We must all accept that science is data and that data are science, and thus provide for, and justify the need for the support of, much-improved data curation. (Hanson, Sugden, & Alberts) 
 
Researchers are producing an unprecedented deluge of data by using new methods and instrumentation. Others may wish to mine these data for new discoveries and innovations. However, research data are not readily available as sharing is common in only a few fields such as astronomy and genomics. Data sharing practices in other fields vary widely. Moreover, research data take many forms, are handled in many ways, using many approaches, and often are difficult to interpret once removed from their initial context. Data sharing is thus a conundrum. Four rationales for sharing data are examined, drawing examples from the sciences, social sciences, and humanities: (1) to reproduce or to verify research, (2) to make results of publicly funded research available to the public, (3) to enable others to ask new questions of extant data, and (4) to advance the state of research and innovation. These rationales differ by the arguments for sharing, by beneficiaries, and by the motivations and incentives of the many stakeholders involved. The challenges are to understand which data might be shared, by whom, with whom, under what conditions, why, and to what effects. Answers will inform data policy and practice. © 2012 Wiley Periodicals, Inc.

科研数据共享的挑战 (The Conundrum of Sharing Research Data)

Given the extraordinary growth in online documents, methods for automated extraction of semantic relations became popular, and shortly after, became necessary. This thesis proposes a new deterministic language model, with the associated artifact, which acts as an online Syntactic and Semantic Framework (SSF) for the extraction of morphosyntactic and semantic relations. The model covers all fundamental linguistic fields: Morphology (formation, composition, and word paradigms), Lexicography (storing words and their features in network lexicons), Syntax (the composition of words in meaningful parts: phrases, sentences, and pragmatics), and Semantics (determining the meaning of phrases). To achieve this, a new tagging system with more complex structures was developed. Instead of the commonly used vectored systems, this new tagging system uses tree-likeT-structures with hierarchical, grammatical Word of Speech (WOS), and Semantic of Word (SOW) tags. For relations extraction, it was necessary to develop a syntactic (sub)model of language, which ultimately is the foundation for performing semantic analysis. This was achieved by introducing a new ‘O-structure’, which represents the union of WOS/SOW features from T-structures of words and enables the creation of syntagmatic patterns. Such patterns are a powerful mechanism for the extraction of conceptual structures (e.g., metonymies, similes, or metaphors), breaking sentences into main and subordinate clauses, or detection of a sentence’s main construction parts (subject, predicate, and object). Since all program modules are developed as general and generative entities, SSF can be used for any of the Indo-European languages, although validation and network lexicons have been developed for the Croatian language only. The SSF has three types of lexicons (morphs/syllables, words, and multi-word expressions), and the main words lexicon is included in the Global Linguistic Linked Open Data (LLOD) Cloud, allowing interoperability with all other world languages. The SSF model and its artifact represent a complete natural language model which can be used to extract the lexical relations from single sentences, paragraphs, and also from large collections of documents.

/pdf/an-online-syntactic-and-semantic-framework-for-lexical-3alztwgqth.pdf

An Online Syntactic and Semantic Framework for Lexical Relations Extraction Using Natural Language Deterministic Model

The Research Data Alliance (RDA) is a global organization focused on developing the social and technical conditions for open data sharing and reuse, and fostering data-based innovation. As part of the RDA Europe 4.0 project, a national Croatian RDA node was established in Srce in 2019 (https://www.srce.unizg.hr/rda). In cooperation with the librarians from the University of Rijeka Library, the University of Split Library, the City and University Library Osijek, and the National and University Library in Zagreb, the handbook for researchers was prepared on how to handle research data for their efficient sharing and reuse.

/pdf/istrazivacki-podaci-sto-s-njima-prirucnik-o-upravljanju-26r67lhaov.pdf

Istraživački podaci - što s njima? : priručnik o upravljanju istraživačkim podacima

Osnovni je motiv objavljivanja znanstvenih i strucnih radova sto sira diseminacija autorovih spoznaja i dostignuca, o kojima u najvecoj mjeri ovi

Knjižničarstvo: glasnik Društva knjižničara Slavonije i Baranje od 1997. do elektroničke inačice

Iz velikog broja znanstvenih istraživanja danas proizlazi ogromna količina različitih podataka do kojih se dolazi s pomoću novih metoda i opreme, koji se pohranjuju u različitim oblicima i s kojima se upravlja na različite načine.1 Podatci iz istraživanja mogu sadržavati kvantitativne informacije ili kvalitativne tvrdnje koje istraživači prikupljaju i bilježe tijekom eksperimenta, promatranja, modeliranja, intervjua i sl., ili to može biti informacija proizišla iz postojećih dokaza.2 U područjima prirodnih znanosti najveći broj podataka prikuplja se promatranjem i eksperimentima, u društvenim znanostima vlastitim opažanjima ili preuzimanjem iz drugih javnih izvora (primjerice, podatci o ekonomskoj aktivnosti), a u humanističkim znanostima podatci se najčešće izvlače iz kulturne baštine, arhivskoga gradiva, artefakata i sl.3 Istraživački podatci (engl. research data) mogu biti objedinjeni i pohranjeni u tzv. sirovom ili obrađenom obliku u datotekama, mogu tvoriti modele, algoritme, protokole ili biti u obliku programirane računalne potpore analizi podataka.

/pdf/istrazivacki-podatci-hrvatskih-autora-na-platformi-web-of-4tn6rs0no3.pdf

Istraživački podatci hrvatskih autora na platformi Web of Science

/pdf/aplikacije-otvorenog-koda-za-koristenje-u-knjiznicama-3a36d7js3x.pdf

Jelena Bolkovac

Papers

Istraživački podatci hrvatskih autora na platformi Web of Science

Aplikacije otvorenog koda za korištenje u knjižnicama