dataesr/scientific-paragraphs-categorization huggingface dataset:
Storage implementation The Core Storage package is responsible for implementing persistent storage based on Apache Hadoop and implementing data accessing interfaces. It consists of two components: • Catalogue -an inventory of all imported datasets and their internal schema. All catalogue data are stored in an HBase database running on the same Hadoop cluster as the EventIndex data. • HDFS namespace -a distributed placeholder for the data. The data are physically stored on the Hadoop Distributed Files system in a format called MapFile  [7]. A MapFile is a union of two files (Sequence Files  [8] ). The first one holds raw data in a sequence of key-value pairs and the other one holds an index to the raw data stored in the first file. The MapFile, compared to other file formats available on Hadoop, is unique, as it allows having sequential scans and random data lookups at the same time.
Data access paths There are two typical access paths that satisfy all the use cases: • Event picking -lookup for a random event by identification attributes. It is the main use case of the ATLAS EventIndex. Until the end of 2015, this access was implemented by using Catalogue-based data pruning and lookup for relevant records in a MapFile by built-in index. • Data scanning -full scan of a population of events in order to perform event skimming or trigger-based selection. For this type of access path, a MapReduce job is used in order to perform distributed and scalable data filtering.
Limitation of the Core Storage implementation During a review of the ATLAS EventIndex project in late 2015, a few limitations have been identified in the Core Storage implementation: • Data ingestion into MapFile format is complex, as it requires sorting datasets by key values before storing them physically in HDFS. Typically this means launching a MapReduce job that will perform data sorting in a distributed way, which in case of small data sets (that can be easily sorted in a single host memory) is suboptimal. The average measured ingestion speed into MapFile format was 6. 4 kHz per a collection set. • Due to the extra effort (mentioned above) needed when loading data into MapFiles, a number of staging areas with duplicated data are created and maintained. • Data and metadata are separated and served by different components.
This means that any data access operations have extra cost (latency) of combing raw data with its metadata -direct access to raw data is not possible. Additionally, this implies that using any of popular opensource community frameworks to process the data is not possible. • Random data lookup of MapFiles is performed on the client side -index files are downloaded to a client machine where they are processed in order to obtain the final location of events of interest in HDFS. This can potentially cause a performance problem when the network connectivity between HDFS and the client is poor or when a single client machine performs multiple requests in parallel like in the case of Query Server. Typical event lookup speed when using MapFiles is around 4s. Most of the limitations identified during the review were related to the usage of the MapFile file format as a container for the data.
Evaluation of alternative modern storage approaches for Core Storage This chapter describes a performance comparison of some popular data formats and storage engines available in the Hadoop ecosystem to evaluate space efficiency, ingestion performance, analytic scans and random data lookup. This should help in understanding how (and when) each of the evaluated technologies can improve handling of the ATLAS EventIndex big data workloads. During the evaluation, the same ATLAS EventIndex data sets have been stored on the same Hadoop cluster using different storage techniques and compression algorithms (Snappy, GZip or BZip2).
Hardware and storage configuration The data access and ingestion tests were performed on a cluster composed of 14 physical machines, each equipped with: • 2 x 8 cores @ 2. 60GHz • 64 GB of RAM • 2 x 24 SAS drives Hadoop was installed from Cloudera Data Hub (CDH) distribution version 5. 7. 0, which includes: • Hadoop core 2. 6. 0 • Impala 2. 5. 0 • Hive 1. 1. 0 • HBase 1. 2. 0 (configured JVM heap size for region servers = 30 GB) • (not from CDH) Kudu 1. 0 (configured memory limit = 30 GB) Apache Impala (incubating) was used as a data ingestion and data access framework in all the conducted tests presented later in this report.
Apache HBase [12] is a scalable and distributed NoSQL database on HDFS for storing keyvalue pairs. Keys are indexed, which typically provides very quick access to the records. When storing ATLAS EventIndex data into HBase each event attribute was stored in a separate cell, and the row key was composed as a concatenation of an event identification attributes (runnumber, eventnumber, project, streamname, datatype and version). Additionally, encoding of the row key was enabled in order to reduce the size of HBase blocks (without this, each row would have the length of 8KB).
The assumption here was that this index should be selfcontained and does not keep pointers to the complete event records available on HDFS. • Indexing events by event number and run number in HBase database. In this approach the indexing key resolves to GUID and pointers to the complete records stored on HDFS. So far both systems have proven to deliver very good events picking performance on a level of tens of milliseconds -an order of magnitude faster than the original approach when using MapFiles solely. The only concern when running a hybrid approach in both cases is the system size and internal coherence -robust procedures for handling HDFS raw data sets updates and propagating them to indexing databases with low latency have to be maintained and monitored.
Bibliometrics and scientometrics in SSH research assessments The application of bibliometric methods to the SSH proved to be problematic and yielded unsatisfying results, so that even bibliometricians caution from applying bibliometric methods to SSH disciplines (see for example,  Nederhof et al. , 1989; Glänzel, 1996; Lariviere et al. , 2006). This is because of several reasons, that we summarize in two main issues: coverage issues and methodological issues. Coverage issues arise for several reasons. First, in the SSH, chapters in books and monographs are more frequently used as publication channels and get cited more often than journal articles  (Hicks, 2004; Nederhof, 2006). This leads to severe coverage issues in the most important databases for bibliometric analyses, which are mainly or exclusively based on scholarly journals  (van Leeuwen, 2013).
Furthermore, even internationally oriented European journals are not covered well in the relevant databases compared with American journals  (Nederhof, 2006). Second, some SSH disciplines are characterized by a more pronounced national and regional orientation  (Nederhof, 2006). Nederhof states in his review of bibliometric monitoring in the SSH: "Societies differ, and therefore results from humanities or social science studies obtained in one country may not always be very useful to researchers in other countries"  (Nederhof, 2006: 83). Thus, even though the topics might be internationally relevant, this kind of output is less visible, as often written in the national languages, seldom covered in the bibliometric databases (see for example,  Chi, 2012) , or even published in other publication channels that are not covered at all (example, reports and other publications directed to national or regional readership).
Third, SSH scholars write not only for the scholarly readers but also for the lay public  (Hicks, 2004). This type of literature is usually not taken into consideration in evaluations and certainly not included in the databases used for bibliometric analyses. However, non-scholarly publications are an important part of SSH research and its societal impact. Methodological issues arise amongst others from the fact that citation behaviour is different in the SSH disciplines. The age of references is remarkably high. Glänzel noted for example in his analysis from 1996 that a 3-year citation window is too short. Given the distribution of the citations over time, almost a 10-year citation window would have to be applied, leading to an obsolete publication set for evaluation purposes  (Glänzel, 1996).
Improving the databases Considering that typical SSH publications (for example, books, proceedings, publications in local languages) are badly represented in current databases 3 , efforts have been made in several countries to improve coverage, especially in the countries with a performance-based funding model, like Spain, Norway, Denmark, Belgium (Flanders) and Finland  (Giménez-Toledo et al. , 2016). There was also an attempt to create a full-coverage bibliographic/ bibliometric database for Europe, but it did not result in an implementation of a European-wide database or standard  (Martin et al. , 2010). In parallel, the ERIH project intended to create a European journal list for the SSH to overcome the problems of under-representation of (European) SSH journals in the main bibliometric databases; however, the project faced strong opposition  (Andersen et al.
, 2009) , had to be remodelled (see  Lauer, 2016)  and was relaunched under the name ERIH Plus 4. Attempts to create publication databases suitable for the humanities have sometimes also been organized at the level of disciplines. The EERQI project included such a database for the educational sciences on the European level; it also investigated methods for using the data in research evaluations in a meaningful way  (Gogolin et al. , 2014; Gogolin, 2016). The database allows scholars to search for publications using keywords in one language, while retrieving results in all four languages covered in the database. Therefore, beyond evaluative purposes, centralized and systematic coverage of SSH production appears as an endeavour with multiple potential benefits, such as improving information retrieval for scholars and widening access to publications in multiple languages.
In all cases, consciousness is raising about the need to compile complete and interoperable databases of SSH scholarly and nonscholarly outputs, so as to gain accurate knowledge about productivity and publication behaviour in these very diverse disciplines. At the same time, the creation of such databases should go hand in hand with the development of standards regarding their use, including standards on how not to use them. An SSH approach towards bibliometrics and scientometrics Bibliometric analyses face many problems when applied to SSH disciplines  (Nederhof et al. , 1989; Archambault et al. , 2006; Nederhof, 2006; van Leeuwen, 2013). However,  Hammarfelt (2016: 115)  observes a shift from investigating coverage issues towards studying the characteristics of SSH publication practices and developing bibliometric approaches sensitive to the organization of SSH research fields.
This includes, but is not limited to, extending bibliometric analyses to non-source items  (Butler and Visser, 2006; Chi, 2014)  or the relatively new Book Citation Index  (Gorraiz et al. , 2013) , using other databases like Google Scholar  (Kousha and Thelwall, 2009)  or data from social media services, the so-called altmetrics  (Holmberg and Thelwall, 2014; Mohammadi and Thelwall, 2014; Zuccala et al. , 2015; Zuccala and Cornacchia, 2016) , analysing the inclusion in library catalogues  (White et al. , 2009) , exploring national databases with full coverage  (Giménez-Toledo et al. , 2016) , extending data to references in research grant proposals  (Hammarfelt, 2013)  or to book reviews  (Zuccala and van Leeuwen, 2011; Zuccala et al. , 2015) , exploring collaboration  (Ossenblok and Engels, 2015)  and publication patterns  (Chi, 2012; Ossenblok et al.
, 2012; Verleysen and Weeren, 2016). From a more pragmatic point of view, attempts are made to "weigh" the various outputs, such as journals or books in the SSH, similar to the journal impact factor, commonly used in the sciences  (Giménez-Toledo, 2016). While most of this research is done by bibliometricians and scientometricians, there are more and more SSH scholars still focusing on their SSH career and at the same time investigating research practices in their disciplines, such as citation practices  (Drabek et al. , 2015; Bunia, 2016) , the influence of databases  (Lauer, 2016) , the relation of bibliometric indicators to research practices  (Gogolin, 2016)  or career building and dissemination  (Williams and Galleron, 2016). Also, more methodological analyses are conducted by SSH scholars, such as the investigation of the inter-rater reliability of research assessment procedures  (Riordan et al.
However, the authors used this tool also in the multilingual search engine for the EERQI-database and found that it can enhance the search results (Sandor and  Vorndran, 2014b). Also for educational research,  Oancea and Furlong (2007)  developed criteria for research performance. They define educational research as practice-based and state that such research is not confined to scientificity (that is, discoveries of universal findings or even laws), impact or economic efficiency but also encompasses, amongst others, methodological and theoretical rigour, dialogue, deliberation, participation, ethics and personal growth. They argue that the evaluation of practice-based research has to cope with the entanglement of research and practice, which means that evaluation still has to reflect reasoning and knowledge but it has also to open up for more experimental modes of knowledge coming from within a context of concrete situations and first-person action.
siampi. eu). One of the major outcomes of the project is to have uncovered that many SSH scholars exercise a form of auto-censorship when it comes to declaring forms of research or outputs destined to a broader or non-scholar readership, these not being included in institutional forms of reporting or in CVs. This finding draw the attention of the project team upon the problems French scholars face when they come to declaring their work, since available fields in templates from AERES (the national agency for evaluation of higher education and research), or metadata structure in national repositories (such as HAL-Hyper Articles en Ligne) do not do justice to the large variety of outputs SSH research produces beyond the well-known books traditionally associated with the field. The project ultimately produced a more refined typology of outputs, which supported the creation of a pilot database destined to cope in a more appropriate way with the wealth and variety of SSH research.
Bottom-up initiatives at the European level The different assessment procedures applied at the university or national level, the initial exclusion of SSH research in the ERC Grant-schemes as well as the initial concerns of severe cut-backs for the SSH in the Horizon 2020 program  (König, 2016: 154-155)  led to a higher interest of SSH scholars in the topic of research assessment. As the sections above show, there is a rise in SSH research on research assessment and evaluation, leading to sessions or even tracks dedicated to SSH research assessment at international scientometric conferences like the ISSI 2015 (www. issi2015. org) or the STI 2016 (sti2016. org) conferences, or to an international conference dedicated exclusively to SSH research evaluation, RESSH 2015 (www. ressh. eu). Even more important, SSH scholars team up with scientometricians concerned about the state of SSH research assessment (often SSH scholars themselves) in a European association called EvalHum initiative (www.
Participants in the Action share data about SSH research and confront methodologies, resulting in coauthored publications but also in policy briefs, collections of best practices and, ultimately, guidelines for SSH research evaluation. ENRESSH seeks also to involve the different stakeholders having a say in assessment principles and processes, to progress towards adequate frameworks and practices of SSH research. The Action consists of 4 Work Groups. The first Work Group focuses on the conceptual frameworks for SSH research assessment and studies the SSH knowledge production processes and strategies as a basis for developing adequate assessment procedures reflecting the SSH research practices. It investigates SSH scholars' perceptions of research quality, peer review practices and national assessment practices.
The second Work Group is about societal impact and relevance of SSH research. It observes the structural requirements needed for a smooth transfer of SSH research to the society, the national policies towards transfer to socio-economic or NGO partners, proposes procedures to collect data about engagement with the society and measures to better value the SSH. The third Work Group concerns databases and the use of data for understanding SSH research. It builds standards for the interoperability of, and methods for integrating data from, current research information systems and repositories dedicated to the SSH, to allow comparability of SSH publishing practices in various countries. It analyses the characteristics of SSH dissemination channels, develops common rules for building databases, designs a roadmap for a European bibliometric database and develops alternative metrics for the SSH.
, 2009; Mair, 2016). The projects presented in this article show furthermore that if the assessment procedures adequately reflect the SSH research practices, scholars are ready to collaborate (for example,  Giménez-Toledo et al. , 2013; Ochsner et al. , 2014)  and to accept more easily research assessment, like in the Norwegian or German case  (Aagaard et al. , 2015; Sivertsen, 2016; Stierstorfer and Schneck, 2016). Full-coverage databases including all relevant document types are of value for scholarly work  (Gogolin, 2016; Sandor and Vorndran, 2014a, b)  and increase the visibility of humanities research production  (Aagaard et al. , 2015). While there are some degrees of convergence in some countries regarding their databases  (Giménez-Toledo et al. , 2016) , the conditions for full interoperability have yet to be discussed.
Therefore, taking the time to encourage bottom-up evaluation initiatives should result in better solving of modern societies' issues. Notes 1 Because it comes from SSH scholars and is clearly bottom-up in nature, we include, however, the initiative by  Oancea and Furlong (2007)  that was motivated by, but did not have a visible impact on, the RAE in the United Kingdom. 2 As mentioned in the introduction, we focus on European initiatives for coherence reasons and because of restrictions of space. 3 Despite the inclusion of (some) books in the commercial databases in recent years as well as the rise of networking sites also promoting bibliographic data, the undercoverage of certain disciplines and languages remains while technical challenges arise and issues of transparency persist  (Gorraiz et al.
Acknowledgements This article is based upon work from  COST Action CA 15137 'European Network for Research Evaluation  in the  SSH (ENRESSH) ', supported by  COST (European Cooperation in Science and Technology). Michael Ochsner  and  Sven E. Hug  would like to thank swissuniversities for their grant for the project " Application of Bottom-up Criteria  in the  Assessment of Grant Proposals of Junior Researchers " within the  "Programme P-3 Performances de la recherche en sciences humaines et socials ". Matching funds were provided by the  University of Zurich.
This US project quickly gained attention, and sparked the foundation of other national and regional LTER networks (e. g. China, Europe, Australia). This lead to the foundation of the global International LTER network in 1993 (ILTER)  (Kim, 2006; Mirtl, 2010; Vanderbilt and Gaiser, 2017) , which currently comprises 44 formal national LTER networks. ILTER provides the scientific expertise, a global-scale site network, and long-term datasets necessary to document and analyze environmental change. Larger scale case study areas (Long-term Socio-Ecological Research Platforms (LTSER)) are designed to support research on long-term humanenvironment interactions and transdisciplinary approaches. Recognizing that the value of long-term data extends beyond use at any individual site, the global ILTER network aims at making data collected by all (I)LTER sites broadly accessible to other investigators (e.
Models associated with CZOs applied significantly (Fisher test, p<0. 05) more data of eddy flux measurements (evapotranspiration and CO 2 ), root density, soil water content, soil temperature, bedrock, and soil texture and physics compared to models associated with LTER. Models using data of habitat mapping, biotic and biodiversity elements were associated much stronger with the LTER community. The majority of variables used in the models are sourced from on-site measurements (55% on average). The rest of the data (45%) is derived from other sources, mostly remote sensing (e. g. , MODIS), to a lesser extent modelled (e. g. , North American Land Data Assimilation System), external database (e. g. , FluxNet), or literature sources. The most common remotely sensed variables were of the biosphere, especially habitat mapping, leaf area index, vegetation structure and dynamics, above-ground biomass, but also include snowpack distribution and duration.
In terms of the modelled time scale, the long-time scales (centuries to millions of years) are mostly covered by models employed in the CZO community. This also lines well with the focus on management and predictive applications for LTER associated responses, while CZO applications focus more strongly on the description of the interplay between various processes. Another example of vegetation dynamics modelling using observation network data concerns forest dieback under climate change  (Breshears et al. , 2005). At an intensively studied site of the Drought-Induced Regional Ecosystem Response Network, after 15 months of depleted soil water content, > 90% of the dominant, overstory tree species died. This combination of detailed spatial-temporal observational data on tree condition, soil water content, precipitation and atmospheric conditions (temperature) allowed for data-driven development and validation of a regional model on droughtinduced vegetation changes.
Open issues and implications The LTER/CZO network sites monitor a wide range of environmental variables with long-term or at least regularly repeated measurements, expected to provide more reliable and robust results than single measurements that produce 'snap-shot' information only. The application of long-term monitoring data in predictive modelling provides a strong opportunity in the era of ESD modelling  (Parr et al. , 2002). Application of the rich data collected at LTER/CZO network sites should improve process understanding and enable the scientific community to address the challenges of validating Earth system models that integrate coupled processes. Although holistic integrated models at LTER and CZO sites are used to raise understanding of the coupled processes, cases are mostly restricted to individual sites and too limited in numbers.