Chrysostomos Zeginis
email: zegchris@ics.forth.gr

Kyriakos Kritikos
email: kritikos@ics.forth.gr

Dimitris Plexousakis

Event Pattern Discovery for Cross-layer Adaptation of Multi-Cloud Applications

Keywords: Cloud computing, SOA, adaptation, modeling, pattern discovery

As Cloud computing becomes a widely accepted service delivery platform, developers usually resort in multi-cloud setups to optimize their application deployment. In such heterogeneous environments, during application execution, various events are produced by several layers (Cloud and SOA specific), leading to or indicating Service Level Objective (SLO) violations. To this end, this paper proposes a meta-model to describe the components of multi-cloud Service-based Applications (SBAs) and an event pattern discovery algorithm to discover valid event patterns causing specific SLO violations. The proposed approach is empirically evaluated based on a real-world application.

Introduction

Cloud computing is a rapidly emerging paradigm offering virtualized resources for developing applications. Its adoption in the Service Oriented Architecture (SOA) world is increasing; enterprises acknowledge its flexibility and elasticity by choosing among various offerings at all Cloud layers (IaaS, PaaS and SaaS). In addition, as developers try to optimize their application deployment cost and performance, they may also deploy application parts on multiple VMs [START_REF] Baryannis | Lifecycle Management of Service-based Applications on Multi-Clouds: A Research Roadmap[END_REF].

In this paper we focus on SBAs deployed on Clouds, which feature three main functional layers: the Business Process Management (BPM) layer, the Service Composition and Coordination (SCC) layer and the Service Infrastructure (SI) layer. In a Cloud environment, the SI layer maps to the PaaS and IaaS layers, while the SaaS layer includes the BPM and SCC layers. It is imperative that such distributed hosting environments, exhibit efficient cross-layer monitoring and adaptation mechanisms combining multi-layer monitored events and mapping them to suitable adaptation strategies. In [START_REF] Zeginis | Towards proactive crosslayer service adaptation[END_REF] we have investigated the need for cross-layer adaptation, as current techniques are mainly fragmented by considering a single SBA layer, while the few cross-layer ones [START_REF] Zengin | CLAM: Cross-layer Adaptation Manager for Service-Based Applications[END_REF][START_REF] Popescu | Taxonomy-driven Adaptation of Multi-Layer Applications using Templates[END_REF] do not consider multi-cloud aspects. Concerning monitoring, in [START_REF] Zeginis | Towards cross-layer monitoring of multi-cloud service-based applications[END_REF] we have presented a multi-cloud SBA framework. This paper goes a step further supporting multicloud SBA adaptation by focusing on an efficient method for processing the huge amount of monitored events and discovering frequent patterns leading to SLO violations. As such, a pattern discovery algorithm is introduced, exploiting a component meta-model whose instances describe SBA component dependencies. The discovered event patterns interrelate events leading to SLO violations and can be further exploited to enrich the scalability rules defined by experts.

The rest of the paper is structured as follows. Section 2 provides a motivating example, while Section 3 analyzes the multi-cloud monitoring and adaptation framework. In Section 4 we describe the component meta-model, exploited by the proposed pattern discovery algorithm (Section 5). Section 6 evaluates the algorithm's accuracy and performance. Finally, Section 7 reviews the related work, before Section 8 concludes and provides future work directions.

Motivating Example

A traffic management SBA deployed in a multi-cloud setup motivates our approach. In a normal traffic scanario, four tasks occur: environmental variable monitoring (T M ), public event and high traffic hours checking (T C ), current condition assessment (T A ) and device configuration (T D ). Task T A requires high computation and storage capabilities, while the other three tasks require moderate storage capacity and low computational power and must be deployed geographically close to the municipal infrastructure. Thus, these tasks can operate on a private/municipal Cloud with their data periodically sent for processing to a central Cloud, hosting T A . As illustrated in Fig. 1, various events are detected by the monitoring mechanisms in this multi-cloud setting, from lower level infrastructure events (e.g. low memory ((w)e 1 ), high CPU load ((c)e 2 ), network uptime ((c)e 4 ), to higher level events (e.g. service execution time ((w)e 3 , (w)e 6 or throughput ((w)e 5 ) violations. The main non-functional application goal is to capture warning (identified by we) or critical events (identified by ce) and interrelate them to discover event patterns leading to SLO violations. The architecture presented in our previous work [START_REF] Zeginis | Towards cross-layer monitoring of multi-cloud service-based applications[END_REF] for cross-layer multi-cloud SBA monitoring is realized and enhanced with specific techniques and algorithms to support proactive adaptation. In this multi-cloud framework (Fig. 2 -the shadowed components indicate where this paper focuses), each of these Clouds exhibits monitoring components, which directly interact with the Monitor Manager, through a complex event processing (CEP) server-client mechanism. The Metric Aggregator component assesses and stores the monitored events to the time-series database (TSDB). The Pattern Discoverer component periodically queries the TSDB to get the assessed raw events for a specific time interval and identifies raw event patterns leading to SLO violations (mapping to specific aggregate metrics). The TSDB provides the aggregated metric values, necessary for pattern discovery. The discovered patterns are sent directly to the Metric Aggregator to detect them at runtime. Upon pattern detection, the Metric Aggregator urges the Rule Engine of the Adaptation Engine to fire the respective scalability rule (i.e. proactive adaptation) dictating the application of an adaptation strategy, realized by the Adaptation Enactment component (some adaptation actions are already realized, especially those mapping to scaling mechanisms provided by Cloud providers). Critical events are also passed to the Rule Engine to perform reactive adaptation.

Component Meta-model

A particular component meta-model (Fig. 3) was developed via UML to describe the source components for each event type which constitute the SBA system, as well as their dependencies. Its main benefits are that it is extensive to capture the most common multi-cloud SBA components, related to functional and nonfunctional violations, and extensible to meet any SBA provider's needs, which may incorporate other layer-specific components utilized by its applications. Any adaptation manager can also exploit it to carefully design scalability rules based on the components' properties to stimulate the mapping from events to specific adaptation actions. Through capturing the component dependencies in a multi-cloud system, a root cause analysis for system faults can be performed. The Pattern Discovery Algorithm also exploits such dependencies to detect valid event patterns leading to critical events, where validity lies on causality by selecting events in the stream that drive the occurrence of other events in the pattern.

Pattern Discovery

This section presents an offline algorithm for discovering event patterns leading to specific SLO violations, based on propositional logic [START_REF] Sim | Logic-based pattern discovery[END_REF]. The algorithm exploits component dependencies and contingency tables (Fig. 4) to identify association rules between events. These tables display frequency distributions of candidate patterns and their negations as antecedents and the specified metric event, as well as its negation as consequences. It mainly focuses on discovering patterns by considering SOA and Cloud layers, but it can also be applied on a single layer, discovering layer-specific patterns.

The algorithm starts by filtering the event stream (line 3 ) from events coming from different Cloud providers than those used by the SBA. Then, the event stream is split based on the aggregate metric's time interval (line 4 ). Intervals are characterized as critical, if there is an aggregate metric violation, or noncritical, otherwise (line 5 ). For critical intervals, the temporal ordered sets of the raw events subset's powerset are calculated, from the first interval event to that before the last critical raw measurement. All the sets of the interval powersets are filtered to discard the ones not interrelated with each other, based on the component model (lines 6-11 ), but the single events that might map to Fig. 3: The Cloud component meta-model Algorithm 1 Event pattern discovery algorithm 1: Input: event stream, application, metric, interval size, component model 2: Output: discovered patterns, patterns ranking, association rules, ambiguous rules 3: filter raw events (ignore success /other applications'/other Cloud provider events) 4: divide event stream in event time intervals 5: define critical and non-critical intervals 6: while not end of event stream do 7:

A = events before the last critical raw event in this interval 8:

P(A) → powerset of set A 9:
filter sets of P(A) according to the component model 10:

update the powerset tree 11: end while 12: for i ← 1, treelevels do 13:

for j ← 1, treebranches do 14:

B i,j = current branch 15:

while not end of event stream do 16:

A = events before the last critical raw event in this interval 17:

C = critical aggregate event for the specified metric 18: compute S(Bi,j, C), S(Bi,j, ¬C), S(¬Bi,j, C), S(¬Bi,j, ¬C) in A 19:

update contingency table 20:

end while 21:

if (S(Bi,j, C) + S(¬Bi,j, ¬C)) > (S(¬Bi,j, C) + S(Bi,j, ¬C)) then 22:

create association rule (Bi,j → C) 23:

store Bi,j in pattern repository 24: else 25:

discard Bi,j 26:

end if 27: end for 28: end for the critical violation are considered. Then, a level-and a branch-based traversal of the tree-based structure storing the candidate patterns are performed to calculate and store (lines 15-20 ) the frequencies for each considered set's contingency table. The powerset tree (Fig. 4) stores only unique sets and each node maps to a candidate pattern comprising all the events from the root to the current node. B i,j is the concerned sub-branch (i indicates the tree level and j the branch counter), C represents the aggregate metric violation, while the pair S(B i,j , C) is the frequency of B i,j set in critical intervals. A candidate set's negation means that either of the included events does not appear. For instance, for the pattern {e 1 , e 2 , e 4 }, the following negation definition exists: ¬{e 1 , e 2 , e 4 } ≡ ¬e 1 ∨ ¬e 2 ∨ ¬e 4 . A negated event means that another or no event appears in the specific pattern's position. Frequencies S(B i,j , C) and S(¬B i,j , ¬C) are used to determine an association rule. The latter invigorates the association rule under consideration, as the concurrent absence of a pattern and the considered violation event also interrelates the root and cause of the association rule. Consequently, to determine such a rule, the sum of frequencies invigorating the association rule should be greater than the sum of frequencies weakening it (lines 21-23 ). The algorithm's time complexity depends on the event stream size n, the average tree level size g and the tree branches b. Thus, as the algorithm requires g*b (i.e., approximately the cardinality of the powersets) iterations on the event stream, its complexity is O(n * b * g). This means that the powerset tree is extensively traversed to discover the association rules. Fig. 5 clarifies the way intervals are processed to identify patterns for the average DeviceConfig average execution time violations (i.e., violation of E 3 event). The event stream comprises 35 events (after event filtering) of Section 2's 6 metrics. Each interval's powerset sets (figure's connected events) are processed to determine association rules. Thus, the event stream is split into 5 intervals: 3 critical (c mark on interval's upper right corner) and 2 non-critical (nc mark on interval's upper right corner). For critical intervals, the subset before the last raw critical DeviceConfig SaaS execution time event is considered, while for non-critical ones the whole interval. The algorithm discovers two patterns and extracts the association rules: (i) {e 1 , e 2 , e 4 → E3} and (ii) {e 4 , e 6 → E3}.

Evaluation

This section experimentally evaluates the algorithm's performance and accuracy, in order to optimize the definition of the aggregate metric (i.e., its optimal The main task is to discover patterns causing DeviceConfig SaaS execution time violations (i.e., violations of E 3 ). The experiments were performed on a machine with quad-core CPU 2.6GhZ, 8GB RAM and Mac OS X operating system. The first experiment evaluates the algorithm's raw relevant and absolute accuracy. The former considers only the five known patterns, while the latter additionally considers their sub-patterns, as they can also drive proactive adaptation. The algorithm's precision and recall is measured while fluctuating the interval size from 4 to 20 events. Fig. 6a shows that relevant precision is 1 for small intervals and falls while increasing the interval size, while absolute precision fluctuates similarly at lower levels (as more irrelevant sub-patterns are discovered). The precision starts to fall over 8-size intervals, i.e., above the double of the longest pattern (4 events). Fig. 6b shows that the algorithm's absolute recall is 1 for all considered interval sizes, except for 4-size and 6-size intervals, where it fails to discover two and one 4-size patterns respectively, due to interval overlapping. Moreover, relevant recall is always 1, as the discovered sub-patterns compensate the "lost" relevant patterns (for 4-and 6-size intervals), as they also map to adaptation strategies addressing the whole pattern. Considering these accuracy results, the optimal definition of metric E 3 is to measure it in intervals containing in average 8 events. Thus, every aggregate metric's definition can be adjusted, enhancing the proactive adaptation of any SBA.

The second experiment evaluates the algorithm's execution time, based on the dataset and interval size. The results in Fig. 7 show that the algorithm's execution time linearly increases with an increasing dataset size, as expected. Larger intervals seem to hurt more the algorithm's performance, due to higher b*g products. However, such execution time is acceptable, as this is an offline algorithm not affecting the overall framework's performance. Furthermore, the results in Fig. 7b reveal a changing relation between execution time and interval size; for larger intervals, it increases with a burst over 20-size intervals, due to rapid increase of b*g (740 (b=148, g=5) for 30-size interval compared to 92 (b=23, g=4) for the 25-size and 48 (b=12, g=4) for the 20-size intervals), posed by the high increase of the considered unique sets.

Related Work

The mining of significant patterns within event stream areas have recently attracted many researchers. Most of these approaches are predominantly based on the apriori algorithm [START_REF] Agrawal | Fast algorithms for mining association rules in large databases[END_REF], producing an association rules set between items of large databases, based on a minimum support (minsup). Other approaches propose variations of these algorithms, focusing on performance [START_REF] Bettini | Discovering frequent event patterns with multiple granularities in time sequences[END_REF] and accuracy [START_REF] Hellerstein | Discovering actionable patterns in event data[END_REF] optimization. All such approaches suffer from many issues stemming from the difficulty in determining the optimal minsup. Contrarily, logic-based approaches exploit inferencing to discover patterns defining respective association rules. In [START_REF] Sim | Logic-based pattern discovery[END_REF] a pattern discovery approach is proposed mapping logical equivalences based on propositional logic. In particular, a rule mining framework is introduced, generating coherent rules for a given dataset that do not require setting an arbitrary minsup. [START_REF] Artikis | Run-time composite event recognition[END_REF] proposes an event calculus (EC) dialect for efficient run-time recognition that is scalable to large data streams.

Concerning IaaS modeling, some well-established approaches, such as the OASIS Cloud Application Management for Platforms (CAMP) specification (www.oasis-open.org), focus on modeling the most generic infrastructure components. At the PaaS layer, the mOSAIC EU Project's (www.mosaic-cloud.eu) entity ontology stands out as a solution for improving interoperability among existing Cloud solutions, platforms and services. Finally, SaaS layer modeling has been widely influenced by the service computing, such as the models introduced within the S-Cube EU project (www.s-cube-network.eu).

Compared to the related work, the main benefits of our approach are the following. First, we propose a component meta-model able to describe the components of multi-cloud SBA along with their interrelationships. The models complying to this meta-model assist in identifying correct event patterns by consid-ering only events originating from interrelated components. Second, we propose a logic-based algorithm for discovering event patterns leading to critical events within a monitoring event stream, enabling injecting proactiveness in an SBA system via mapping event patterns to respective adaptation strategies.

Conclusions and Future Work

This paper has presented an approach towards efficiently discovering detrimental event patterns causing critical violations during multi-cloud SBA execution. In particular, a component model is presented, describing SBA components and their interrelationships, that is exploited by a logic-based algorithm discovering event patterns leading to specific metric violations and can be further exploited by any adaptation engine to trigger suitable proactive adaptation actions when detected. For future work, we plan to optimize the pattern discovery algorithm's accuracy and performance and develop a scalability rule mechanism that could semi-automatically map discovered event patterns to suitable adaptation strategies. Finally, we are going to employ new techniques to infer new component dependencies from the current irrelevant discovered patterns.

Fig. 2 :

 2 Fig. 2: Framework's architecture

Fig. 4 :Fig. 5 :

 45 Fig. 4: Powerset tree

Fig. 7 :

 7 Fig. 6: Algorithm's accuracy

we 1 ce 2 ce 4 we 5 we 3 we 6 Fig. 1: Traffic management example Monitoring tools

	(Astro, Cloudwatch, Cloudify, ...)
	TSDB KairosDB	roll-ups assessed raw events	Metric Aggregator Esper	assessed raw events aggregated metrics classification
	queries	discovered patterns		detected patterns
	Pattern Discoverer
	Esper, Drools
		Application Server Special software		Application Server Database Special software
		VM		VM
		Monitoring sensors		Monitoring sensors
		Compute		Compute
		Storage		Storage
		Network		Network

Monitor Manager Adaptation Engine Rule Engine Drools Adaptation Enactment

	NTP server
	Monitoring Engine
	Cloud 1	Cloud 2
		Monitoring tools
	(Astro, Cloudwatch, Cloudify, ...)
	Esper client	Esper client	SBA provider
		Multi-Cloud
		deployment
	synchronized
	raw events
	Assessed raw events
		simple
		adaptation/scalability
		rules
	detected
	patterns
			Model Repository
			Event model
			Component model
	adaptation actions		Adaptation model SLA model

  Model-driven technologies of the Eclipse Modeling Framework (EMF) are exploited to create models complying to this meta-model. The core meta-model is graphically produced in ecore and then used to generate the base domain code. Next, the Connected Data Objects (CDO) technology is used, offering a model repository and a run-time persistence framework, accessible via querying mechanisms (SQL, HQL). For instance, the following SQL query returns the total number of active components included in the VM hosting the Monitor and De-viceConfig services (componentID=7001) and having ID 7026 or 7027 (i.e., the components producing e 1 and e 2 events), in order to identify if both components reside in the same VM and thus affect each other when a violation occurs.

	SELECT COUNT(*)
	FROM (SELECT VM_COMPUTE_LIST
	FROM VM WHERE ComponentID=7001) as computeList
	WHERE componentID IN (7026,7027) AND (state = active);

Acknowledgements We thankfully acknowledge the support of the PaaSage (FP7-317715) EU project.


Dominik Wierzbicki

Radosław Debek

Monika Motak

Teresa Grzybek

Maria Elena Gálvez

Patrick Da Costa
email: patrick.da_costa@upmc.fr

Novel Ni-La-Hydrotalcite derived catalysts for CO 2 methanation

Keywords: CO 2 methanation, hydrotalcite, nickel, Lanthanum

A series of hydrotalcite-derived mixed oxides containing Ni/Mg/La/Al obtained by thermal decomposition were characterized by XRD, CO 2 -TPD and H 2 -TPR. The results confirm the formation of periclase-like materials, and the addition of lanthanum resulted in the formation of a separate phase. The incorporation of 2 wt.% of lanthanum leads to an increase of the catalytic performance at temperatures from 250 to 300°C with CO 2 conversion of 46.5-75% and CH 4 selectivity of 99-98%. The activity is directly connected with basicity that increases with the incorporation of La into the HT-derived catalysts.

Introduction

The CO 2 concentration increase in atmosphere, which is considered to be one of the anthropogenic causes of global warming, has led to renewed interest in CO 2 hydrogenation (Sabatier reaction). This process offers the possibility of storing off-peak renewable energy, i.e. in the form of water-electrolysis hydrogen, and, at the same time, treating CO 2 as raw material, to produce storable and transportable fuels (methane), or other commodities [1]. This way of producing of gaseous and/or liquid fuels may become an effective method of stabilizing CO 2 emissions, in a global zero-emission closed cycle.

Catalytic CO 2 methanation has been deeply studied using catalysts containing group VIIIB metals (Fe, Ru, Co, Rh, Ir, Ni, Pd, Pt) on different supports (Al 2 O 3 , SiO 2 , ZrO 2 , CeO 2, mixed oxides of Ce-Zr and TiO 2 ) [2]. The catalytic systems containing Ni, Ru and Rh were the most effective [3][4][5][6]. Though much cheaper than Ru and Rh, Ni-based catalysts suffer from deactivation at low temperatures due to the strong interaction of Ni with CO and the formation of mobile carbonyls, which leads to the sintering of the active phase [7,8]. The choice of the support is furthermore important since it may determine the adsorptive properties of the catalytic system and the interaction support-active phase [2]. Acid-basic properties of oxides derived from hydrotalcites (HT) can be tailored for specific catalytic applications such as for CO 2 valorization through dry reforming [9]. However, to date few publications deal with CO 2 methanation over HT-derived catalysts [10,11]. Gabrovska et al.

[10] studied co-precipitated NiAl-HT-based materials with different content of nickel (21, 32 and 42 wt.%) in which the catalytic activity strongly depended on Ni content, reduction and reaction temperatures. He et al. [11] reported that well-dispersed and stable nickel particles could be obtained through the decomposition of Ni-containing HTs, and claimed that this fact together with the existence of strong basic sites resulted in enhanced methanation activity.

It is nowadays well known that lanthanum can modify the redox properties of a catalytic material. In fact, the incorporation of lanthanum into Ni-containing HT-derived catalysts led to a beneficial effect on the nickel dispersion, catalytic activity and suppressed the formation of carbon in dry methane reforming [9]. However, there is no information in the existing literature dealing with the influence of the presence of La in HT-derived catalysts for CO 2 methanation. The aim of this work is thus to study the properties and activity of modified hydrotalcite-like materials containing Ni, La, Al and Mg as prospective catalysts for CO 2 methanation, with low Ni loadings.

Experimental

Synthesis of the materials

Hydrotalcites containing M(III) trivalent and M(II) divalent metals (Al, La, Mg, Ni,) with M(III)/(M(III)+M(II)) molar ratio of 0.25, (Table 1), were prepared through a co-precipitation method at constant pH (from 9.5 to 10). Two aqueous solutions, of respectively the mixed nitrates of the divalent and trivalent metals and of sodium hydroxide (1M), were added dropwise into a flask containing an aqueous solution of sodium carbonate, under vigorous stirring at 65°C and constant pH. The mixture was aged for 24 h at 50°C, then filtered, washed with deionized water and dried at 80°C overnight. The obtained materials were finally calcined at 550°C for 5 h. The nominal (assumed) concentration of the components is listed in Table 1.

Physico-chemical characterization

The HT-derived catalysts were characterized by XRD, TPR and TPD-CO 2 . XRD measurements were carried out using PANalytical-Empyrean diffractometer, equipped with CuK  (λ=1.5406Ǻ) radiation source, within 2θ range from 3 to 90°, (step-size=0.02°/min). Ni crystallite sizes were calculated for the catalysts after reduction and reaction using the Scherrer equation. Temperature programmed reduction (H 2 -TPR) profiles were obtained using BELCAT-M (BEL Japan) apparatus equipped with a thermal conductivity detector (TCD). The calcined materials were first outgassed at 100°C for 2h and then reduced using 5%H 2 /Ar at the heating rate of 7.5°C/min from 100 °C to 900 °C. For each measurement a sample of 60 mg was taken. CO 2 Temperature programmed desorption (CO 2 -TPD) was performed on the same device. The materials were degassed for 2 h at 500°C and then cooled to 80°C. Subsequently a mixture of 10%CO 2 /He was fed for 1h in order to adsorb CO 2 , followed by desorption of weakly adsorbed CO 2 using a flow of He for 15 minutes. In order to measure the evolution of CO 2, the material was heated up under He flow at 10°C/min from 80°C to 900°C. The concentration of evolved CO 2 was measured with a TCD detector.

CO 2 hydrogenation experiments

CO 2 methanation was studied in a tubular quartz reactor heated by an electric furnace.

Temperature was measured and controlled inside the catalytic bed with the aid of a K-type thermocouple. A reactant flow of 100 ml/min (GHSV=12,000 h -1 ) containing H 2 /CO 2 /Ar = 12/3/5 was sent to the reactor. The products were analyzed using an on-line Varian GC4900 micro-chromatograph equipped with a TCD detector. Prior to the reaction the catalysts were reduced in situ at 900°C for 1h under 10% H 2 /Ar. The catalytic activity was then determined from 250 to 450°C. At each temperature the sample was kept for 30 minutes in steady-state operation.

Results and discussion

From the hydrotalcite precursors to the mixed oxides derived materials

Figure 1 shows the diffractograms acquired for the fresh hydrotalcite (a), the hydrotalcitederived catalyst (NiLa4-HT) obtained upon calcination (b), the reduced (c) and the spent (d) HT-derived catalyst. The patterns obtained for fresh HT show the typical reflections of layered-structured hydrotalcites [13]. In the case of the HT containing higher amounts of lanthanum, i.e. NiLa4-HT and NiLa2-HT (not shown), separate phases arising from La 2 (CO 3 ) 2 (OH) 2 and La 2 O 2 CO 3 were as well observed. Upon calcination, XRD patterns evidence the typical reflections of a periclase-like structure at 2θ = 35.3, 43.5 and 63°.

Lanthanum carbonates are as well observed as a separate phase, as well as La 2 O 3 . The reflections corresponding to this isolated lanthanum carbonate phase disappear for the catalysts submitted to reduction in 10% H 2 /Ar. These patterns reveal the existence of a metallic Ni phase. The crystal sizes for such Ni particles are in the range 8-9 nm, see Table 2, similar to those reported in the existing literature for Ni-containing HT-derived catalyst [14].

Crystal sizes remained practically unchanged in the catalysts employed in the methanation reaction, i.e. 8-10 nm crystal size calculated for the spent catalysts. Though the incorporation of only 1 wt.% of lanthanum leads to a slight decrease in total basicity, the amount of basic sites, i.e. sites able to chemisorb CO 2 , generally increases upon La-loading. Moreover, from peak deconvolution it seems that medium strength basic sites are more present in the La-doped HT-derived catalysts, i.e. its concentration increases from 60 µmol/g for Ni-HT to 113 µmol/g and to87 µmol/g, for the catalysts respectively containing 2 and 4 wt.% of La. Let us remark here that the differences between basicity for Ni-HT's containing 1 wt.% and 2,4 wt.% of La might be as well caused by a partial blocking of the basic sites in the mixed oxide hydrotalcite-derived material, upon the introduction of low amounts of lanthanum and its compensation through the formation of new basic sites after incorporation of 2 and 4 wt.% of La. Fig. 3 shows the H 2 -TPR profiles for the calcined HT-derived catalysts. They all exhibit one wide asymmetric peak arising from the reduction of nickel oxide species to metallic Ni° (814-846°C). This higher reduction temperatures vis-à-vis the much lower temperatures expected for the oxidation of either bulk NiO or dispersed NiO crystallites points to the existence of a thermally stable phase of Mg(Ni,Al)O in the form of a solid solution of mixed oxides, and thus to a very strong interaction between the nickel species and the Al-Mg hydrotalcite matrix [9,16]. The addition of La visibly shifts the reduction of Ni-species to lower temperatures, i.e. from 846°C for Ni-HT to 814-821°C for NiLa1-HT and NiLa4-HT, respectively. Additionally, a shoulder appears at ca. 690°C for NiLa2-HT and NiLa4-HT (2 and 4 wt.% of La, respectively), which can be assigned to isolated and more weakly bonded NiO species. Moreover, for NiLa2-HT an additional weak peak can be as well observed at temperatures ca. 400 and 490°C that may correspond to bigger bulk NiO crystallites. Lucredio et al. [17] showed that low amounts of lanthanum resulted in further stabilization of the Niphase and thus increased reduction temperatures, at higher La-loadings, however, TPR reduction temperature decreased, pointing to weakened interaction between Ni-species and the hydrotalcite matrix [18]. Nickel-containing materials obtained upon calcination of hydrotalcites form homogenous mixed oxides (periclase structure), where NiO and MgO interactions are very strong, resulting in the need of harsh reduction conditions, in contrast to Ni impregnated supports, where the nickel is more likely to be deposited on the surface, and then the reducibility may be expected to be much higher than for hydrotalcite systems. The obtained H 2 -TPR results are in good agreement with literature reports [11].

Basicity and active sites

Catalytic activity towards CO 2 hydrogenation

The CO 2 conversion measured during the methanation experiments is plotted in Fig. 4, for the different HT-derived catalysts and as a function of reaction temperature. The thicker continuous line represents the CO 2 conversion forecasted by the thermodynamic equilibrium for this reaction. Thermodynamics predicts complete CO 2 conversion at low reaction temperatures, decreasing with increasing temperature, since the other routes start to be favored, such as all the set of reforming reactions, resulting in the formation of undesirable side-products such as CO. At 250°C, the CO 2 conversions measured in the presence of the different HT-derived catalysts are still far away from the maximal thermodynamic conversion limit. The highest conversions are obtained for the catalysts containing 2 and 4 wt.% of lanthanum, i.e. 46.5% and 46% for NiLa2-HT and NiLa4-HT, respectively. Activity towards CO 2 methanation is thus promoted in the presence of La, as a consequence of increased basicity, concretely in terms of medium strength basic sites, and looser interaction of Nispecies and the Al-Mg hydrotalcite matrix, resulting in enhanced reducibility. Indeed, the difference in catalytic activity is in good agreement with much higher basicity shown for catalysts containing 2 and 4 wt.% of La. As observed by XRD, La forms separate phases and is not introduced into the hydrotalcite structure. Therefore, the changes in basicity are a consequence of two opposing effects: partial blockage of hydrotalcites basic sites by lanthanum oxide and the introduction of new basic sites by the latter. For the catalyst with 1% La, the decrease of hydrotalcite basic sites could not be compensated (due to low amount of new added basic sites), in contrast to HTLa2 and HTLa4, where the overall effect was positive. As reported by Pan et al. [19] the reaction of CO 2 methanation on nickel containing catalysts involves (i) H 2 dissociative adsorption on metallic nickel and (ii) CO 2 adsorption on basic sites, thus making it necessary to find an optimum composition of the catalysts. Pan et al. also suggested that the presence of medium strength basic sites resulted in improved catalytic activity due to the promoted formation of monodentate formate species, which is an active intermediate in methane formation. However, as reaction temperature increases CO 2 conversion converges to similar values independently of the HT-derived catalysts used. At temperatures higher than 400°C, methanation and its side-reactions become temperaturepromoted and the intrinsic features of each catalyst leading to improved performance at lower temperatures are no longer that important. Moreover, at temperatures higher than 400°C, a loss in reaction selectivity can be expected. The selectivity towards methane production measured for the different catalysts during the activity tests is plotted in Fig. 5 as a function of temperature. In the low temperature range almost complete selectivity to methane was measured for all the catalysts tested, i.e. 98 to ca. 99% at 250°C. As expected, selectivity slightly decreases with increasing temperature. As expected, selectivity slightly decreases with increasing temperature for samples Ni15, Ni15La2 and Ni15La4, while for the Ni15La1 sample the selectivity towards methane increased from 400°C to 450°C, which is in the range of experimental error. No other product except CO and CH 4 were registered. The selectivities to CO were between ca. 1 and 3% (3% for the most active Ni15La2 at 450 o C). The amounts of registered CO are relatively low, it is rather difficult to discuss a relationship between the selectivity and basicity, or any other property of the studied catalysts. We can only roughly say that, a priori, the samples with the highest amount of basic sites (Ni15La2 and Ni15La4) show the highest and the lowest selectivity towards methane. Let us note here that the catalytic activity was found to remain completely stable after 5h time on stream, without further evolution of basicity and no modification of Ni-crystal size on the spent catalysts (Table 2).

Conclusions

La-promoted Ni-Mg-Al hydrotalcite-derived catalysts were prepared through coprecipitation, characterized and tested in the CO 2 hydrogenation reaction. The introduction of La affected the CO 2 adsorption capacity of the catalysts through the introduction of medium strength basic sites. The presence of La also influenced the interaction of Ni-species with the Mg-Al matrix. In HT-derived catalysts, Ni-species are found commonly in the form of mixed oxides solid solutions together with Mg and Al oxides. Lanthanum increases the reducibility of Ni-species by means of softening the interaction between them and the HT matrix. Both increased basicity, in terms of medium strength basic sites, and increased Ni-reducibility results in much higher activity at low temperatures for such La-promoted HT-derived catalysts.

Fig. 2

 2 Fig. 2 contains the CO 2 -TPD profiles acquired for the different HT-derived catalysts after

Acknowledgements

R. Dębek, M. Motak and T. Grzybek would like to acknowledge AGH grant 11.11.210.213 and French Embassy in Poland.


Tobias Rauter
email: tobias.rauter@tugraz.at

Integrity of Distributed Control Systems

Security is a vital property of SCADA systems, especially in critical infrastructure. In this work we focus on the integrity of the overall distributed control system. First, we classify properties that enable the verification and proof of the integrity of different subsystems. Based on this classification, we show how we protect the overall system's integrity at different system levels and which implications arise for the development and manufacturing stage of control devices by applying the proposed approaches. Based on an exemplary system in the domain of hydro-electric power plants, we also show practical examples how we plan to apply our work in real world.

I. INTRODUCTION

The growth of the renewable energy sector has a high impact on the technology of hydropower plant unit control systems [START_REF] Liserre | Future Energy Systems: Integrating Renewable Energy Sources into the Smart Power Grid Through Industrial Electronics[END_REF]. Nowadays, these have to react on power grid changes in time to achieve overall grid stability. As a consequence, control devices (depending on the provided functionality, they are also referred to as Remote Terminal Unit (RTU) or Programmable Logic Controller (PLC)) in single power plants, as well as control devices of different power plants have to cooperate in order to achieve the system-wide control goal. These requirements lead to networks of small, embedded control devices and heavyweight Supervisory Control and Data Acquisition (SCADA) servers and clients. At the same time, these power plants represent critical infrastructures that have to be protected against security attacks that raised lately [START_REF] Miller | A survey SCADA of and critical infrastructure incidents[END_REF].

Fig. 1 shows one exemplary architecture of such systems. One central SCADA client is used to supervise RTUs of different plants at different sites. The RTUs are the actual control devices that execute the control strategy and interface with the environment (i.e., communicate with sensors and actuators). Since the control strategy could be distributed, the RTUs have to communicate directly with each other. Technically, RTUs often comprise different hardware components, where each one is in charge for a specific functionality. For example, the device consists of a main controller that executes the control strategy and communicates with the outer world. However, in order to access sensors and actuators, an additional I/O device is connected via an internal bus system. This I/O device usually contains its own, lightweight CPU and provides the actual physical interface to connect peripherals.

While recent work in the SCADA field is focusing on the security properties of the servers (e.g., [START_REF] Tantillo | Toward Survivable Intrusion-Tolerant Open-Source SCADA[END_REF]), we focus on security properties of the RTUs and their interactions. A lot of research has been done to improve the authentication of devices and the integrity and confidentiality of their communication. However, even if a communication partner is authenticated, how is it possible to ensure that it can be trusted? Fig. 1. Overview of an exemplary SCADA system which is used to control power plants at different locations According to the Trusted Computing Group (TCG), a trusted system is a 'device that will behave in a particular manner for a specific purpose' [START_REF] Tcg | Trusted Computing Group[END_REF]. Similarly, the integrity property of a computer system is seen as the guarantee, that the system will perform as intended by the creator [START_REF] Biba | Integrity Considerations for Secure Computer Systems[END_REF]. Therefore, one can trust a system if we trust the initial system state and we can ensure that its integrity is not violated.

In this work, we examine the question of how integrity can be ensured in such distributed systems. Since integrity cannot be 'measured' directly, other properties that reflect the integrity of sub-systems have to be found. These properties have to be measureable and verifiable. The first part of our contribution is a classification on how integrity can be verified (locally and remotely) and what types of properties could be used (static and dynamic) based on patterns. As a next step, we identify such properties for distributed control systems on different system levels, such as bus-level, device-level and compoundlevel. On bus-level, we plan to use statistical analysis of sensor data, which has already been done in previous work. On device level, we propose a new attestation method that uses privileges of software components as integrity property to overcome common problems of integrity attestation. For compound-level, we plan to exploit the distributed nature of control devices that work in the same environment to verify whether specific behaviours of single subsystems reflect an ©2015 IEEE integer subsystem state. Additionally, we propose methodologies and tools for the development and manufacturing process that enable the integrity checks in the further life-cycle. In order to simplify the integrity checks, the system has to be carefully designed, especially concerning the principle of least privilege and privilege separation. Moreover, a unified production process for all types of devices and components enables a secure provisioning of secrets like private keys that have to be in place later on.

Section II describes the pattern-based classification. In Section III, how we want to ensure the overalls system integrity and which properties we use for different system levels. Section IV shows supportive methods we propose for earlier parts of the system lifecycle (development and manufacturing) and Section V sums up the work and describes future directions.

II. CLASSIFICATION OF INTEGRITY VERIFICATION

There are different attributes to classify integrity checks in distributed systems. During our research, we investigated two dimensions concerning the entity of verification and the frequency of the measurements..

Regarding the verification entity, we identified two patterns [START_REF] Rauter | Patterns for Software Integrtiy Protection[END_REF]. INTEGRITY PROTECTION adds the ability to enforce a policy that protects the system from behaviour that would violate its integrity. INTEGRITY ATTESTATION (also known as 'Remote Attestation') is used to prove the system's integrity state to a remote system. In both cases, the integrity of a system A is 'measured' somehow. For INTEGRITY PROTECTION implementations, these measurements are checked against a policy on the same system. The system A thus enforces its own integrity. On the other hand, INTEGRITY ATTESTATION implementations send this measurements to a remote system B. In this case, B verifies the integrity of A by checking whether the measurements comply to B's policy for A. In this case, B verifies the integrity of A. This can be done periodically or event-based (for example prior to normal communication).

However, integrity cannot be 'measured' directly. Therefore, one has to find system properties that reflect the integrity of the overall system when checked against a policy (e.g., the hash of an executed software module has to be signed by the software vendor). In this work, we denote such properties as 'integrity properties'. Using such properties is only an approximation because they always only reflect a sub-set of the overall system integrity. They thus have to be chosen carefully in order to fit given integrity requirements.

Similarly to the verification entity, we plan to document two patterns, STATIC INTEGRITY PROPERTIES and DYNAMIC INTEGRITY PROPERTIES, as classification regarding their measurement frequency. STATIC INTEGRITY PROPERTIES do not change during execution of the system and are thus only measured once (i.e., before the execution of the measured subsystem). One example would be the hash of an executed binary that can be verified to detect malicious modifications of the executable. DYNAMIC INTEGRITY PROPERTIES reflect the behavior during execution of the system or usage of the data. Therefore, they have to be measured (and also verified) continuously. The access to critical system functions is one example of such properties.

Based on these patterns, we can classify integrity verification for distributed systems into 4 segments. Secure Boot, for example is INTEGRITY PROTECTION based on STATIC IN-TEGRITY PROPERTIES. Another example is remote attestation with Integrity Measurement Architecture (IMA) [START_REF] Sailer | Design and implementation of a TCG-based integrity measurement architecture[END_REF]. Here, IN-TEGRITY ATTESTATION based on STATIC INTEGRITY PROP-ERTIES is used.

This classification is used as foundation for further discussions of integrity properties in our work. The pattern-based description enables a common language and also supports decisions whether specific properties with specific verification points fulfill our integrity requirements.

III. INTEGRITY PROPERTIES

As illustrated in Fig. 1, we consider three different levels:

The bus level consist of sensors and actuators, as well as the physical world. The second level is the device level. Here, the interaction of different RTUs and components inside one RTU are considered. We thus consider point-to-point connections between devices at one side and connections between different sites. However, at the compound-level, additional examinations are required. Even if the direct communication partner of the other site is trusted, the system has to ensure that the complete remote network of systems is acting on behalf of the common control strategy.

In common systems, an attacker may be able to gain limited physical access to sensors and actuators, since the facilities are spaciously. Moreover, he may have logical access to the device network but no physical access to the RTUs or SCADA server, since they are protected physically.

We neither consider authentication of the different devices nor security measures on the channels (such as integrity and confidentiality protection) here. We assume that proper measures are in place. Therefore we have to ensure that the required secrets (such as private keys and certificates) are distributed securely. Moreover, we do not consider the bus level in this work. A lot of research has been done in the field of data veracity [START_REF] Krotofil | The Process Matters : Ensuring Data Veracity in Cyber-Physical Systems[END_REF]. Here, the trustworthiness of sensor data is ensured based on the correlation entropy in a cluster of related sensors. In our work we thus focus on device and compound level.

A. Device Level

As mentioned before, in our real world scenario we have to consider component compositions that form one RTU, as well as the connection between devices at this level. From a security point of view, both types are basically computing platforms that are connected via a network bus (e.g., Ethernet). Therefore, we only consider inter-device communication because the same technologies can be used for the internal components. Fig. 2 shows the basic integrity measures at device level. To achieve INTEGRITY PROTECTION, each device uses secure boot and sandboxing (if applicable). We thus use static (i.e., hash values of the executables) and dynamic (i.e., the behaviour) properties to ensure the integrity. These technologies are well known and state of the art.

However, RTUs also have to verify the integrity of potential communication partners. In today's systems, remote attestation is used to achieve such a verification. One device (prover) proves its integrity by sending a signed representative measurement to another entity (challenger). Similar to secure boot, common methods use hash values (binary measurements) of all files that comprise a device's configuration (e.g., executed programs and their configuration files) to represent the overall integrity (e.g., IMA [START_REF] Sailer | Design and implementation of a TCG-based integrity measurement architecture[END_REF]). The challenger thus has to know a reference hash value of all 'good' executables. Due to the high amount of possible RTU configurations and different versions of single programs, this method is not feasible in distributed control systems. Every time one device is updated, all other devices would have to update their references too.

In order to tackle this problem, we proposed PRIvilege-Based remote Attestation (PRIBA) [START_REF] Rauter | Privilege-Based Remote Attestation: Towards Integrity Assurance for Lightweight Clients[END_REF]: The prover may execute many services that are not of interest for the challenger (e.g., Service 1.1 in Fig. 2). When such a service does not have the privileges or permissions to harm the integrity of the targeted service, the challenger does not have to know a reference measurement. The list of binary measurements is thus reduced to the number of targeted services. Additionally, the prover has to provide a 'measurement' of the privileges of all other services. The challenger checks this measurement against a policy and decides whether the prover's integrity is intact. We have investigated different methods of privilege measurements and propose a simple check for library calls as most efficient way.

However, the implementation of PRIBA raises some challenges. In order to identify and analyze them, we integrated PRIBA into IoTivity, an existing Internet of Things (IoT) communication stack. IoTivity offers a flexibility and multiple platform support, which enables different experiments with low effort. The integration of our method into the actual RTUs is planned later.

In order to implement PRIBA, we had to build a framework [START_REF] Rauter | Thingtegrity: A Scalable Trusted Computing Architecture for Resource Constrained Devices[END_REF]: First, the privilege measurement unit requires 'measureable' accesses to privileged system functions. Therefore, we introduced an API with appropriate access granularity (API calls have to reflect privileges, e.g., access to system files). Furthermore, the system has to ensure, that these measured accesses are not circumvented at runtime. This is ensured by a sandbox. In order to enable a simple integration, we designed the introduced API in a way that enables automated generation of sandbox-policies at service-startup. The privilege-measurement unit is the Root of Trust for Measurement (RTM) for this type of measurements. However, privilege measurements of this component as well as other low-level components cannot be taken. Therefore, we integrated the existing IMA [START_REF] Sailer | Design and implementation of a TCG-based integrity measurement architecture[END_REF] implementation for Linux into our framework to enable binary-measurements.

For verification, we introduced a simple policy that enables the decision whether the communication partner's integrity is intact. However, through the IMA-based measurements, the reference configuration lists may be too big and too dynamic to be handled in a network of constrained devices. Therefore, we also implemented a property-based attestation scheme, where measurement lists are signed by Trusted Third Parties (TPP). Additionally, we use the authentication mechanisms of the underlying communication protocol to integrate authentication of the device hardware.

To recap, we combined concepts from binary-, propertyand privilege-remote attestation and integrated it into IoTivity. The architecture is transparent and hides the complexity of remote attestation from the overlying application. Additionally, we provide a testbed that enables the investigation of further attestable properties for future devices and systems. We showed that the architecture enables a simplified bootstrapping of trusted environments. Compared to traditional remote attestation systems, the maintainability and scalability of the trusted relations is improved. This is achieved by reducing the complexity of configuration measurements. This reduces the memory and communication overhead significantly for systems with a high number of services or devices.

B. Compound Level

While the checks on device level verify the integrity of the device's configuration, we also have to ensure the integrity of control decisions. Recent studies have shown that one effective attack vector is to get logical access to the control clients and perform malicious actions [START_REF]Electricity Information Sharing and Analysis Center[END_REF]. While such attacks have to be prevented in the infrastructure of the plant operators, we plan to exploit the distributed nature of the system to verify at least some integrity properties of control commands.

One example in the domain of hydro-electric power plants is shown in Fig. 3: An adversary has access to the SCADA client and tries to perform a command with potentially enormous impact (e.g., open the gates to flood a valley). However, before executing the command, the control system gathers information from a third party. In this case, it may ask other downstream plants about their water level. Only if their level is low enough to compensate the released water, the command is executed and the gates are opened.

In contrast to other security protections, such a system has to be configured by domain experts, not security experts. They map domain properties to DYNAMIC INTEGRITY PROPERTIES that are used for INTEGRITY ATTESTATION. Therefore, we plan to introduce a Domain Specific Language (DSL) that enables domain experts to formulate and analyze different policies for their specific use-cases.

IV. LIFECYCLE SUPPORT

The proposed approaches raise requirements for the development and production phase of the system. In order to ensure Since all of the proposed methods rely on asymmetric cryptography for authentication and message integrity verification, we have to provide a process that securely distributes secrets such as private keys to a variety of devices. Here, two main challenges exist: First, even the manufacturer may be (partly) compromised. We thus have to ensure that the access to private key material is as hard as possible during the production process. Moreover, a high number of different and customized devices has to be built and provided with key materials. Therefore, we plan to introduce a model-based production and test system that enables an easy adoption of a secure provisioning process to the variety of produced devices.

V. ONGOING ACTIVITIES AND FUTURE WORK

In summary, we plan to investigate properties that reflect the integrity of distributed control systems at different system levels. Moreover, we want to use the identified properties to integrate integrity verification into actual control devices used in hydro-electric power plants. We already finished a classification scheme for such properties and identified software privileges as property that enables remote attestation in our system.

As a next step, we want to finish the automated privilege separation process and investigate how to find optimal positions of filter components based on the dataflow graph. Moreover, based on the already finished implementation of our production tool, we have to analyze different approaches for the provisioning-approach.

The second big workpackage is the analysis of the compound-level integrity properties. Here, we have to investigate what kind of policies have to be formulated and provide a DSL that enables their generation. Moreover, we have to provide a framework that enforces the policies and examine whether the proposed approach is feasible in terms of communication and time overhead.

Finally, we plan to integrate a proof-of-concept implementation into a demonstrator for next-generation control systems that enables run-time reconfiguration of the system based on the identified integrity violations [START_REF] Höller | Poster: Towards a Secure, Resilient , and Distributed Infrastructure for Hydropower Plant Unit Control[END_REF].

Compound Level

their feasibility, we have to provide supportive methodologies and tools for these lifecyle phases.

A. Support Separation of Privilege

An efficient implementation of PRIBA is only possible, when the different components and services running on a system are separated as strictly as possible. Therefore we plan to help to automate the process of privilege separation in early system design phases.

As a first step, we proposed a metric that quantifies software components by the assets they are able to access [START_REF] Rauter | Asset-Centric Security Risk Assessment of Software Components[END_REF]. Based on a component model of the software architecture, it is possible to identify trust domains and add filter components that split these domains. We show how the integration of the methodology into the development process of a distributed manufacturing system helped us to identify critical sections (i.e., components whose vulnerabilities may enable threats against important assets), to reduce attack surface, to find isolation domains and to implement security measures at the right places.

Based the data-flow flow graph and the information, which components have to access which assets, we plan to automated the process of finding the optimal position of filter components and thus minimizing the size of high-privilege trust domains. B. Support for the Provisioning Process


P Mallet

F Varchon

C Naud

L Magaud

C Berger

J.-Y Veuillen

Electron states of mono-and bilayer graphene on SiC probed by STM

Keywords: numbers: 73.20.-r, 68.37.Ef, 72.10.Fk

We present a scanning tunneling microscopy (STM) study of a gently-graphitized 6H-SiC(0001) surface in ultra high vacuum. From an analysis of atomic scale images, we identify two different kinds of terraces, which we unambiguously attribute to mono-and bilayer graphene capping a C-rich interface. At low temperature, both terraces show ( √ 3 × √ 3) quantum interferences generated by static impurities. Such interferences are a fingerprint of π-like states close to the Fermi level. We conclude that the metallic states of the first graphene layer are almost unperturbed by the underlying interface, in agreement with recent photoemission experiments (A. Bostwick et al., Nature Physics 3, 36 (2007)).

Although the first band structure calculation of graphene (one sp 2 bonded carbon layer) has been performed almost 60 years ago [1], the experimental proof of the remarkable electron properties of this system has been reported only recently. In particular, the predicted Dirac character of graphene fermions close to the Fermi level (E F ) has been shown, giving rise to anomalous integer quantum hall effect and phase shifted Shubnikov de Hass oscillations [2,3,4]. For these pioneering experiments, ingenious techniques were applied to isolate graphene layers, either by graphite exfoliation [2,3] or by graphitization of SiC [4,5].

For both methods, decoupling of the graphene wave functions from the neighboring environment is a fundamental issue. In graphitized SiC surfaces, the graphene layer(s) is (are) separated from the bulk by a carbon rich interlayer which is of primary importance. Very recently, Angle-resolved Photoemission Spectroscopy (ARPES) measurements were reported on both bilayer and monolayer graphene obtained on a graphitized n-type doped SiC(0001) substrate [6,7]. For the graphene monolayer, the Dirac-like character of carriers was evidenced from the linear dispersion close to the Dirac point (the point were hole and electron bands touch each other), and many-body interactions in this two-dimensional (2D) system could be studied [7]. This is a clear demonstration that the C rich interface has an almost negligible influence on the surface Dirac-like carriers, as previously suggested [4,5,8]. Apart from electron doping of the graphene layer due to charge transfer from the bulk, the conduction states of this system can be considered as those of an almost free-standing graphene sheet [7].

Scanning Tunneling Microscopy (STM) is a powerful technique for studying surface (quasi) 2D states at the atomic scale [9,10,11]. However, no direct STM investigation of the graphene low energy states has been reported. This technique has been used to characterize the surface morphology down to atomic scale for different stages of the graphitization of SiC(0001) [4,12,13,14].

Interestingly high bias images of areas with one graphene monolayer shown in references [4,12,13] are often dominated by a strong contrast related to the interface. This might be interpreted as an evidence of a strong interaction between interface states and surface states, in apparent contradiction with ARPES results of Ref. [7]. A second issue is related to the exact number of graphene layers below the STM tip. In particular, a clear fingerprint of the single graphene layer has not been demonstrated. This point must be overstepped for future STM investigations of the unique electron properties of graphene.

In this letter, we present an STM study of the initial stages of graphitization of a 6H-SiC(0001) substrate. Starting with the precursor C rich phase, the so-called (6 √ 3 × 6 √ 3) reconstruction, the sample is annealed to promote the synthesis of a few graphene layers. The surface becomes metallic, as shown by low bias STM images at T = 45K which are routinely achieved. From the analysis of the STM contrast at atomic scale, two different phases are identified, which are attributed to single and double graphene layer. For both phases, quantum interferences are found in the vicinity of impurities, leading to a ( √ 3 × √ 3)R30 • superstructure with respect to the graphene (1×1) lattice. Such interferences originate from intervalley coupling of graphene (graphite) π-like states. Our atomic scale investigation demonstrates that the metallic states of the single graphene layer are essentially not affected by underlying interface states.

The sample preparation was done in ultra high vacuum, with low energy electron diffraction (LEED) and Auger spectroscopy, following the procedure of Forbeaux et al [5]. A n-type (nitrogen 1 × 10 18 cm -3 ) 6H-SiC(0001) (i.e. Si terminated) substrate was first heated at 900 • C under a low Si flux, producing a (3 × 3) Si rich phase. Successive annealings at increasing temperatures (from 900 to 1100 • C) led first to a ( √ 3 × √ 3)R30 • (R3) phase, then to a C-rich phase with a (6

√ 3 × 6 √ 3)R30 • (6R3) reconstruction.
As reported in [12,14], R3 spots, which initially coexist with the 6R3 spots in the LEED pattern, disappear with further annealings. The pattern shown in Fig. 1 (a), obtained with a primary energy of 109 eV, exhibits SiC(0001) (1×1) spots surrounded by hexagonal 6×6 spots (SiC-6×6 in the following), and also faint 6R3 spots.

An STM image of this surface, recorded at 45K and at sample bias -2.0 V, is shown in Fig. 1 (b). It is similar to occupied states-images of the carbon nanomesh of Ref. [14], and to some images of Ref. [12,13]. The honeycomb structure close to a SiC-6×6 is related to the 6R3 reconstruction. It is always observed and has been largely discussed in these references. However, the precise atomic structure and the related electron properties of the actual reconstruction are far from fully understood. As shown in Ref. [14], the large corrugation found on the terraces is not of electronic origin. The authors have suggested that the whole surface is covered by tiny graphene-like carbon islands, self-organized to form the honeycomb structures, with part of C atoms forming covalent bonds with Si atoms [14]. However no atomic resolution has been achieved on this surface to our knowledge, so that there is no direct evidence of such local graphene-like structure. Additionally, ARPES measurements have identified σ-bands related to graphitic sp 2 bonded carbon, but have pointed out the lack of π-like bands in the vicinity of E F [15]. We note that STM images at low bias are not achievable, neither at room temperature nor at 45K. This points to a non metallic character of the surface (the substrate is insulating at 45K), which implies that the first C rich layer has no graphene-like electron properties close to E F .

In the following, we study the same sample after a subsequent annealing at 1300-1350 • C during 8 mn. The C:Si Auger ratio does not exceed 2, indicating that only a few C layers are present onto the surface. As shown in Fig. 1 (c), the surface layers have the lattice periodicity of a graphene sheet: pronounced spots of the (1×1) graphene lattice are found in the LEED pattern, in addition with the SiC related spots. STM images of large areas, such as Fig. 1 (d), reveal terraces with a periodic superstructure, the lattice parameter of which corresponds to that of the SiC-6×6 shown in Fig. 1 (b). Therefore, this superstructure is induced by the C-rich interface lying just below the graphene sheets. Surprisingly, we find that the corrugation of this superstructure is not the same for all terraces. This is demonstrated in the lower part of Fig. 1 (d), where the image has been derivated. The central terrace (labelled M) exhibits a higher corrugation than the other terraces (labelled B), with a factor between 3 to 5 depending on the sample bias. We have checked that most of the terraces studied on this sample are either of M or B type (their identification is made easy on large scale derivated images).

To elucidate the nature of the two different terraces, we focus on STM images with atomic resolution. Such images are routinely achieved at 45K with sample bias as low as 50 mV, which means that the surface is metallic. Fig. 2 is a panel of typical STM images, at sample bias + 0.2V. For type M terraces shown in Fig. 2 (a-c), images reveal a graphene (1×1) lattice of dark spots (with a measured lattice parameter of 2.4 ± 0.2 Å). The six C atoms surrounding each spot give the same bright signal, which leads to a true honeycomb atomic pattern (symmetric contrast). As quoted above, images of type M terraces such as Fig. 2 (a) are also frequently dominated by features related to the C-rich (6×6) interface, which are superimposed to the graphene (1×1) pattern (see also Fig. 3 (c)). Occasionally, uncontrolled change of the tip apex gives rise to a strong attenuation of this interface contribution. This is illustrated on Fig. 2 (b), where only a smooth SiC-6×6 pattern remains together with the graphene (1×1) lattice. Fig 2 (a) and(b) correspond to the same area and the contrast difference between the two images is only due to a tip apex modification. The honeycomb atomic pattern is not affected by this tip effect.

We compare now a 3D zoom of Fig. 2 (b), shown in Fig. 2 (c), with the equivalent data for a B type terrace (Fig. 2 (d)). Two differences are found between the images. First, the SiC-6×6 superstructure is weaker for terraces B than terraces M. Second, and more important, the atomic pattern observed on B terraces shows an asymmetric contrast: bright spots originate from only A hexagonal graphene unit-cell is depicted on both images. Sample bias was set at +0.2V for all the images. three C atoms out of six of a graphene unit cell. This asymmetric contrast is commonly reported for highly oriented pyrolitic graphite (HOPG) surfaces [16]. The results concerning the symmetric (asymmetric) atomic contrast found on M (B) type terraces are general and robust. Occasionally, unexpected tip modification may lead to puzzling contrasts, as reported for HOPG [17].

Results of Fig. 2 can be interpreted in a very simple manner by attributing type M terraces to monolayer graphene covering the C rich interface. A symmetric atomic contrast has been reported recently for a graphene monolayer on Ir(111) [18]. This is intuitively expected for one single graphene layer that is essentially decoupled from the substrate, since all C atoms of the layer are equivalent. On the other hand, surface C atoms of a graphene bilayer with AB stacking become inequivalent, as in HOPG. The B terrace corresponds to bilayer graphene, since the graphitization of the SiC(0001) surface is a layer by layer process [13].

We attribute terrace M to one graphene layer also from the analysis of the contribution of the C-rich interface layer to the STM images. As seen above, the corresponding corrugation is weaker for terraces B than M type. Having a closer look to images of M terraces, we find that atomic details of the interface can often be distinguished "through" the honeycomb atomic pattern (Fig. 2 (a) and 3 (c)). This observation can also be found in previous reports on graphitized SiC [4,12,13], on ar-eas attributed to only one single graphene layer. Our interpretation of such contrast is the following: for one graphene monolayer and at low bias, we expect the tip to probe graphene metallic states but also possible states located just below the surface, namely at the C-rich interface. This is indeed possible due to the peculiar shape of the graphene Fermi surface, where only high momentum 2D states exist. In that case, tunneling between the tip and the interface will occur for electrons having wave vector with small parallel component k // , through the graphene layer which has no small k // available. This tunneling process is hindered in the case of a graphene bilayer, because of the increased tip-interface distance (∼3.5 Å, i.e. a graphite interlayer distance).

Our interpretation for the strong interface STM contrast on terraces M requires interface states (below the single graphene layer) close to E F . From ARPES [7] and Momentum-resolved Inverse Photoemission Spectroscopy (KRIPES) [5], it appears that the π-like bands of the graphene monolayer on 6H-SiC(0001) are essentially not affected by any interface states. Recent density functional theory calculations show that remaining dangling bonds of the complex carbon interface give rise to interface states, which however preserve the Dirac dispersion of the first graphene layer [8]. Confirmation of a weak interaction between such interface states and the metallic states of the surface is also shown on Fig. 2 (c), in which the graphene lattice appears almost perfect at the atomic scale. The remaining tiny SiC-6×6 modulation is probably a real deformation of the surface layer, and apparently has no incidence on the surface electron properties close to E F [7].

In the last part of this letter, we focus on the character of the metallic states probed either on M or B terraces. For that purpose, we use the STM tip as a local probe of the Local Density of States (LDOS) at the vicinity of static defects. Some impurities (of unknown nature) are located on top of the surface (they eventually can be swept by the STM tip). An impurity on a B type terrace (graphene bilayer) is shown on Fig. 3 (a). The sample voltage was fixed at -0.1 V. Superimposed to the (1×1) atomic lattice, a ( √ 3 × √ 3)R30 • (R3) superstructure surrounds the impurity, with a lateral extension of ∼ 5 nm. The corresponding FFT is shown on Fig. 3 (b), exhibiting the (1×1) and the R3 spots. The R3 superstructure is commonly found at many impurities of B type terraces, for positive or negative sample bias as low as 10 mV. For M type terraces (graphene monolayer), the R3 superstructure is much more difficult to identify. The main reason is that only very few effective impurities (i.e. generating R3 superstructure) are identified on M terraces. Moreover, their observations are made difficult due to the strong corrugation generated by the interface. Image of Fig. 3 (c), recorded at sample bias -0.5V, shows evidence of such an R3 superstructure, but the impurity generating this pattern does not appear clearly on the image. The R3 pattern is also found on low bias images for this terrace (not shown). Importantly, interface states dominating the contrast on most images of terraces M do not induce any R3 pattern (see. The R3 superstructure around impurities has been reported for HOPG graphite surfaces [19,20], and also for one single graphene layer on Ir(111) [21]. This pattern is related to quantum interferences (QI) of π-like states scattered by an impurity, as illustrated in Fig. 3 (d). We have plotted a schematic Fermi surface (FS) of a lightly n-doped graphene monolayer (this picture is also valid for graphene bilayer). The FS consists in circular tiny pockets around K symmetry points of the graphene Brillouin zone. Scattering by an impurity between a state -→ k 1 and a state -→ k 2 of two adjacent pockets leads to LDOS spatial modulation with wave vector -→ q = -→ k 2 --→ k 1 , i.e. -→ q ≃ -→ ΓK 3 for states depicted in Fig. 3 (d). The hexagonal symmetry of the FS leads to the R3 modulation in the LDOS, which is essentially recovered in constant current STM images of Fig. 3 (a) and 3 (c) [START_REF]Constant current images at low bias can be approximated to images of the LDOS at EF , given our limited instrumental resolution and the very high dispersion[END_REF].

The observation of the R3 pattern at impurities of terraces M or B demonstrates that the STM tip probes graphene π-like states on the surface, and that such states are essentially not altered by interface or substrate states, as shown by ARPES [6,7]. To our knowledge, this is the first report of R3 QI on a single graphene monolayer on an insulating substrate. As seen above, the R3 pattern is a proof of intervalley scattering, which is a key issue for transport properties in graphene. In particular, it should play a role in the quantum corrections to the electrical conductivity, with subtle effects since adjacent valley are nonequivalent in graphene [START_REF] Suzuura | [END_REF]24].

In conclusion, we studied the local electron properties of graphene monolayer and bilayer grown on a SiC substrate. STM allows a clear identification of the two systems and confirms the effective electron decoupling between the graphene layers and the substrate. Furthermore, STM offers the opportunity to probe scattering processes at impurities, consistent with the expected shape of the mono-and bilayer graphene Fermi surface.

FIG. 1 :

 1 FIG. 1: (color online) (a) 109 eV LEED pattern of the 6H-SiC(0001) 6R3 reconstruction. (b) 40 × 40 nm 2 STM image at 45 K of the same surface, exhibiting the carbon nanomesh phase [14]. Sample bias: -2.0 V. Inset: a 5×5 nm 2 zoom of the central terrace. (c,d) equivalent data of (a,b) after the last annealing step. (c) the dashed arrow indicates one of the graphene (1×1) spots. (d) The bottom part of the image is derivated to highlight the different corrugation between terraces M and B. Sample bias: +0.5 V.

FIG. 2 :

 2 FIG. 2: (color online) (a-b) 5.6 × 5.6 nm 2 STM images of the same area of an M type terrace, with an unexpected tip change between the two images. (c-d) 4 × 4 nm 2 3D view of an M-monolayer (c) and a B-bilayer graphene (d) terrace. A hexagonal graphene unit-cell is depicted on both images. Sample bias was set at +0.2V for all the images.

FIG. 3 :

 3 FIG. 3: (color online) (a) Impurity-induced quantum interferences on bilayer graphene. Image size: 7 ×7 nm 2 , sample bias: -0.1V. (b) FFT of (a). outer spots: (1x1) atomic lattice, inner spots: R3 superstructure. (c) QI on monolayer graphene. Image size 7 ×7 nm 2 , sample bias: -0.5V (d) Illustration of intervalley coupling for graphene π states at the Fermi level. Figures (a) and (c) were obtained at T = 45K.

Fig 2 .

 2 (a) and 3. (c)), which supports once again an efficient decoupling of the graphene layer.

The authors thank Didier Mayou, Valerio Olevano, Laurent Lévy and W.A. de Heer for very fruitful discussions.


Vincent Charbonnier

une réflexion sur la notion de ressource(s)

Le terme de « Ressources », dont on use le plus souvent au pluriel, est aujourd'hui devenu un véritable « mot-valise » dont l'empan et l'usage sémantiques sont très larges (voir par exemple sa page d'homonymie sur Wikipédia [http://fr.wikipedia.org/wiki/Ressources]). Ressource désigne « ce qui peut fournir de quoi satisfaire au besoin, [ce qui peut] améliorer une situation. » L'etymon du terme est d'ailleurs intéressant à noter puisque ce syntagme apparaît d'abord vers 1160, sous la forme de resorse, « secours » puis, au XV e siècle, sous la forme ressourse, « relèvement, rétablissement », participe passé substantivé de resourdre « rejaillir » (dérivé de « sourdre »), et figuré, « se rétablir, se relever », au sens du latin resurgere, dont resourdre est dérivé.

Une ressource est donc génétiquement seconde, elle vient après et en appui à un besoin, plus ou moins formalisé. Dans le registre et le champ de la production et de la diffusion des savoirs, une ressource se présente donc comme une réponse à un besoin de connaissance, c'est-à-dire comme une ressource d'information. Et par information, on désigne « une connaissance inscrite (enregistrée) sous forme écrite (imprimée ou numérisée) orale ou audiovisuelle », comportant « un élément de sens » (Le Coadic, 1994, p. 7) dans le but de sa transmission » à un ou plusieurs autres individu(s) 1 .

Autrement dit, les ressources d'information constituent des documents, c'est-à-dire, des « ensemble[s] cohérent[s] et fini[s] d'informations structurées et lisibles ; à usage défini quel qu'en soit le support » (Roux-Fouillet, 2004, p. 65). Plus précisément, pour qu'un ensemble d'informations soit appelée document, cinq éléments sont indispensables : 1/ l'objet « document » contient des informations ; 2/ les informations sont structurées de manière « lisible » par un homme ou une machine ; 3/ il repose sur un support qui est transportable, reproductible et relativement stable ; 4/ le document a une unité en terme de contenu, il est fini ; 5/ le document a une finalité.

On peut alors repréciser la définition du terme Ressource, en s'appuyant sur celle donnée par le Dictionnaire de l'information (Cacaly et al., 2004, p. 196) : « Dispositif humain ou matériel qui permet d'accéder à des informations factuelles, à des supports de connaissance, à des logiciels de calcul ou à des matériaux didactiques en vue de la réalisation d'études ou de projets ou encore en appui à des actions de formation. Ces ressources peuvent être sous forme traditionnelle ou sous forme électronique ou encore multimédia, disponibles localement, dans un centre de ressources, où à distance. » On est donc reconduit à la vaste question des usages et des usagers puisque toute élaboration de ressources ou de documents inclut nécessairement une réflexion des usages possibles et/ou souhaitables, etc. Sans possibilité de les épuiser -ce qui constituerait une clôture pour le moins problématique -, il est indubitable que les « ressources » déterminent en partie, mais en partie seulement, les usages qui peuvent en être faits. La question des destinataires et de leur différenciation selon leurs champs d'activité ou d'intervention (niveau d'enseignement, champs disciplinaires-académiques, etc.) est également cruciale.

À cet égard, la question de la qualité ou de la pérennité d'une ressource documentaire recèle une difficulté : elle n'est pas seulement une propriété ontologique d'objet (de la ressource donc), mais dépend également et surtout des usages qui en sont ou peuvent en être faits, lesquels ne sont pas tous pensables ni maitrisables a priori.

Il paraît en outre assez fondamental que la qualification des ressources, c'est-à-dire la validation de leur aptitude à satisfaire un/des besoin(s) exprimés ou implicites de la part des « communautés » vi-* Chargé de médiation et d'appui scientifiques, équipe Actualisation continue des connaissances des enseignants de sciences (ACCES), Institut français de l'Éducation, École normale supérieure de Lyon | vincent.charbonnier@ens-lyon.fr 1. Dans cette perspective, je me positionne, théoriquement parlant, en dehors du paradigme généralisant la théorie mathématique de l'information de Shannon (relative à la mesure et à la transmission des signaux électriques) à d'autres champs du savoir, notamment la biologie, où l'information est la mesure de l'organisation d'un système. Cf. Le Coadic, 1994& Escarpit, 1991. sées, réside dans la qualité de leur indexation, dans la précision -c'est-à-dire le raffinement et la complétude -, de thésaurus2 à élaborer, à compléter et peut-être aussi à articuler entre eux. On retrouve ici la question de la normalisation des procédures et de la définition des ressources en fonction des usages et des usagers. Autrement dit, la question de la qualification des ressources pose simultanément celle de leur production. La normalisation des procédures doit aussi se penser comme cela.

À cet égard, elle fait écho à une proposition d'un système d'information documentaire interface figurant dans le Rapport du groupe de réflexion « Ressources » de l'INRP (Trouche, 2010, p. 10 sqq.), lequel me paraît être une épine dorsale d'un développement et d'une qualification des ressources de l'IFÉ et de l'ENS de Lyon.

Quelles articulations ensuite entre élaboration d'un label et production de ressources ? S'agit-il d'élaborer un filtre, au sens d'un tamis, qui sélectionne des ressources, c'est-à-dire de construire ou de s'inscrire dans une logique de distinction ? Ou bien s'agit-il de produire aussi une expertise qui (se) reconduit à la production des ressources, pour les transformer ?

Des questions plus particulières enfin. Comment définir assez précisément la « qualité littéraire ou scientifique élevée » ainsi que la « qualité pédagogique incontestable » des ressources ? Autrement dit, quels critères ? Et comment les construire ? Comment évaluer et qualifier la pérennité et la qualité documentaire ? Sur le plan épistémologique et didactique également, qu'entendre par « collections », « groupes disciplinaires » et « classifications disciplinaires robustes » ?

Ces questions me paraissent être par définition transversales et définissent, a minima, des thèmes de travail communs avec plusieurs composantes de l'établissement, et au-delà, des thématiques et des objets de recherche à construire. Outre les équipes elles-mêmes qui produisent des ressources au sein de l'IFÉ, et de certaines qui produisent des « méta-ressources » comme le service « Veille & analyses », il faut compter le Service commun de la documentation-Bibliothèque de Diderot de Lyon, en y incluant les collègues chargé-e-s de la documentation dans les équipes et les laboratoires ainsi que la Direction des systèmes d'information au point de vue de l'infrastructure matérielle et logicielle.

Assurément, l'intérêt de « labelliser » des ressources possède une fonction politique d'émargement de l'IFÉ et, par métonymie, de promotion de l'ENS de Lyon, par la mise en valeur de son expertise en matière de formation, vis-à-vis de la communauté enseignante lato sensu, du premier degré au supérieur.

Quelques difficultés

Les enseignants déclarent rencontrer des difficultés dans leurs recherches documentaires (empiriques donc) pour un certain nombre de raisons qui sont essentiellement les suivantes : 1/ le temps passé à trouver, à trier et à choisir le bon document ; 2/ le manque d'adéquation des documents à l'enseignement, i. e. un document pertinent et utilisable en classe ; 3/ la profusion des informations et la multiplicité des sources, esquissant en creux le requisit de sites référents ; 4/ la question de la granularité ou du raffinement des contenus informationnels, trop souvent écartelés entre documentation « grand public » et documentation scientifique ; 5/ l'accès payant à l'information. Quant aux ressources pédagogiques en tant que telles, ce sont, en priorité et massivement, des sites académiques3 qui sont utilisés.

Attentes

Elles sont assez multiples finalement et concernent tout d'abord, et de manière assez syncrétique, l'accès à des ressources numériques, qu'elles soient ou non en ligne. Elles ont ensuite trait aux pro-ducteurs et/ou fournisseurs d'informations spécialisées et se manifestent d'abord par une électivité, décroissante, de certains types d'institutions ou d'organismes, soit : recherche scientifique puis recherche en éducation et formation ; réseau de publication et de diffusion de la documentation scolaire (CNDP-SCÉREN) ; médiation scientifique et services communs (universitaires) de documentation. Elles concernent ensuite leurs besoins en termes de développement de compétences dans le domaine de l'information-documentation, que les enseignants identifient comme celui de savoir exploiter l'information dans une perspective pédagogique. Elles concernent enfin les critères de qualité des ressources pédagogiques mises à disposition. On peut distinguer trois types :

1/ pédagogiques, qui se déclinent en : a) pertinence de l'intention pédagogique, par la prise en compte du contexte d'usage des ressources produites (niveau d'enseignement/âge des élèves, type(s) d'activité(s) pour laquelle elles sont conçues) ; b) faisabilité d'application en classes (exploitation pédagogique) ; c) adéquation du contenu aux objectifs pédagogiques et, de manière initiale ; d) cohérence des contenus avec le programme (le « curriculum prescrit ») ; 2/ techniques : ergonomie et design du point de vue des usages pour les enseignants et les élèves et de l'attractivité pour les élèves ;

3/ certification des ressources par des enseignants experts et/ou des scientifiques, tant au plan pédagogique qu'au plan scientifique.

De manière générale, les enseignants insistent sur la nécessité d'une centralisation des ressources en SVT sous la forme de portails ou de plateformes spécialisé(e)s, impliquant une certification pédagogique des ressources numériques, autrement dit, une forme de cohérence cognitive. On note également que les dimensions pédagogique et scientifiques des ressources numériques sont, du point de vue des enseignants de SVT, radicalement indissociables, avec, semble t-il, une petite mais nette préséance accordée à la première sur la seconde. D'autre part les relations et/ou les rapports qu'ils entretiennent avec les ressources numériques, dont on a dit, et dont eux-mêmes disent, que la valence pédagogique est décisive, on a le sentiment qu'ils en « attendent » beaucoup, qu'ils les envisagent au moindre coût, non par avarice mais par prudence, et qu'ils s'impliquent finalement assez peu dans leur(s) possibles ré-élaboration(s) ou usage(s). Où plutôt, qu'ils attendent des ressources « clés-en-main », faisant partiellement fi de leurs capacités et aptitudes à les problématiser ce qu'elles peuvent leur proposer.

Il y a comme une conception non pas prothétique mais « orthétique » des ressources qui viennent en quelque sorte corriger une altération fonctionnelle. Ils formulent des exigences relativement précises, tant au plan pédagogique qu'au plan scientifique, sur ces ressources tout en paraissant vouloir se délivrer ou se désimpliquer de toute co-élaboration. Il y a comme un effet d'« auctorialité » (Leclerc, 1998), visant à se mettre sous (le) couvert de… Cette division technique du travail entre producteurs d'un côté et usagers de l'autre, pose un certain nombre de questions et de problèmes, en particulier celle d'un isolement dans une position secondaire de simple validation ou certification, sans retour sur la construction même des ressources, avec le risque d'une segmentation, voire d'une disjonction. En ce sens, il me semble que la certification doit aussi et peut-être d'abord se donner pour objet et pour mandat, une homogénéisation interne des ressources produites, qui a des implications fortes quant à la constitution d'un véritable système d'information documentaire interface.

Demeure également la question particulière de la pérennité documentaire d'une ressource. Il s'agit là d'une question difficile en ceci que la distinction entre une valence physique/matérielle et une valence intellectuelle/formelle me paraît sans aucun fondement. Au reste, la définition de la notion de document n'opère pas cette distinction et c'est pourquoi il me semble que la qualité et la pérennité d'une ressource doivent s'apprécier sur la base des cinq éléments indispensables pour qualifier un document comme tel (Roux-Fouillet, 2004, p. 65). J'insisterai à nouveau sur le fait que la pérennité ou qualité documentaire n'est pas (seulement) une propriété d'objet mais dépend des usages et des pratiques, par définition immaîtrisables en leur totalité.

De ce point de vue également, je suggère de plutôt parler de ressources documentaires et de ressources documentaires numériques qui le sont désormais toutes peu ou prou, quoique selon des formats différents.

Ébauche de critères

Ces réflexions faites, je propose ci-dessous une ébauche relativement à la constitution pratique des critères. On peut d'ores et déjà en retenir quatre : la qualité littéraire, la qualité scientifique, la qualité pédagogique, la qualité documentaire. Dans le détail, qui est à discuter bien sûr, on désignera, par qualité littéraire, tant à l'oral qu'à l'écrit, la précision de la langue utilisée et la rigueur du vocabulaire employé (terminologie, notations, écriture des formules, définitions) ; par qualité scientifique, la rigueur, la clarté, la conformité avec les programmes scolaires (les curricula) de l'enseignement primaire et secondaire ; par qualité pédagogique, l'aisance d'intégration dans une démarche pédagogique quotidienne, la possibilité d'usages variés et cohérents (en classe, en situations de travail autonome pour les élèves) ; 4/ par qualité documentaire, l'ergonomie générale du dispositif documentaire, le raffinement de l'indexation, des thésaurus pertinents c'est-à-dire avec une qualité des liens sémantiques. Quant à la méthode, un court texte argumenté/argumentatif pour valider une ressource, me semble tout à fait pertinent, avec une question subsidiaire mais décisive : quel est le seuil de validation d'une ressource ? Autrement dit, est-ce qu'il y a pondération des critères entre eux ? Sont-ils tous isonomes (au sens politique et non pas minéralogique du terme) ? Autrement dit, ont-ils tous la même valeur, le même poids décisionnel ? [http://intranet.inrp.fr/intranet/institut/groupes-de-travail/rapport-final]

  ; LE COADIC Y.-F. ; POMART P.-D. & SUTTER É. [dir.] (2004). Dictionnaire de l'information. Paris : A. Colin [2 e éd.]. ESCARPIT R. (1991). L'information et la communication : théorie générale. Paris : Hachette. LE COADIC Yves-François (1994). La science de l'information. Paris : PUF. LECLERC Gérard (1998). Le sceau de l'oeuvre. Paris : Éd. du Seuil, ROUX-FOUILLET Jean-Paul (2004). « Document ». In S. Cacaly et alii (dir.), Dictionnaire de l'information. Paris : A. Colin, p. 64-65. TROUCHE Luc [coord.] (2010). Un institut de recherche, développant des ressources vivantes avec et pour les acteurs de l'éducation. Rapport du groupe de réflexion « Ressources », 31 mars 2010. In Rapports des groupes de travail. Lyon : INRP, p. 48-119 (document PDF consulté le 27 mai 2014).

Liste hiérarchisée et coordonnée de termes qui fonctionnent en réseaux sémantiques.

Le terme doit selon moi s'entendre ici, avec toute la charge d'ambiguïté sémantique qu'il recouvre, désignant à la fois un site élaboré sous le couvert institutionnel de l'Éducation nationale et généralement hébergé sur les sites web des Rectorats d'académie et le caractère conventionnel de (ce) qui suit étroitement les règles conventionnelles justement.Quelques éléments pour une réflexion sur la notion de ressource(s) | 

Quelques éléments pour