Efektyvus elektroninių mokslo informacijos išteklių naudojimas: Modulis 12: Praktinės užduotys

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Kokia straipsnio struktūra ir sudedamosios dalys nurodytos reikalavimuose?

Atsakymas

Tarkim, kad parengėte straipsnį apie efektyvų saulės kolektorių naudojimą šildymui. Kuris iš pateiktų reikšminių žodžių geriausiai apibūdintų parengtą straipsnį:

tradiciniai energijos šaltiniai,
alternatyvūs energijos šaltiniai,
saulės energija,
kuras.

Atsakymas

Įvertinkite, ar toliau pateiktose santraukose yra pagrindiniai santraukos elementai: tyrimo aktualumas ir problema, tikslas, tyrimo klausimas, metodai, rezultatai, išvados, rekomendacijos. Atsakykite į klausimus:

ar visi santraukos elementai pristatomi tinkamai?
kurių elementų trūksta?
ar yra perteklinės informacijos?

Pirma santrauka.

Straipsnyje nagrinėjama smurto prieš moteris problema kaip diskriminacijos dėl lyties forma ir lyčių stereotipų pasekmė. Aptariamos kai kurios Jungtinių Tautų konvencijos dėl visų formų diskriminacijos panaikinimo moterims (CEDAW) ir Europos Tarybos konvencijos dėl smurto prieš moteris ir smurto šeimoje panaikinimo nuostatos, susijusios su smurtu prieš moteris kaip diskriminacijos forma. Taip pat analizuojami Jungtinių Tautų Moterų diskriminacijos panaikinimo komiteto sprendimai dėl seksualinio smurto, kuriuose Komitetas pabrėžė lyčių stereotipų įtaką ne tik smurtui prieš moteris, bet plačiąja prasme – Konvencijos garantuojamų moterų teisių realizavimui. Sprendimuose buvo išryškinta niokojanti stereotipų įtaka įgyvendinant vieną iš žmogaus teisių apsaugos pagrindų – teisę į veiksmingą teisinę gynybą ir nešališką bylos nagrinėjimą. (Michalovič, Ilona. Smurtas prieš moteris kaip diskriminacijos dėl lyties forma ir lyčių stereotipų pasekmė. Informacijos mokslai, 2017, 80, p. 50–60. DOI: <https://doi.org/10.15388/Im.2017.80.11671>)

Atsakymas

Antra santrauka.

Some scholars think that Open Science practices constrain researchers in ways that reduce their creativity, arguing, for instance, that preregistration discourages data exploration and so stifles discovery. In this article, we argue the opposite: Open Science practices are liberating and can foster creativity. Open Science practices are liberating because they (a) enable us to explore data transparently and comfortably; (b) reward quality, which is under our control, rather than outcomes, which are not; and (c) reduce the choke hold of needing to find “positive” results for career advancement. Open Science practices can foster creativity because they cultivate an open and flexible mind-set, create a more collaborative and constructive climate, and generate more accurate information and make it more accessible. In sum, Open Science liberates researchers more than it constrains them. (Frankenhuis, Willem E.; Nettle, Daniel. Open Science Is Liberating and Can Foster Creativity, 2018, 13 (4), p. 439-447. DOI: <https://doi.org/10.1177%2F1745691618767878>.

Atsakymas

Trečia santrauka.

The recent revolution in science and technology applied to medical research has left in its wake a trial of biomedical data and human samples; however, its opportunities remain largely unfulfilled due to a number of legal, ethical, financial, strategic, and technical barriers. Precision oncology has been at the vanguard to leverage this potential of "Big data" and samples into meaningful solutions for patients, considering the need for new drug development approaches in this area (due to high costs, late-stage failures, and the molecular diversity of cancer). To harness the potential of the vast quantities of data and samples currently fragmented across databases and biobanks, it is critical to engage all stakeholders and share data and samples across research institutes. Here, we identified two general types of sharing strategies. First, open access models, characterized by the absence of any review panel or decision maker, and second controlled access model where some form of control is exercised by either the donor (i.e., patient), the data provider (i.e., initial organization), or an independent party. Further, we theoretically describe and provide examples of nine different strategies focused on greater sharing of patient data and material. These models provide varying levels of control, access to various data and/or samples, and different types of relationship between the donor, data provider, and data requester. We propose a tiered model to share clinical data and samples that takes into account privacy issues and respects sponsors' legitimate interests. Its implementation would contribute to maximize the value of existing datasets, enabling unraveling the complexity of tumor biology, identify novel biomarkers, and re-direct treatment strategies better, ultimately to help patients with cancer. (BROES, S., LACOMBE, D., VERLINDEN, M. & HUYS, I. 2018. Toward a Tiered Model to share clinical Trial Data and samples in Precision Oncology. Frontiers in Medicine, 5, p. 1-13. <https://doi.org/10.3389/fmed.2018.00006>).

Atsakymas

Trečia santrauka.
(1) The recent revolution in science and technology applied to medical research has left in its wake a trial of biomedical data and human samples; however, its opportunities remain largely unfulfilled due to a number of legal, ethical, financial, strategic, and technical barriers. Precision oncology has been at the vanguard to leverage this potential of "Big data" and samples into meaningful solutions for patients, considering the need for new drug development approaches in this area (due to high costs, late-stage failures, and the molecular diversity of cancer). (2) To harness the potential of the vast quantities of data and samples currently fragmented across databases and biobanks, it is critical to engage all stakeholders and share data and samples across research institutes. (3) Here, we identified two general types of sharing strategies. (4) First, open access models, characterized by the absence of any review panel or decision maker, and second controlled access model where some form of control is exercised by either the donor (i.e., patient), the data provider (i.e., initial organization), or an independent party. Further, we theoretically describe and provide examples of nine different strategies focused on greater sharing of patient data and material. (5) These models provide varying levels of control, access to various data and/or samples, and different types of relationship between the donor, data provider, and data requester. (6) We propose a tiered model to share clinical data and samples that takes into account privacy issues and respects sponsors' legitimate interests. (7) Its implementation would contribute to maximize the value of existing datasets, enabling unraveling the complexity of tumor biology, identify novel biomarkers, and re-direct treatment strategies better, ultimately to help patients with cancer. (BROES, S., LACOMBE, D., VERLINDEN, M. & HUYS, I. 2018. Toward a Tiered Model to share clinical Trial Data and samples in Precision Oncology. Frontiers in Medicine, 5, p. 1-13. <https://doi.org/10.3389/fmed.2018.00006>).
(1) Aktualumas
(2) Tyrimo problema
(3) Tyrimo tikslas
(4) Metodai
(5) Rezultatai
(6) Išvados
(7) Rekomendacijos
Santraukos dalys yra gerai subalansuotos.

Pēdējās izmaiņas: otrdiena, 2019. gada 2. aprīlis, 11:39