dataesr/scientific-paragraphs-categorization huggingface dataset:
It also requires effective combination of enablers such as ontology, model driven/service oriented architecture and enterprise modeling, coupled with Model Based System Engineering, Computer Aided Design, Computer Aided Manufacturing and Computer Aided Support. Creating such effective combination of standards is a scientific challenge, due to the silos induced by each concerned community using heterogeneous technologies, languages and paradigms. Applying such effective combination of standards within a DMN is also a challenge because of the uncontrolled evolution of the technologies and solutions developed by each domain or used by each stakeholder. In order addressing such issues, we have been developing a federative framework for eBusiness PLM interoperability within DMN. We integrated within this framework the Open Group's ArchiMate open and independent standardized enterprise modeling language, which supports the description, analysis and visualization of architecture within and across business domains in an unambiguous way.
This choice was made after assessing other enterprise modeling standards, and was motivated by the simplicity of the language, its alignment with principles of governance of the evolution of the information system defined by enterprise modeling and control urbanism of enterprise information system, its intent of use for facilitating the communication between enterprise, process, information system and ICT architects, and the existence of the Archi modeling tool. Archi modeling tool (http://www. archimatetool. com) was created by Phil Beauvoir on top of the Eclipse Modeling Tools which implements OMG's specification related to Meta Object Facilities in order supporting Model Driven Architecture. It relies on a formalization of ArchiMate using eCore (http://eclipse. org/modeling/emf), on top of which visual modeling capabilities were develop with full alignment with underlying principles of ArchiMate, i.
e. support of multiple views derived from predefined viewpoints associated to precise stakeholders, concerns and authorized subset of language modeling constructs. Archi also provides ability to the user for definition of properties as (name, value) couples, which can be used as a way for annotating an Archi model. In addition, Archi is open source and is an implementation of reference of the open ArchiMate standard, which is a mature standard, as several implementations are available, being on top of commercial or free open source solutions. It makes Archi an appropriate ground for including ArchiMate as a branch of an extended hypermodel for interoperability  [3].
g. ISO 10303, ISA 95) and System Engineering standards (e. g. ISO15288), Enterprise process standards (e. g. ArchiMate), Application family (e. g. PDM) standards or ICT standards (e. g. XML technologies), as inputs for being able to define how to jointly combine them all along their lifecycle in order supporting PLM interoperability with a DMN. A fist target is being able to use it for appropriate functional and non-functional specifications by the enterprises for implementation by software solutions, testing, deployment, integration and support. A second target is to support demonstration of appropriate and effective usage for supporting enterprise objectives, goals and processes.  Definition of a model based approach for assessing PLM standards and their implementation through a test based approach, on top of a test bed which will allow in a first phase to simulate the expected collaboration in a DMN using the standards for targeted business collaboration scenarios, and in a second phase to validate implementations of the standards for supporting these scenarios reusing simulation process, scenarios and data for unitary and integration testing.
Implementations of the standards concerns as well software products, applications, methods and business processes within the DMN, and between the partners, their applications and their specific business processes Doing so, several issues arose concerning usage of model based enterprise modeling relying on Archi within PLM interoperability within System Engineering and manufacturing DMN context. First ArchiMate scope and intent of use is not the same than other standardized languages such as UML used for Software development, BPMN used for Business Process modeling or XPDL used for design of workflow models and their execution on workflow engines. It's the reason why methods and tools build on top of Archi and enterprise modelling are to be interconnected with methods and tools relying on such standardized languages and associated modeling languages and platforms, implying to properly manage the produced models as consistent sets of artefacts, their relationships with used modeling platform and targeted enterprise execution platforms.
Second Archi is a modeling tool built on top of Eclipse that can be used only on a personal desktop. A single model is produced within a single XML file, but with multiple views. No capabilities exist allowing combining several model trunks, produced by different persons or tools (e. g. self-describing enterprise applications). Or the different blueprint models for support of a DMN have to be produced independently by several organizations and tools as separate artefacts, using ArchiMate with Archi, but also other languages and related modeling tools. As a consequence, as for a manufactured Product, Enterprise data management solution, similar to Product Data Management solutions, are required for collaborative production and consumption of Enterprise models. Third the enterprise applications underlying conceptual models and the enterprise modeling language are not based on the same meta model and on the same semantic.
However it requires installing a sophisticated mechanism of model transformation, which enables a wide range of different automated activities such as translation of models (expressed in different modeling languages), generating code from models, model refinement, model synthesis, model extraction and model refactoring. It proposes EMF refactoring usage in a transformation chain based on the AndroMDA tool for model driven software development. We assessed AndroMDA in ATHENA and OpenDevFactory projects. One issue identified comes from the fact that Platform Models are not provided and that transformation is based on velocity, which is not a model to text solution. Underlying technology is really hidden, making it difficult to establish communication between the functional and ICT infrastructure architects.
Transformation and deployment logic is hidden and very difficult to correct or debug when something is going wrong. Finally, creating Platform Independent model from PLM standards is an important manual task. Transforming these standards formalization in Domain Specific Language, as UML profiles or as MOF/EMF based DSL, should allow generating the PIM from models of the PLM and System engineering standards, which include as well domain information models (e. g. ISO STEP application protocols, ISA 95), business processes (e. g. ISO15288, SCOR) or business services (e. g. OMG's PLM Services). An issue here is that formal language for specifying the standards are heterogeneous implementation languages which are not necessarily the one used in the execution platform. E. g. a STEP application protocol is formalized in EXPRESS, while languages considered by the targeted execution platform are based on AndroMDA profiles, which consider Manageable entities, value objects, services (local, remote, web), internal processes and user/machine interface interaction processes.
Platform targeted for PLM hub are quite more complex than the one targeted by AndroMDA, and being able capturing infrastructure as visual model with appropriate DSL is an important need. Finally, hiding the infrastructure as aimed by model software driven engineering is not accurate when willing ensuring that infrastructure fits with enterprise motivation and when willing to deal appropriately with deployment and evolution. [6] puts the emphasis on Sirius, a Domain Specific Model graphical editor, which simplifies the production of graphical editing tools for domain specific language, which respond to the previously identified need. So we assess Sirius which is now integrated on OBEO designer, an open source tool based on Eclipse Modeling Tools. One drawback we identify comes from the fact the graphical DSL editors are generated on top of Eclipse as execution Platform, and not on top of Web solution.
The need exists for publishing a referential of models for supporting effective collaboration, and eventually ability of designing and monitoring the collaboration using graphical modeling and monitoring tools on the web using the created DSL notation. [7] reports on the TEAP (TOGAF Enterprise Architecture Platform) experience to target Model Driven Organization (MDO) limitations in an industrial context while identifying relevant improvements to the MDE techniques themselves. The focus is on federation of heterogeneous data sources to integrate relevant Enterprise Architecture (EA) information, more easy adaptation of an EA standard to a client needs, with traceability of the different usages, and finally support of multiple views/viewpoints over the same EA repository. The proposed approach indicates that solutions will be made available, which will enrich the Eclipse Modeling Tools for collaborative modeling and federation of models.
The same approach is to be applied with services and data objects. Description of services with ArchiMate doesn't support capture of operations, which is a too low grain of detail. Description of data doesn't support capture of entities. So it will be needed associating services and data objects in Archi with representation based on other languages, supporting the appropriate level of detail. It can be UML for software design (deployment and component diagrams), EXPRESS, XML Schema, Json or EJB entities for data serialization, WSDL for web services, etc. Similarly, ICT layer can be mapped with underlying network and eventually virtualization servers (e. g. ProxMox) allowing automated generation of virtual network or creation of views querying the virtualization servers. At business layer, such mapping can be done with models using more rich languages such as BPMN, IDEF0 or SPEM.
For motivation views, it can be mapped with more detailed decision models. Finally implementation and migration views can be related to project planning models. Archi model can be use as integration model dedicated to communication between the different architects and stakeholders, in order aligning CIM, PIM and PM models. Two model transformation chains, one for software artefacts generation and deployment on the cPlatform, based on solution such as AndroMDA, one for model to model generation and DSL integration, based on solution such as Obeo Designer.
Blueprint template for manufacturing PLM standards Numerous types of manufacturing PLM standards have been produced, providing several frameworks for system engineering processes, product data exchange, sharing and long term archiving, PLM services, CAD services, etc. Such processes don't aim at standardizing the business processes or the software tools. It is the reason why important work is still to be done when willing to implement them and to use them in operational context, as the link is to be made with the specific context, i. e. the actual processes and operational platforms. In order facilitating assessment and implementation of the standards, our approach allows to produce blueprints describing the standards in order helping each stakeholders, and in particular the architects referenced in the ArchiMate specification (enterprise, process, information system, ICT technologies architects), to better understand how the proposed standards can be use.
It was done through participation to or assessment of several research projects in PLM area (RISESTEP -Enterprise Wide standard access to STEP distributed databases -Esprit Project 20459), SAVE (Step in a virtual enterprise-bright euram project 97-5073), OpenDevFactory (Paris cluster Usine Logicielle), CRESCENDO (FP7 Transport 234344 Collaborative and robust engineering using simulation capability enabling next design optimization), TOICA ( Thermal Overall Integrated Conception of Aircraft), SIP@SystemX , Factory of the future area (IMAGINE FoF ICT 201173 Innovative end to end management of DMN), in enterprise application interoperability area (IDEAS IST 2001 37368, ATHENA FP6 IST 507849 Advanced technologies for interoperability of heterogeneous enterprise networks and their applications -COIN Collaboration and interoperability for networked enterprises IST FP7 IST IP project 216256, NEFFICS Networked enterprise transformation and resource management in future internet enabled innovation cloud FP7 ICT 258076) or in Digital Business Ecosystems (FP6 Integrated Project IST-2002-507953).
In section §2, we describe the ALHAMBRA dataset. Section §3 provides the basic information about the BCF cluster finder. Section §4 is devoted to the description of the mock catalogues used in this work on one hand and, on the other, to the results regarding cluster detection on them, the description of the selection function for the ALHAMBRA survey and the accuracy in measuring cluster properties such as redshift or mass. In Section §5, we present the ALHAMBRA optical cluster and group detections. We first compare the detections found in this work with those found by other authors using different datasets and techniques. Then, we explore the main properties of the detections such as the stellar mass distribution, the presence of colour-magnitude relations and the fraction of blue and late-type galaxies in the cluster.
THE BAYESIAN CLUSTER FINDER In this work, we have used the Bayesian Cluster Finder (BCF;  Ascaso et al. 2012) , a technique developed to detect galaxy clusters and groups in any optical/infrared image dataset. This method is based on a modification of the Matched Filter Technique  (Postman et al. 2002)  including photometric redshifts and the presence of Bayesian priors. In more detail, the BCF initially calculates the probability that there is a cluster centered on each galaxy at a given redshift. In order to calculate this likelihood, we assume that clusters are modeled as a convolution of a particular density, luminosity and photometric redshift profile. We choose to use the Plummer density profile  (Postman et al. 2002) , the Schechter luminosity function  (Schechter 1976 ) and the full redshift probability function (P(z),  Benítez 2000; Molino et al.
5M pc) (4) i. e, defined as the sum of all the stellar masses of the galaxies, M * , statistically belonging to the cluster. The stellar masses have been calculated with BPZ2. 0 in the same way as  Molino et al. (2014). So far, the BCF has been applied to two more optical surveys: a wide survey, the CFHTLS-Archive Research Survey (CARS,  Erben et al. 2009; Ascaso et al. 2012) , and a very deep survey, the Deep Lens Survey (DLS,  Wittman et al. 2002; Ascaso et al. 2014a). In this work, we apply the BCF to a high photometric redshift resolution survey, the ALHAMBRA survey. The comparison between these studies will indicate the benefits and drawbacks of using datasets with different properties for detecting galaxy clusters and groups in the optical.
The population of dark matter (DM) haloes for the mock catalogue comes from the Millennium Simulation  (Springel et al. 2005 ), a 2160 3 particle N-body simulation of the Λ Cold Dark Matter cosmology starting at z = 127 and models the hierarchical growth to the present day. The halo merger trees are constructed using particle and halo data stored at 64 fixed epoch snapshots spaced logarithmically in expansion factor. The minimum halo resolution is 20 particles, corresponding to 1. 72 × 10 10 h -1 M⊙. Finally, the light-cone was constructed from this simulation by replicating the simulation box and choosing an orientation. In addition, a flux cut at F 814W < 24. 5 AB was applied to reproduce the selection of the ALHAMBRA survey. The final mock catalogue is limited to z < 2 and it does not include stars.
This is exactly what we find when we run BPZ2. 0 on the original mock catalogue, obtaining a photometric redshift accuracy of ∆z/(1 + z) = 0. 0319, a factor of ∼ 3 worse than in the real data  (Molino et al. 2014). A closer inspection of the original photometry included in the light-cone, evidenced the above mentioned fact that the SED of a significant fraction of the galaxies included in this mock did not match any of the spectra in the BPZ. 2. 0 library. Therefore, to obtain a galaxy colour distribution which accurately resembles our real ALHAMBRA catalogues, we had to force these objects into realistic colours, assigning then the closest BPZ2. 0 SED. This technique, called PhotReal, has already been applied to previous work  (Arnalte-Mur et al. 2014; Zandivarez et al. 2014; Ascaso et al.
As stressed in  Molino et al. (2014)  with the ALHAM-BRA data, we can additionally increase this resolution by performing a cut in the odds parameter. This parameter is defined as the integral of the redshift probability function P (z) around its maximum peak within twice the expected photo-z accuracy for the survey/data which, in the case of the ALHAMBRA data, it was measured to be 0. 0125. The odds parameter gives us a direct estimation of the quality of the photometric redshift since it measures how concentrated around the 'true' photometric redshift value the P(z) is  (Benítez 2000; Benítez et al. 2009; Molino et al. 2014). For instance, performing a cut in odds > 0. 5 in the simulation increases the photo-z resolution to ∆z/(1 + z) = 0. 0098 while a cut in odds > 0. 9 provides a subsample of even higher photometric resolution, ∆z/(1 + z) = 0.
7. The restriction of the ALHAMBRA data to z < 2 is plotted in order to match the redshift limit of the mock catalogue. The simulation counts are only ∼ 8% smaller than the real data, a discrepancy that could be attributed to cosmic variance (e. g. López-Sanjuan et al. 2014). The second check performed has been to compare the stellar masses provided by BPZ2. 0 in the mock catalogue with the stellar masses in the ALHAMBRA data. In Fig. 3 , we display the stellar mass histograms for the ALHAM-BRA data, together with the initial simulation and the postprocessed simulation. The stellar masses of the initial simulation refer to those provided by GALFORM. The three distributions have been restricted to F 814W < 24. 5, the completeness limit for the ALHAMBRA survey. We find that the agreement of the observed and post-processed stellar mass distribution is very good (<8%), while the difference is higher for the observed and initial stellar mass distribution (<17%).
While the purity rates remain >60% for all redshift and mass richness, the completeness rates are lower and decrease with redshift in general. We obtain completeness and purity rates >80% for clusters with total stellar masses larger than 1. 5 × 10 12 M⊙ or halo masses of 6 × 10 13 M⊙ up to redshift ∼ 0. 8. For higher redshifts (0. 8 < z 1), we increase the threshold mass for which we find completeness >80% to M * CL > 1. 8 × 10 12 M⊙, equivalently M h > 1. 0 × 10 14 M⊙. We fail at detecting galaxy clusters with completeness and purity rates >80% for clusters at redshift z > 1. If we relax instead both completeness and purity rates All the distributions are restricted to the magnitude limit where ALHAMBRA is complete (F 814W < 24. 5). We confirm a good agreement between the stellar mass distribution of the ALHAM-BRA data and the final mock catalogue (<8%), finding a higher difference (< 17%) between the ALHAMBRA data and the initial mock catalogue.
Comparison with other studies One of the most attractive features of the ALHAMBRA survey is the number of different surveys with overlapping data, providing an excellent way to deal with the cosmic variance (e. g. Molino et al. 2014; López-Sanjuan et al. 2014). In addition, we can take advantage of early searches on these fields to cross-correlate them with our detections and quantify the degree of agreement between different datasets and methodologies. From all the surveys extending over the seven ALHAM-BRA fields, one of them has been widely studied for cluster purposes in the literature: the COSMOS survey, overlapping with the ALH-4 field. Up to date, several work has provided us with catalogues of large-scale structure or cluster/group detections in the COSMOS survey in the optical. Scoville et al.
(2007b)  detected very large-scale structure up to redshift 1. 1 in the COSMOS field using photometric redshifts. In addition,  Olsen et al. (2007)  detected clusters in the CFHTLS-Deep Survey, also overlapping with the COS-MOS field. Later on,  Bellagamba et al. (2011)  used an optical and weak lensing search to detect galaxy clusters in the COSMOS field. Two recent works,  Castignani et al. (2014)  and  Chiang et al. (2014)  have provided a list of high redshift (z > 1) clusters and proto-clusters detections. The former is based on detecting over densities around radio galaxies to detect high-redshift (z ∼ 1 -2) galaxy clusters and the latter, used the photometric redshift obtained from the combination of the optical and IR data to detect very high-redshift proto-clusters (z ∼ 2 -7). In addition, there are some more works that have been detecting groups and clusters with other techniques:  Knobel et al.
5 and z>0. 85. More details are given the text. The different cluster and group catalogues analysed in this work are built from different datasets, using a variety of methodologies each of them carrying their own systematics, and with different selection functions. These facts make the comparison difficult, as it becomes evident in Fig. 10 , where the different spatial distributions of each dataset become noticeable. Notwithstanding these facts, we still find a general tendency in this comparison to agree at the highend of the mass distribution function (M h > 1 × 10 14 M⊙ at least) and at redshifts (z < 0. 7 at least), as expected from the simulations.
SUMMARY AND CONCLUSIONS In this work, we present the first release of the optical galaxy clusters and groups catalogue in the ALHAMBRA survey. ). The fraction of blue galaxies appears to be higher for the less massive structures and few early-type galaxies are already in place on the red sequence in the same clusters. According to simulations, we are able to sample the mass function down to ∼ 6 × 10 13 M⊙, up to redshift 0. 8, with both completeness and purity higher than 80% and down to ∼ 3 × 10 13 M⊙, with detection rates >70% to the same redshift. At higher redshift, the mass threshold increases, being able to detect structures with masses > 1×10 14 M⊙ up to redshift 1 in the first case, and > 6×10 13 M⊙ up to redshift ∼ 1 and > 1 × 10 14 M⊙ up to redshift ∼1. 2, in the second case. Additionally, we have compared our detections with other cluster samples obtained from a variety of datasets and techniques, achieving a very good agreement when matched to our sample, confirming the completeness of our results.
ACKNOWLEDGEMENTS This work is based on observations collected at the  Centro Astronmico Hispano Alemn (CAHA) at Calar Alto , operated jointly by the  Max-Planck Institut fr Astronomie  and the  Instituto de Astrofsica de Andaluca (CSIC). We thank the anonymous referee for his/her valuable comments that help to improve this paper. BA thanks  Carlton Baugh  for his useful comments on an earlier version of the draft. We acknowledge support from the  Spanish Ministry for Economy and Competitiveness  and  FEDER  funds through grants  AYA2010-22111-C03-02 ,  AYA2010-15169 ,  AYA2012-30789 ,  AYA2013-48623-C2-2 ,  AYA2013-42227-P ,  AYA2013-40611-P ,  AYA2011-29517-C03-01 ,  AYA2014-58861-C3-1 ,  AYA2010-15081 ,  Generalitat Valenciana  projects  PROMETEOII/2014/060 ,  Junta de Andalucía  grant  TIC114 ,  JA2828 ,  Aragón Gorvernment  -Research Group E103.