dataesr/scientific-paragraphs-categorization huggingface dataset:
IDEADB The Innsbruck Dissociative Electron Attachment (DEA) database node collects relative partial cross sections for dissociative electron attachment processes of the form: AB + e -→ A -+ B, where AB is a molecule. Queried identifiers are searched in both products and reactants of the processes. XSAMS files (see Section 3. 1. 1) are then returned which describe the processes found including numeric values for the relative partial cross sections of the dissociative electron attachment reactions. Additionally, a visual representation of the cross sections can be viewed on the web site. Since 2016 the possibility to add cross sections for cationic products and resolution of several minor issues have been addressed. It is planned to modify the database structure, so that measurements in matrices such as water or helium nanodroplets can be added.
VAMDC Data Nodes that Have not Evolved since 2016 There have been no changes to some databases and nodes since 2016. These will be described in this section, and more information can be found in our previous publication  [3]. It should be noted that these databases contain quite unusual species and processes for the VAMDC e-infrastructure, for which the current VAMDC visualisation tools and even the current VAMDC standards lack features that would allow a full display of the databases contents. Therefore at present VAMDC mainly provides only a simple view of those databases.
LASp The LASp (Laboratorio di Astrofisica Sperimentale) database is hosted at the Catania Astrophysical Observatory in Italy  30  and additional information can be found at its URL  31. LASp spectra are taken by using in situ techniques and equipment especially developed to analyse the effects of irradiation (ion and/or UV photons) and thermal cycling (down to 10 K) by infrared, Raman and UV-VIS-NIR spectroscopy. Analysed materials include frozen gases, solids samples and meteorites. The main application field up until now has been in astrophysics, and over the years many hundreds of ice mixtures of various compositions and of solids have been studied. Through the VAMDC portal, transmission and optical depth data for water-ice experiments are available  [122, 123]. The public database also includes optical constants of solid-state CO, CO 2 and CH 4 deposited at various temperatures.
PAH The Cagliari-Toulouse PAH theoretical spectral database  [36]  is a joint effort by the groups of G. Mulas (INAF-OAC) and C. Joblin (Univ. Toulouse III/CNRS-IRAP) aimed at providing all the "ingredients" needed for modelling the photophysics of individual polycyclic aromatic hydrocarbons (PAHs) in space, mainly in photon-dominated interstellar and circumstellar environments. It includes basic structural properties of PAHs in four charge states (-1, 0, +1 and +2), ionisation potentials and electron affinities, harmonic vibrational analyses and vertical photoabsorption electronic spectra. The link to the "old" database with flat files, which includes more data than available through VAMDC, is still online  32. The web interface to the relational database, holding the data available through VAMDC, is hosted at the Cagliari Observatory in Italy  33.
ExoMolOP The ExoMol project provides molecular line lists for exoplanet and other atmospheres  [124]  with a particular emphasis on studies of hot atmospheres. Besides line lists, which are stored as states and transitions files  [125] , the ExoMol database  34  stores a variety of other associated data including partition functions, state lifetimes, cooling functions, Landé g-factors, temperature-dependent cross sections, opacities, pressure broadening parameters, k-coefficients and transition dipoles. These data and the associated data structure are described in the database release papers  [126, 127]. The line lists provided by ExoMol are huge and are too big to be handled by the VAMDC portal; this issue is described below. Recently a new offshoot of the ExoMol project called ExoMolOP has been created, which contains opacity cross sections and k-tables  [128]  for molecules of astrophysical interest  [37].
This database is built on ExoMol data but contains input from HITRAN  [16] , the empirical MolList database of Bernath  [129]  and NIST for selected atoms. ExoMolOP provides data on a grid of 22 pressures and 27 temperatures on a grid of wavelengths for each species. By comparison with the unprocessed ExoMol data, these provide a comparatively compact representation of the absorption property of each species. An implementation of the ExoMolOP data within the VAMDC portal is currently in progress.
SSHADE in VAMDC Currently VAMDC allows access to the original GhoSST database  35  (Grenoble astropHysics and planetOlogy Solid Spectroscopy and Thermodynamics) to search for a few pure and mixed molecular solids through their constituent species and to retrieve their infrared spectra, either as absorption coefficients or as optical constants. SSHADE  36   [35]  is a database infrastructure of solid-state spectroscopy that hosts spectral data of many different types of solids including ices, snows, minerals, carbonaceous matters, meteorites, interplanetary dust particles and other cosmo-materials covering a wide range of wavelengths: from X-rays to millimeter wavelengths. The data are collected from a consortium of partners  37  , which provide their data in their own database of the SSHADE infrastructure.
Currently a "band list" database of molecular solids is under development in the frame of the Europlanet-2024 research infrastructure program. It will host critical compilations of the position, intensity, width and vibration modes of absorption bands (visible-infrared or Raman active) of pure and mixed molecular solids as well as for several types of molecular compounds such as hydrates and clathrate hydrates. Both the SSHADE spectral databases and the band list database will be linked to VAMDC, but this will require an upgrade of the XSAMS data model (see Section 3. 1. 1) in order to describe the fundamental solid constituents better. With such databases, VAMDC will allow the user to retrieve and compare the band parameters of molecular species in both gaseous and solid states, and therefore, will allow them to determine which one does actually contribute to observed absorption features.
AMBDAS AMBDAS (Atomic and Molecular Bibliographic Data System) Integration of AMBDAS within the VAMDC infrastructure is planned for release in 2020 as part of an upgrade to the database software, which includes a recently developed DOI-centred reference management library  [85]  and an updated classification of plasma processes  [130]. In addition to a new search interface, VSS2 queries and XSAMS output (see Section 3. 1. 1) are supported. The AMBDAS system will be queried by species and processes, and so will be accessible from the species database. In addition, since the AMBDAS system is a bibliographic database, it will be queried through the new bibliographic service described in Section 6. 5.
DREAM-DESIRE The Database of Rare Earths At Mons University (DREAM) contains information concerning the radiative parameters (wavelengths, transition probabilities and oscillator strengths) for more than 72,000 spectral lines belonging to the lower ionisation stages of lanthanide elements (Z = 57 to 71), from neutral to triply ionised species. This database, originally created by Biémont et al. [131]  and recently updated by Quinet and Palmeri  [39] , is hosted by Mons University  39. All the data tabulated in DREAM have been determined from detailed pseudo-relativistic Hartree-Fock calculations including core-polarisation effects  [132, 133]  carried out by the Atomic Physics and Astrophysics group at Mons University, Belgium. The accuracy of the theoretical results have been assessed through comparisons with experimentally measured radiative lifetimes using laser-induced fluorescence spectroscopy.
IAMDB The volume of high-precision data generated by the Indian atomic and molecular community is quite substantial. This is evident from the number of articles published by various groups. However, such data are not well organised and, hence, very difficult to retrieve for further use. This is the reason for the requirement of an atomic and molecular data repository in India, which has been envisaged for many years now. The Indian Atomic and Molecular DataBase (IAMDB  41  ) is the outcome of such an effort. With the help of the VAMDC interface, the data generated and gathered in IAMDB can be easily retrieved by any user. In the last few years a great deal of electron scattering data has been produced in India. In particular, partial and total electron ionisation cross sections have been measured over an extended energy regime for about two dozen organic molecules important to radiation biology  [134, 135].
PEARL The PEARL (Photonic Electronic Atomic Reaction Laboratory) database in the Korea Atomic Energy Research Institute (KAERI) includes electron impact ionisation (EII), recombination and photoionisation for atoms and ions. The EII  [143]  and the dielectronic recombination (DR)  [144]  have been calculated using a relativistic distorted wave approximation, and the photoionisation  [145]  has been calculated using a non-iterative eigenchannel R-matrix method for the ground and lower excited levels of atomic ions below Z = 30, which are of interest in astrophysics. The EII  [146]  and the DR  [147]  calculations have also been performed for tungsten (W, Z = 74) ions, which are essential in fusion tokamak research. The calculated cross section data can be graphically displayed on the PEARL web site 42 , together with other available experimental and theoretical data for comparison, the numerical data can be also downloaded.
This will return all datasets with clusters of "(CO 2 ) n (H 2 O) m ", (m, n > 0). Often, the produced mass spectra display features of many different cluster ions, because impurities are attached to the clusters of interest. Fragmentation of larger molecules may also display features of further non-stoichiometric cluster progressions. Thus, different queries return the same dataset. On the website of the node itself we will offer more filter options: • Method of cluster formation (supersonic expansion, seeded beam, gas aggregation, electrospray ionization, helium nanodroplets,. ) • Method of ionization (electrospray ionization, matrix-assisted laser desorption/ionization, electron impact, photo ionization,. ) • Steps in between (tandem mass spectrometry, collision-induced dissociation,. ) • Analysis method (time-of-flight, quadrupole, ion cyclotron resonance,.
) • Environment (temperature, pressure,. ) • Others (evaluation of data, publication, magic numbers, solvation-effect,. ) The most important returned data will be mass spectra (which can also be visualized in a browser). Published papers related to the species asked for as well as possible evaluation programs  [149]  and their output will be made available. Larger files will be available by a download link found in the XSAMS data file (see par. 3. 1. 1). Since 1986 a group in Innsbruck  [150, 151]  has been producing mass spectra of clusters via different approaches. These results are planned to be made available in this database.
Overview of the VAMDC e-Infrastructure Components The e-infrastructure currently connects, in an interoperable way, 38 heterogeneous databases with atomic and molecular data. By providing data producers and compilers with a large dissemination platform for their work, VAMDC successfully removes the bottleneck between data producers and the wide community of atomic and molecular data users. The "V" of VAMDC stands for "virtual" in the sense that the e-infrastructure itself does not contain the data: it is a wrapper that exposes the heterogeneous databases in a unified way. The wrapping software, called the node-software  [152] , integrates a stand-alone database into a VAMDC federated database to become a data-node. Each data-node accepts queries submitted in a standard grammar (see Section 3.
Data Nodes, Query Language and Data Formats A data-node is a database, either pre-existing or created for the purpose of VAMDC, wrapped in the node-software that implements the web-service  43  protocol VAMDC-TAP, which is derived from the International Virtual Observatory Alliance (IVOA)  44  Table Access Protocol (TAP). 45 ll VAMDC-TAP services support a common data model, query language and output format. The data model, expressed in the VAMDC Dictionary, represents the data both in a tree structure and as a standardised set of virtual tables. The query language VAMDC SQL Subset 2 (VSS2) 46 operates on these virtual tables. The common output format is the XML Schema for Atoms, Molecules and Solids (XSAMS) 47   [153]  that uses the tree-structured form of the data model. All VAMDC-TAP services allow XSAMS output while the nodes may optionally support other formats.
XSAMS is highly flexible and expressive, but other formats may be preferred for compactness. Libraries in Python of the node software are provided by the VAMDC consortium. The node owner configures these libraries for the database of choice by adding small translation-functions from VSS2 to SQL operating on the actual database, and from the query results to XSAMS or other formats. Additional information and examples of best practices were described by Regandell et al. [152].
Registry The VAMDC metadata registry 48 lists the details of the VAMDC data-nodes. Applications use the registry to decide which databases should be queried and to locate the services for those databases on the internet. The VAMDC registry is based on the work of Astrogrid, which was the UK's Virtual Observatory development project from 2001 to 2010  [154]. They developed a registry whose interface is based on the then-current IVOA standard. To simplify the access to this registry, the VAMDC consortium provides Java and Python libraries that are used by the VAMDC portal, among other applications.
The Portal The VAMDC portal 49   [155]  relies on the infrastructure elements previously described in this section to provide seamless access to the inter-connected VAMDC databases. Through this unique interface a user can query any database member of the VAMDC infrastructure and can retrieve data in the common shared file format VAMDC-XSAMS (see Section 3. 1. 1). The page displaying the resulting data recalls the exact query processed by the infrastructure to produce the data (for example, see Fig. 1 ). 46 http://vamdc. eu/documents/standards/queryLanguage/vss2. html 47 https://standards. vamdc. eu/#data-access-protocol-query-language-and-dictionaries 48 http://registry. vamdc. eu/registry-12. 07/main/index. jsp 49 https://portal. vamdc. eu/vamdc_portal/home. seam The portal embeds processors to convert data from the XSAMS format into several formats (chosen by user) and has several graphical tools to visualise the extracted data.
The Species Database To overcome the problem of species identification, the VAMDC consortium created in 2016 a centralised chemical-species repository called the species database. Updated daily by automated collation of data from the VAMDC data-nodes, it contains the list of all the species in each VAMDC database. Every species is identified uniquely by an InChIKey  [157] , a hash code generated from an InChI description  51. In the species database each InChiKey is associated with the different ways of identifying a species; e. g. their chemical names, formula, stoichiometic formula and CAS number. By adding a REST API and a web graphical interface to this species database  52  , we provide a versatile tool to explore the species content of the atomic and molecular VAMDC connected databases.
The Query Store By using the VAMDC facilities, scientists can easily discover the atomic and molecular resources and access their data in a unique and practical way. However, as VAMDC has been adopted by a larger range of communities it has revealed a new set of challenging issues linked with citation and data reuse: • The VAMDC infrastructure data are dynamic. A database displayed through the VAMDC infrastructure may evolve over time: the most recent and precise version of given data may replace old ones. We therefore needed mechanisms to allow the citation of dynamic data. • The data set provided by the VAMDC infrastructure always contains the references of the papers used for compiling the data sets. However, the citation process may become cumbersome when the extracted data sets come from many sources.
The data-set sources become the references of the DOI. The authors/papers referenced in the VAMDC extracted data set will automatically get credit when the data set is cited (using the DOI) into a paper. Table  2  lists the VAMDC databases currently integrated with the Query Store service, whose queries may be discovered by accessing the URL 55 ; this service is the most complete collection of VAMDC queries that may be cited as example of the queries performed through the infrastructure.
Treatment of Big Data The growth in large data sets, which is common to all areas of science, is also true in A&M physics. VAMDC uses a tightly defined and rigorous data structure that is also, as a result, relatively 54 DOI: Digital Object Identifier, a formal name for a document or data-set in a standard format intelligible by software. 55 https://cite. vamdc. eu verbose. This means that the data returned by queries to some databases such as VALD and KIDA are already limited by the software so as not to cause problems. Moreover, if many current VAMDC molecular spectroscopic databases contain data with a relatively limited amount of spectral lines for each molecule (HITRAN, JPL, CDMS,. ), some others (MeCaSDa,. ) contain extensive calculated line lists, and in this case, their number for a given species can be very large (several millions of spectral lines at least) and could increase even more with subsequent updates.
At present there is a limit within the VAMDC data retrieval volume. Queries producing large data extracts time out or are truncated by the data-nodes to avoid timeouts. This prevents downloads of line lists over a wide spectral range or for many molecules at once. The actual limits vary from node to node according to the computing resources invested and the details of the database. For example, when asked for all data connected with lines between 150 nm and 800 nm, seven nodes produced a complete result, three produced a truncated result, two failed and one timed out; the others quickly reported that they had no relevant data. The largest response was for 67 million lines in 218MB of XSAMS, and this is close to the practical limit of the system. For this data-set, three of the recommended displays and format-converters were able eventually to process the data, one failed and one produced no results within 10 minutes.
This is a problem for applications in atmospheric planetary physics and exoplanet studies. A solution currently under investigation is the possibility of asynchronous queries that run slowly in the background and leave their results cached and accessible by an ephemeral URL. There are also whole databases that are currently really too big to be usefully probed via the VAMDC portal. A particular area that produces very large data sets is the provision of molecular line lists for studies of hot atmospheres. The ExoMol  [126, 127] , TheoReTS  [159]  and the NASA Ames group (e. g. [160] ) all employ theoretical methods to compute very extensive lists of molecular transitions particularly for high-temperature applications in astrophysics. Many of these line lists are huge; for example, the ExoMol line list CH 3 Cl contains 166 billion transitions for each of the two main isotopologues  [161].
Even at room temperature, complete line lists for relatively heavy long-lived greenhouse molecules with low-frequency vibrations like CF 4  [162]  or NF 3  [163]  require billions of transitions to converge opacity calculations over infrared wavelengths. Data sets of this size are completely outside the current capabilities of the VAMDC project. Some work has been performed on data compacting, in particular using the so-called super-lines approach  [164, 165]. Another method of big-data compression is to use "effective" lines as implemented in a recent addition of methane  [89]  to the HITEMP database  [86]. Use of these protocols can lead to a very significant reduction in the size of the effective line list, but these compressed lists still contain many millions of lines making it difficult for the current VAMDC infrastructure to process or download the full line list even after it is compacted.
We note that the ExoMol line lists have recently been used to generate a set of temperature and pressure dependent opacities  [37]  creating the so-called ExoMolOP database. These opacity functions provide a much more compact representation of the molecular data, and an implementation of the ExoMolOP database within VAMDC is currently being explored. A similar direction is currently being followed for the TheoReTS information system 56 containing a theoretical and experimental atlas of methane absorption/emission cross sections  [166]  up to 1000 K.
Selection and Comparison of Atomic States It is a long-standing goal of VAMDC to be able to combine data from different databases that relate to a given state or energy level of an atom or molecule. This allows comparison of measurements or theoretical values from different sources, and also permits a fuller set of data to be built up: e. g. energies for radiative transitions from one database combined with broadening values from another. This comparison needs a common labelling-scheme for states and energy levels. This common labelling is already achieved for simple molecules in the "case by case" formalism of XSAMS. The tool SPECTCOL  [109, 110] , which takes spectral data from CDMS and collisional excitation rates from BASECOL, exploits this. The labelling of states simplifies the current, theoretical understanding of the molecules sufficiently for the software to suggest states that might be treated as equivalent: i.
e. it performs a "fuzzy" match from which an expert user can pick states to treat as true matches. It is currently much harder to combine data on atomic states and levels. This part of the XSAMS data-model allows greater precision and flexibility in the description of a level at the cost of easy matching between databases. We hope to retain the current accuracy of the data model while augmenting it with extra notations that are less precise but more consistent between databases. Thus we may recover the ability to make "fuzzy" matches between databases. The restricted notations introduced by the PyValem software-package 57 may be relevant here. We emphasize that we are not seeking exact and complete, quantum-mechanical descriptions of all states. We understand that such a description may not be possible with the current, theoretical models of atoms, which are themselves approximate and incomplete (except for the simplest atoms).
Furthermore, state descriptions precise to the limits of current theory may not be unique e. g. due to underlying assumptions about coupling and state mixing. Thus, the VAMDC consortium is exploring hierarchical structures for describing atomic terms and electronic configurations. At the highest, most-precise level, these would describe the atoms to the full extent allowed by current theory. At the lower, more-approximate levels, they would allow automatic matching of data that probably describe the same states, leaving final interpretation to expert users. As a bonus, we hope to make it possible to select from the databases just the data relating to particular atomic levels and states.