedure using PEG 6 000 for a suction of 8.5 MPa. The final concentration of the PEG solution was 0.879 g of PEG per g of water. The result of this test was in good agreement with existing data and the empirical relationship. The osmotic method could therefore be used up to 8.5 MPa.

A schematic representation of an osmotic oedometer is presented in Figure 4 ( [START_REF] Kassif | Experimental relationship between swell pressure and suction[END_REF]. A pump allows to circulate a solution of macromolecules (PEG), at a given concentration. The solution passes through the grooved base of the oedometer, which was designed to allow fluid to circulate through the whole bottom surface of the sample. Between the sample and the PEG solution a semi-permeable membrane (Spectra/Por® n°4) was introduced to prevent PEG macromolecules from passing toward the sample. In our device, the maximum vertical pressure accessible was 1 800 kPa. The range of suction was comprised between 0 and 8.5 MPa. The deformability of the semi-permeable membrane and the overall device was evaluated. The evaporation through the upper face of the sample was minimized by positioning a plastic film all around the oedometer. The diameter of the sample was 7 cm and its initial height was about 1 cm. When a given suction was applied, approximately ten days were required for a deformation equilibrium to be reached. The mechanical loading was made in the same manner as in a typical oedometer test, and approximately 2 days were needed to reach a deformation equilibrium for a given stress step [START_REF] Cuisinier | Comportement hydromécanique des sols gonflants compactés[END_REF].

MATERIAL AND SAMPLE PREPARATION

The study was conducted with an artificially prepared mixture (40 % of silt and 60 % of bentonite). The mineralogical composition of the materials was determined by X ray diffractometry. The silt contained 60 % quartz, 20 % montmorillonite, 11 % feldspar, and the remaining part was made up of kaolinite and mica. The bentonite was composed of more than 90 % of calcium montmorillonite. The main physical properties of the materials and of the mixture are shown in Table 1.

The size of the particles used to prepare the samples was less than 400 µm (obtained by sieving). The materials were mixed together and wetted up to a gravimetric water content of 15 % (dry side of optimum). Then the mixture was statically compacted under a vertical pressure of 1 000 kPa. This low gravimetric water content, close to the shrinkage limit, was selected in order to prevent the shrinkage of the sample when very high suctions were imposed. It was not possible to prepare samples at a gravimetric water content lower than 15 % as they would not have been sufficiently cohesive to be handled.

Under these conditions, the initial dry unit weight of the samples was about 12.7 kN.m -3 . The initial matric suction, measured by the Filter Paper Method (ASTM, 1995a), was comprised between 20 and 25 MPa and the osmotic suction was comprised between 1 and 2 MPa. The swelling potential ∆H/H when a sample is fully saturated, and the swelling pressure P s , required to eliminate height variations during wetting, measured by the free swelling method (ASTM, 1995b), were respectively 19 % and 250 kPa. The gravimetric water content determined after full saturation inside an oedometer was 49 %.

STUDY OF HYDROMECHANICAL BEHAVIOUR FROM LOW TO VERY HIGH

SUCTIONS

In the remaining part of the paper, the tests are referenced in order to identify the type of suction control method: O for osmotic and S for saturated salt solutions. The subsequent letters indicate qualitatively the stress paths followed: W for wetting phase, D for drying phase and L for the loading/unloading phase.

Test program

The stress paths followed are plotted in Figure 5. All the tests began at point "A" under a low vertical pressure of about 10 kPa, and an initial suction of about 20/25 MPa. During the first phase, a different suction was applied in several steps for each test. In the second phase the samples were loaded in several steps and then unloaded under constant suction. The test OWL4 is not represented in Figure 5 as the applied suction was 0 MPa in this test.

Correlation between two suction control methods

As these two methods do not impose the same suction components, the correlation between the results obtained with them was checked. Two tests were conducted: OWL1 in the osmotic oedometer and SWL1 in the saturated salt solutions oedometer. In both tests, the same stress paths were followed. These paths began by a wetting from the initial suction to a suction of 8.5 MPa under a low vertical pressure (10 kPa). Following equilibrium under a constant suction, the samples were loaded in several steps and then unloaded (Fig. 6). The swelling potential ∆H/H registered at the end of the wetting phase, the slope of the consolidation curves κ, the slope of the virgin compression line λ(s), and the preconsolidation pressure p 0 (s), were determined and summarized in Table 2. In the same table, the initial and final gravimetric water contents of the samples w i and w f , are given. As is shown in Figure 6 and in Table 2, λ(s) and κ are not significantly affected by the suction control method contrary to p 0 (s), which is 80 kPa lower for the test performed in the osmotic oedometer. The swelling potential and the final water content are both higher in the test performed in the osmotic oedometer.

The prepared samples contained a certain amount of dissolved salts. [START_REF] Olsen | Osmosis: a cause of apparent deviations from Darcy's law[END_REF] has demonstrated that, when exposed to distilled water, the dissolved salts contained inside a soil sample tend to diffuse outwards of the sample, and the water inward of the sample. This phenomenon occurred in our osmotic tests as the semi-permeable membrane is permeable to water and solutes. In fact, during a test in the osmotic oedometer, a certain amount of water exchange is controlled by the PEG concentration, but an additional amount of water enters the soil sample because of this solute gradient. This could explain the higher water content and swelling potential ∆H/H in test OWL1 than in test SWL1 where such a phenomenon was not possible. The larger ∆H/H in test OWL1 than in test SWL1 tend to soften the soil structure and consequently, p 0 (s) is low in test OWL1. On the other hand, small variations in the calibration of osmotic suction applied by PEG solution or the uncertainty associated to suction imposed by salt solutions may explain the small differences observed in both tests.

The effect of suction components on the compressibility parameters, λ(s) and κ, is not significant in our tests. This could be explained by the nature of the clay used. During the vertical loading stage, the salt concentration is probably higher in sample SWL1 than in sample OWL1. [START_REF] Olson | Mechanisms controlling compressibility of clays[END_REF] have also shown that the salt concentration slightly affects the compressibility parameters, λ(s) and κ of calcium montmorillonite.

These tests demonstrate that the influence of the osmotic component of suction is not significant for a suction of 8.5 MPa, under which the correlation between both suction control techniques is checked for this material.

Hydromechanical behaviour from low to high suctions

Figure 7 depicts the relationship between the void ratio and the net vertical stress for all the tests. The hydromechanical parameters determined from these curves are presented in Table 2. The parameters λ(s) and κ are plotted in Figure 8. It seems that the parameter κ was not significantly affected by the applied suction in opposition to the parameter λ(s). These observations are similar to other data available in the literature (e.g. [START_REF] Alonso | Special problem soils. General report[END_REF].

Figure 9 compares the variation of p 0 (s) and ∆H/H after wetting at the applied suctions. First, it can be seen that the volume of the sample did not decrease significantly when a suction higher than the initial suction was applied (test SDL1 -40 MPa). During wetting two swelling phases were highlighted: a low swelling phase above 4 MPa and a high swelling phase below this value. It is well known that the swelling of clays occurs in several steps [START_REF] Kassif | Experimental relationship between swell pressure and suction[END_REF][START_REF] Komine | Prediction for swelling characteristics of compacted bentonite[END_REF]. The first step corresponds to the initial hydration of clays with the insertion of between the unit clay layer. This could explain the low swelling phase: the clay particles fill the initial voids of the sample. The high swelling phase started when the major part of the macropores of the sample were already filled by the expanded clay particles.

Figure 9 demonstrates that p 0 (s) decreased continuously from 40 down to 0 MPa. A basic assumption is to link this parameter to the density of the sample: the lower the density, the lower the preconsolidation pressure. But this interpretation is not sufficiently satisfactory to explain such a sharp decrease of preconsolidation pressure. A possible explanation could be the void filling by the clay particles in the low swelling phase. In fact, during the first stage of wetting, the macrostructural density is not changed significantly, but the microstructure of the sample is altered dramatically, decreasing the mechanical properties of the studied material.

However, further microstructural investigations are required before a conclusion can be arrived at on this point. It will also enable the influence of the montmorillonite swelling to be determined more precisely.

CONCLUSION

Two kinds of suction controlled oedometers, one with saturated salt solutions technique (control of total suction) and the other with the osmotic method (control of matric suction)

were used in this study. The correlation between the two methods was checked. It was found that, for the studied soil, the methods used did not significantly affect the values of the hydromechanical parameters determined.

The swelling upon wetting was studied as a function of the applied suction. Two swelling phases have been highlighted: a low swelling phase for suctions higher than 4 MPa and a high swelling phase below 4 MPa. The preconsolidation pressure is strongly affected by the suction decrease between the initial suction and 4 MPa, that is to say during the low swelling phase. This demonstrates that the preconsolidation pressure of a compacted swelling soil is not only a function of its density but it depends also on the microscopic repartition of the clay particles inside the soil.

Our results highlight the extreme sensitivity of the hydromechanical behaviour of a compacted swelling soil to any variation in suction, even in the range of very high suctions.

Figure 2

Schematic of the suction controlled oedometer device using saturated saline solutions [START_REF] Cuisinier | Comportement hydromécanique des sols gonflants compactés[END_REF]. Schematic of the suction controlled oedometer device using osmotic solutions.

Cuisinier and Masrouri

Figure 5

Stress paths followed.

Cuisinier and Masrouri

Figure 6

Correlation between the two suction control techniques.

Cuisinier and Masrouri

Figure 7

Results of the different suction controlled oedometer tests.

Cuisinier and Masrouri

Figure 8

Parameters κ and λ(s) as a function of the applied suction during mechanical loading (white signs: salt solutions technique; black signs: osmotic technique).

Cuisinier and Masrouri

Figure 9

Percent heave (∆H/H) after wetting to a given suction and preconsolidation pressure p 0 (s) as a function of the suction applied during mechanical loading (white signs: salt solutions technique; black signs: osmotic technique).

Cuisinier and Masrouri

Figure 2 .

 2 Figure 2. Schematic of the suction controlled oedometer device using saturated salt solutions.

Figure 3 .

 3 Figure 3. Calibration curve between suction and PEG concentration.

Figure 4 .

 4 Figure 4. Schematic of the suction controlled oedometer device using osmotic solutions.

Figure 5 .

 5 Figure 5. Stress paths followed.

Figure 6 .

 6 Figure 6. Correlation between the two suction control techniques.

Figure 7 .

 7 Figure 7. Results of the different suction controlled oedometer tests.

Figure 8 .

 8 Figure 8. Parameters κ and λ(s) as a function of the applied suction during mechanical

Figure 9 .

 9 Figure 9. Percent heave (∆H/H) after wetting to a given suction and preconsolidation pressure

  Figure 3

Table 2

 2 Hydromechanical parameters from s = 0 to 40.0 MPa. Range of suction of the main suction control techniques.

	[O: osmotic; S: saturated salt solutions; W: wetting; D: drying; L: loading]
	Test	Stress	Suction under	w i	w f	∆Η/Η	κ	λ(s)	p 0 (s)
	number	paths	which sample	(%)	(%)	(%)			(kPa)
		(Fig. 6)	is loaded*
			(MPa)
	SDL1	A-I-J-I	39.7	14.9	12.4	-0.2	0.02	0.26	1 090
	SL	A-B-A	20.8	14.9	15.1	0	0.03	0.28	1 000
	SWL1 A-C-D-C	8.5	15.0	16.8	0.5	0.03	0.31	450
	SWL2 A-C-D-C	8.5	15.0	17.0	0.5	0.03	0.30	490
	OWL1 A-C-D-C	8.5	14.7	17.7	1.2	0.03	0.29	370
	OWL2 A-C-E-F-E	4	14.5	20.7	2.8	0.03	0.30	200
	OWL3 A-G-H-G	1.2	14.9	26.4	11.6	0.03	0.23	65
	OWL4	/	0	14.7	42.0	16.2	0.05	0.22	50
	*: the initial total suction for all the samples is about 20/25 MPa

1 Dalton (Da) = 1.6605.10 -24 g.

Range of suction of the main suction control techniques.

Cuisinier and Masrouri